Pathological Validation of the Role of Endoscopic Contouring in Head and Neck Cancers

by

Niousha Aflatouni

A thesis submitted in conformity with the requirements for the degree of Master of Health Science in Clinical Engineering

Institute of Biomaterials and Biomedical Engineering University of Toronto

© Copyright by Niousha Aflatouni 2017

ii

Pathological Validation of the Role of Endoscopic Contouring in

Head and Neck Cancers

Niousha Aflatouni

Master of Health Science in Clinical Engineering

Institute of Biomaterials and Biomedical Engineering

University of Toronto

2017

Abstract

Purpose: To develop and test methods of correlating whole-mount pathology of head and neck

(H&N) samples to pre-operative radiological imaging. The ultimate goal of this study is to

correlate pathology samples of H&N cancers to pre-operative computed tomography (CT)

imaging and navigated endoscopy.

Methods: Tongue and mandible samples from non-survival pig studies were used. We assessed

tissue shrinkages and proposed methods to enhance the registration accuracy. A slicing apparatus

was designed that generates consistent tissue sections to aid histology to pre-operative

registration. Finally, the whole registration pipeline was tested using intermediate steps.

Results: The fiducial registration error (FRE) from histology to pre-operative imaging was 1.94

mm for tongue and 1.07 mm for mandible.

Conclusion: We demonstrated the feasibility of registering pathology findings with volumetric

imaging. The registration error can further improve by utilizing techniques of deformable

registration and adding more landmarks in our specimens to calculate the registration error

reliably.

iii

Acknowledgments

Foremost, I would like to express my sincere gratitude to my supervisor, Dr. Robert Weersink,

for his enthusiastic encouragement, guidance, support, and useful critiques of this research work.

I also wish to thank my committee and examination members Dr. Jonathan Irish, Dr. Kazuhiro

Yasufuku, Dr. David Steinman and Dr. Naomi Matsuura for sharing their valuable expertise and

knowledge on this project.

I would like to greatly acknowledge and thank Jimmy Qiu for all of his time and effort he has put

into assisting me with the medical registration aspect of this project, especially for providing the

images in Chapter 5.

I am particularly grateful for the surgical assistance and clinical advice given by Dr. Wael Hasan.

I would also like to extend my thanks to Dr. Bayardo Perez-Ordonez and Dr. Theodorus van der

Kwast for their constructive feedback about tissue handling and pathology workflow.

I would like to thank the staff of the Surgical Pathology Lab and Pathology Research Program at

Toronto General Hospital, especially Sarah James and Melanie Peralta for enabling me to

observe their routine tissue handling techniques and providing solutions to my clinical/research

pathology inquiries.

I would like to extend my gratitude to the members of STTARR facility lab for acquiring

medical imaging, processing my specimens and providing technical support.

I also would like to thank members of GTx lab, for all of their supports, kindnesses and co-

operations during the time of my study.

Finally, I must express my deepest gratitude to my family for providing me with continuous

support, encouragement and understanding throughout the completion of this thesis work.

Thank you!

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Table of Contents

Contents

Acknowledgments.......................................................................................................................... iii

Table of Contents ........................................................................................................................... iv

List of Tables ............................................................................................................................... viii

List of Figures ..................................................................................................................................x

List of Acronyms ........................................................................................................................ xvii

Chapter 1 ..........................................................................................................................................1

1.1 Motivation ..................................................................................................................................1

1.1.1 Importance of Accurate Contouring in RT ........................................................................1

1.1.2 Improve Contouring by Incorporating Endoscopy ............................................................1

1.2 Correlating Medical to Histopathology Images .........................................................................2

1.2.1 Routine Pathology Practice ................................................................................................2

1.2.2 Challenges for Correlative Pathology ................................................................................3

1.3 Thesis Statement ........................................................................................................................3

1.4 Relevant Literature for Correlative Pathology ...........................................................................3

1.5 Overview of Image Registration ................................................................................................5

1.5.1 Evaluation Metrics .............................................................................................................6

1.6 Thesis Organization ...................................................................................................................7

1.6.1 Image Acquisitions for Tongue Specimens .......................................................................8

1.6.2 Image Acquisitions for Mandible Specimens ....................................................................8

Chapter 2 ..........................................................................................................................................9

2.1 Materials and Methods ...............................................................................................................9

2.1.1 Method for Assessing Tongue’s Shrinkage .......................................................................9

v

2.1.2 Method for Assessing Mandible’s Shrinkage ..................................................................10

2.1.3 Estimating the Maximum Registration Error for Mandible .............................................11

2.2 Results ......................................................................................................................................12

2.2.1 Shrinkage Evaluation of Tongue ......................................................................................12

2.2.2 Evaluating Impacts of Fixation and Decalcification on Mandible...................................12

2.2.3 Calculating the Effect of Shrinkage on Registration Error for Mandible ........................15

2.3 Discussion ................................................................................................................................16

2.3.1 Impacts of Fixation on Pigs’ Tongue Samples ................................................................16

2.3.2 Impacts of Fixation and Decalcification on Pigs’ Mandible Samples .............................17

Chapter 3 ........................................................................................................................................19

3.1 Materials and Methods .............................................................................................................19

3.1.1 Design Specifications .......................................................................................................19

3.1.2 Design Components .........................................................................................................20

3.1.2.1 Tissue Embedding Section .....................................................................................20

3.1.2.2 Tissue Slicing Section ............................................................................................21

3.1.2.3 Tissue Imaging Section ..........................................................................................24

3.2 Results ......................................................................................................................................25

3.3 Discussion ................................................................................................................................27

Chapter 4 ........................................................................................................................................29

4.1 Immobilizing Specimens during Slicing ..................................................................................29

4.1.1 Materials and Methods .....................................................................................................29

4.1.2 Results & Discussion .......................................................................................................30

4.2 Reducing a Tongue’s Boundary Deformations Before and After Surgery ..............................33

4.2.1 Materials and Methods .....................................................................................................33

4.2.1.1 Mold Preparation ...................................................................................................33

4.2.1.2 Image Co-Registration ...........................................................................................33

vi

4.2.2 Results ..............................................................................................................................34

4.2.3 Discussion ........................................................................................................................38

4.3 Reducing Boundary Deformations of a Resected Tongue Using Mold Fabrication ...............40

4.3.1 Materials and Methods .....................................................................................................40

4.3.1.1 Mold Fabrication ....................................................................................................40

4.3.1.2 Estimating Registration Error and Image Co-Registration ....................................43

4.3.2 Results ..............................................................................................................................45

4.3.2.1 Calculating the Registration Error based on Volume Change and Image

Registrations ..........................................................................................................47

4.3.3 Discussion ........................................................................................................................51

4.4 Fixing the scan orientation of the successive ex vivo mandible specimens .............................53

4.4.1 Materials and Methods .....................................................................................................53

4.4.1.1 ex Vivo Mandible Imaging .....................................................................................53

4.4.2 Results ..............................................................................................................................54

4.4.3 Discussion: Successive Mandible CT Scans ....................................................................57

Chapter 5 ........................................................................................................................................62

5.1 Materials and Methods .............................................................................................................63

5.1.1 Post-op to Pre-op Registration .........................................................................................63

5.1.2 Ex vivo to Pre-op Registration..........................................................................................64

5.1.3 Optical to ex vivo Registration ........................................................................................65

5.1.4 Histology to optical registration: ......................................................................................68

5.1.5 Histology to Pre-op Registration: ....................................................................................69

5.1.6 Role of Implanted Suture Fiducials .................................................................................72

5.2 Results ......................................................................................................................................73

5.2.1 ex vivo to Pre-op Registrations .........................................................................................73

5.2.2. Optical to ex vivo Registration ........................................................................................74

vii

5.2.3. Histology to Optical Registration ...................................................................................75

5.2.4 Registration Evaluation ....................................................................................................78

5.3 Discussion ................................................................................................................................79

Chapter 6 ........................................................................................................................................85

References ......................................................................................................................................87

viii

List of Tables

Table 2.1- Volume changes for total of n=8 tongue samples ....................................................... 12

Table 2.2- Percentage changes in volumes of mandibles after fixation and decalcification for

total of n= 5 samples ..................................................................................................................... 13

Table 2.3- The effect of shrinkage of registration error for mandible .......................................... 15

Table 3.1- Design specifications for our tissue slicer ................................................................... 19

Table 3.2-Design choices for our tissue slicer .............................................................................. 20

Table 3.3- Thickness measurements from the entire sections of a tissue block ........................... 26

Table 4.1- Trials for different alginate gel preparations ............................................................... 30

Table 4.2- Fixative Gels Tested for Tissue Embedding and Slicing ............................................ 31

Table 4.3- Mean and standard deviations of FRE and TRE values after point-based and intensity-

based registrations. The teeth are chosen as fiducials for calculating the FREs and the points on

tongues’ boundaries are chosen for TRE calculations .................................................................. 36

Table 4.4- Impacts of Normal Saline as percentages of volume change (mean ± SD) for a total of

n=4 tongue samples, collected from Tongue 1_Test over ~ 30 hours. The percent changes for all

the samples are compared with the initial volume at 0 hours. ...................................................... 47

Table 4.5- Impacts of normal saline as percentages of volume change (mean ± SD) for total of

n=4 tongue samples collected from Tongue 2_Test, over ~29 hours ........................................... 47

Table 4.6- Changes in the volume of the specimens from fresh to each of the Post-Saline and

Post-Formalin along with the percentages of the volume change ................................................ 48

Table 4.7- Volume changes, estimated maximum registration error caused by volume changes

and FRE between the fresh and post-formalin conditions. ........................................................... 48

Table 4.8- measurements for quantifying registration accuracy ................................................... 57

ix

Table 5.1- Summary of the registration steps for the tongue ........................................................ 70

Table 5.2-The summary of the registration steps for the mandible .............................................. 71

Table 5.3- Registration Evaluations .............................................................................................. 78

x

List of Figures

Figure 2.1- Tongue specimens on CT scanner: a) fresh at 0 hour, b) fixed at 10 hours, and c)

fixed at 26.5 ± 0.5 hours ............................................................................................................... 10

Figure 2.2- CT images of a pig’s mandible at a) fresh, b) fixed, and c) decalcified states (The

contrast adjustments for all three images were set at: Window: 5912 and Level: 2589) ............ 11

Figure 2.3- Volume changes post fixation after 10 hours and 26.5 ± 0.5 hours on tongue

specimens ...................................................................................................................................... 12

Figure 2.4- Effects of fixation and decalcification at different times for total of n= 5 samples ... 13

Figure 2.5- Volume changes with time after fixation of mandibles ............................................. 14

Figure 2.6- Volume changes with time after decalcification of mandibles .................................. 14

Figure 2.7- Histology images after 5 days of decalcification in RDO: a) shows the cellular

content of the bony region (H&E staining, magnification ×10), b) the arrow points at the area

where the normal squamous cell mucosa is expected to be seen; prolonged decalcification

created artifacts, as the blue dots, corresponding to the cell nuclei, are not visible in this region

(H&E staining, magnification ×20) .............................................................................................. 15

Figure 2.8- Decalcified mandible after 3 days in RDO Rapid Decalcifier. The white spots shown

by arrows indicate that the mandible is not yet fully decalcified. ................................................ 16

Figure 3.1- Gel/Tissue Box for embedding specimens ................................................................. 20

Figure 3.2- Illustration of the tissue embedding section from SolidWorks. Both removable walls

and spaces for fiducial placements are shown in a). The assembled view of the box is also

provided in b). ............................................................................................................................... 21

Figure 3.3- The exploded view showing the components of tissue slicing and tissue imaging

sections .......................................................................................................................................... 22

Figure 3.4- The assembled view of the apparatus in SolidWorks ................................................ 22

xi

Figure 3.5- 3D printed representation of the designed tissue slicer apparatus ............................. 22

Figure 3.6- Illustrating a series of actions from a) to f) that are used to generate and image a

single tissue slab: a) the tissue block was loaded into the slicer, b) a 3 mm cut was made, c) the

Removable Wall was removed, d) the generated section was also carefully removed, e) An

optical image was acquired from the exposed block face, f) the Gel-Block Advancer pushed the

remaining block forward for the next cut. .................................................................................... 23

Figure 3.7- Tissue slicer setup including the tissue imaging system ............................................ 24

Figure 3.8- Shows a) the checkerboard for scaling tissue images, and b) an illustrative example

of a tissue image as seen from the camera .................................................................................... 25

Figure 3.9- a) Measuring each block thickness was done using the location of arrows followed by

taking their mean and standard deviation across the whole block. The device thickness was also

measured from the same locations to ensure 3 mm thickness as shown in b). ............................. 25

Figure 3.10- Illustrating uniformity across tissue sections using the designed tissue slicer ......... 27

Figure 4.1- Results of tissue embedding gel-media for specimen sectioning. A) and b) show fixed

and fresh tongue specimens embedded in 5% agarose, while c) and d) show fixed and fresh

tongue samples embedded in alginate. Arrows in b) and d) show specimen detachments from the

gels. ............................................................................................................................................... 31

Figure 4.2- Showing the mold as it is positioned in the mouth during pre-op and post-op MR

scans to hold the boundaries of the tongue ................................................................................... 33

Figure 4.3- Illustrations of the pre-op (Left) and the post-op (Right) MR images of a pig’s tongue

before and after resection while immobilized using the mold during imaging (also referred to as

Case 1) .......................................................................................................................................... 34

Figure 4.4- Illustrations of the pre-op (Left) and the post-op (Right) MR images of a pig’s tongue

before and after resection without using the mold during imaging (also referred to as Case 2) .. 35

xii

Figure 4.5- An example of selecting fiducial points from pre-op (top row) and post-op (bottom

row) for performing the registration. Each point corresponds to a sharp edge of a tooth in the

lower jaw (teeth are not visible clearly). ....................................................................................... 35

Figure 4.6- An example of selecting 10 TRE points from the boundaries of the tongue after

registering post op ( bottom row) to the pre-op (top row) images ................................................ 36

Figure 4.7- Point based rigid registration of post-op on pre-op images, a) with and b) without

using the fixative mold inside the mouth. The gray regions in both images indicate the pre-op

image, while the green and red regions refer to the post-op images for Case 1 and Case 2,

respectively. .................................................................................................................................. 37

Figure 4.8- Intensity based rigid registration of post-op on pre-op images, a) with and b) without

using the fixative mold inside the mouth. The gray regions in both images indicate the pre-op

image, while the green and red regions refer to the post-op image for Case 1 and Case 2,

respectively ................................................................................................................................... 37

Figure 4.9- Intensity based deformable registration of post-op on pre-op images, a) with and b)

without using the fixative mold inside the mouth. The gray regions in both images indicate the

pre-op image, while the green and red regions refer to the post-op image for Case 1 and Case 2,

respectively ................................................................................................................................... 38

Figure 4.10- Showing the maximum dimensions of the specimen in a) that were used to segment

the resection area while assuming larger by 6 mm in b) x and c) y direction of the pre-op

imaging (Note: the specimen was flipped in a)) .......................................................................... 40

Figure 4.11- Screenshot of the 3D representations of a) the tongue model and b) the two part

mold designed based on the tongue model in OpenSCAD ........................................................... 41

Figure 4.12-The mold fabrication technique to reduce the boundary deformation of the tongue

during formalin fixation process: a) the two-part 3D printed tongue mold and b) the enclosed

mold holding the tongue in a 10% formalin container. Note that the parallel slots designed in the

mold allow for penetration of formalin inside the tongue. ........................................................... 42

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Figure 4.13- Illustrating a 3D segmentation of the specimen that helps to identify the edges along

the cut lines in a), and the 2D coronal representation of the same specimen on b). In both images,

the crosses and the white arrows show the identified tip in that image. ....................................... 44

Figure 4.14- The point selection in 3D Slicer from each of the axial view of a) pre-op and b) ex-

vivo images. The window to display the overlay during the selection process is shown in c).

Arrows show the selected corresponding point in pre-op and ex vivo images. ............................ 45

Figure 4.15- Illustrating the changes in volume of 4 tongue samples harvested from Tongue

1_Test, over ~ 30 hours in normal saline ...................................................................................... 46

Figure 4.16- Illustrating the changes in volume of 4 tongue samples harvested from Tongue

2_Test, over ~ 29 hours in normal saline ..................................................................................... 46

Figure 4.17- Pre-operative and ex vivo images of Case 3, after the specimen was fixed in the 3D

printed mold during formalin fixation. The ex vivo image in b) is registered and showed to be in

the reference frame of the pre-op image in a). An artifact is shown in a). The square around the

specimen in b) is due to the gel that the specimen was embedded in. .......................................... 49

Figure 4.18- Pre-operative and ex vivo images of Case 4, where the specimen was freely

immersed in the formalin fixation container. The ex vivo image in b) is registered and showed to

be in the reference frame of the pre-op image in a). The square around the specimen in b) is due

to the gel that the specimen was embedded in. ............................................................................. 49

Figure 4.19- Registered ex vivo on pre-op of Case 3. The overlay quality of the pre-op and ex

vivo boundary is compared based on the alignment of the white dots and red dots, respectively.

An indentation which is shown by the yellow dotted circle was an artifact, hence was ignored in

our assessment. ............................................................................................................................. 50

Figure 4.20- Registered ex vivo on pre-op image of Case 4. The quality of the registration was

compared based on the alignment of the white dots and the blue dots which represented the pre-

op and ex vivo outer boundaries, respectively. ............................................................................. 50

Figure 4.21- Techniques for creating the same scanning location for each of the ex vivo images to

facilitate their co-registrations: a) Aligning the CT emitted lights drawn on the specimen before

xiv

each scan, and b) Using the imprinted reference plate during each of the fresh, fixed and

decalcified CT acquisitions ........................................................................................................... 54

Figure 4.22-Showing CT scans of the a) fresh, b) fixed and c) decalcified states of a mandible,

which were obtained while positioned on the reference plate (The contrast adjustments for all

three images were set at: Window: 5912 and Level: 2589) ......................................................... 55

Figure 4.23- Unregistered overlay of a) fixed to fresh and b) decalcified to fresh mandible CT

scans with reference plate. The gray area shows the fresh mandible in both cases ...................... 55

Figure 4.24- Unregistered overlay of a) fixed to fresh and b) decalcified to fresh mandible CT

scans without the reference plate. The gray area shows the fresh mandible in both cases ........... 56

Figure 4.25- Illustrating the resulting mutual information based rigid registration of a) the fixed

on the fresh and b) the decalcified on the fresh mandible images. The fixed image is shown as

yellow in a) while the decalcified image is represented by red in b). In both a) and b) the CTs of

the fresh mandible are displayed as gray and are pointed by the arrows to show the

misalignments. .............................................................................................................................. 56

Figure 4.26- TRE point selections on a) fresh, b) fixed and c) decalcified mandible images ...... 57

Figure 4.27- Bone removal process. a) gel is used to imprint the soft tissue + mandible. b)

mandible is removed and it got substituted using the purple gel. c) after a few minutes the gel is

set and the block is ready for cutting. ........................................................................................... 59

Figure 4.28- Matching CT scans of the original mandible before and after removing the bone in

a) and b). The corresponding optical image after removing the bone is also shown in c). ......... 60

Figure 5.1- Illustrating a pipeline for histology to pre-operative image registration.................... 62

Figure 5.2- An illustrative example of selecting a suture point in 3D slicer. The point in each of

the corresponding axial, sagittal and coronal view is shown in both pre-op (top) and post-op

(bottom) images. ........................................................................................................................... 63

xv

Figure 5.3- Selecting the point correspondences from the surface rendering between fresh ex vivo

(left) and pre-op image (right). The points for performing the registration and for validating the

registration accuracy are shown by green and red, respectively. .................................................. 64

Figure 5.4- Surface registration performed using 4PCs algorithm. The resultant image is shown

from different angles, where the gray areas represent the area of resection as obtained from the

post-op to pre-op registration and the yellow regions show the ex-vivo image. ........................... 65

Figure 5.5-The quality of the stacked optical images is shown by verifying the straightness of the

cavity fiducials in sagittal and coronal views. Both a) and b) show the optical stacking for tongue

samples while c) shows the stacking for a mandible specimen. Axial views display the location

of each of the corresponding fiducials as seen from the camera’s view point, by red arrows. .... 67

Figure 5.6- Aligning the optical and ex vivo tongue images using the cavity fiducials that are

filled with MR contrast agents and ultrasound gel to be visible in both modalities (shown by red

lines). The blue lines show the corresponding suture points used to calculate the TRE after

performing the registration. .......................................................................................................... 68

Figure 5.7- Illustrative examples showing point selections on unregistered histology and optical

for tongue (top) and mandible (bottom) images. .......................................................................... 69

Figure 5.8- Configurations used for inserting the two types of suture fiducials inside the tongue

....................................................................................................................................................... 72

Figure 5.9- ex vivo to pre-op registration results from axial, sagittal and coronal viewpoints,

where a) and b) correspond to the point-based and the mutual information based rigid

registrations of the mandible and c) shows the point-based registration result of the tongue ...... 73

Figure 5.10- Optical to ex vivo registration of tongue specimen using the fiducial landmarks

placed in the gel (the cavity fiducials are not shown in this picture). ........................................... 74

Figure 5.11- Registered optical to ex vivo image of the mandible specimen using landmarks

identified within each corresponding slice ................................................................................... 74

Figure 5.12- Histology to optical registration of the tongue specimen. Overlay in a) shows a

larger area of histology than the underlying optical due to not cutting along the exact cross

xvi

section as the optical image, while b) shows minor missing pieces from the histology slides that

are identified by dashed ovals. ...................................................................................................... 75

Figure 5.13- Histology to optical registration of the mandible specimen. The overlap in a) shows

two missing pieces that are marked by dashed circles, while b) shows some degree of shrinkage

shown by a dashed oval and a fold which is pointed by an arrow. ............................................... 75

Figure 5.14- Suture fiducial representations on a histology image in a), where b) and c) show the

magnified (×5.1) non-removed and removed suture landmarks from the specimen, respectively.

The green dye is also visible around both markings in b) and c). ................................................ 76

Figure 5.15- Final optical to pre-op registration. .......................................................................... 77

Figure 5.16- Final histology to pre-op registration. ...................................................................... 77

Figure 5.17- Testing the appearance of suture fiducials soaked in 25% diluted barium sulfate

under microCT imaging ................................................................................................................ 83

xvii

List of Acronyms

RT Radiation Therapy

HNCs Head and Neck Cancers

NBF Neutral Buffered Formalin

CT Computed Tomography

MRI Magnetic Resonance Imaging

GTV Gross Tumour Volume

EDTA Ethylenediaminetetra-acetic acid

IHC Immunohistochemistry

FRE Fiducial Registration Error

TRE Target Registration Error

H&E Hematoxylin and Eosin

Pre-Op Pre-operative

Post-Op Post-operative

1

Chapter 1 Introduction

1.1 Motivation

1.1.1 Importance of Accurate Contouring in RT

About 75% of patients with Head and Neck Cancers (HNCs) will receive Radiation Therapy

(RT) as part of their primary treatment or as a supplementary treatment modality after surgery.1

Although RT technologies have significantly improved over the past few decades and allow the

delivery of highly conformal dose to the tumour, there is a critical need for precise 3D

delineation of target volume to avoid marginal misses of the tumour or overdose treatment to the

surrounding normal tissue.2 While radiation therapy planning predominantly makes use of

computed tomography imaging.3, 4

studies have demonstrated that contouring using a single

modality does not necessarily contain all the diagnostic information required for proper treatment

planning.5 For instance, the results from comparison of gross tumour volume (GTV) delineation

between different imaging modalities, such as computed tomography (CT), magnetic resonance

(MR) and fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) with the

macroscopic surgical specimen in pharyngolaryngeal squamous cell carcinoma, show that GTVs

delineated from the surgical specimen were smaller in volume yet were not fully encompassed

by the GTVs obtained from those imaging modalities.6 Histological examination also showed

that superficial tumour extension in the mucosa of the contralateral larynx as well as

extralaryngeal extension was missed in all three imaging modalities.6, 7

A similar study

investigating multimodality imaging among CT, MR and PET in oropharyngeal squamous cell

carcinoma has shown improved tumour contouring, yet no single imaging modality was able to

encompass all potential GTV regions.4 Therefore, due to the poor spatial resolution of 3D

volumetric imaging modalities to depict superficial tumour extension4, 6

, sole reliance on these

technologies to identify targets for GTV delineation is not recommended.7

1.1.2 Improve Contouring by Incorporating Endoscopy

Superficial tumour extent that is often missed by volumetric imaging modalities is often revealed

by performing a physical exam that includes endoscopy.7, 8

The current problem with this

approach is its dependency on clinicians’ memory which is prone to contouring bias. To be more

2

specific, to achieve comprehensive GTV delineation for head and neck RT, clinicians commonly

use endoscopy and physical examination and translate that information into the detected tumour

on the CT frame of reference. This process is done by recalling common anatomical fiducial

landmarks relative to the visible extent of disease.2, 8

To solve for contouring bias that this may

cause and uncertainty during GTV delineation, a novel technique has been developed and

proposed by Weersink et al. to quantitatively register contours of tumours identified in 2D

endoscopic images into the corresponding 3D data set.8 Margins currently selected for RT can be

between 5 to 10 mm9 depending on the clinician’s confidence in contouring and patient setup.

Hence the proposed technique’s aim is to show an improvement in contouring to be less than 5

mm to make this an effective and worthwhile platform for tumour delineation in HNCs.

To confirm the need to accurately contour superficial disease, a clinical trial is in preparation

comparing CT alone and CT with navigated endoscopy. These contours will be compared with

pathology findings in patients with primary cancers treated with surgery. For full and detailed

comparison of the pathology findings to the CT and endoscopic imaging, whole-mount

correlative pathology10

will be used. In preparation for this trial, the goal of this thesis is to

develop and test methods of correlating whole-mount pathology samples10

to pre-operative (pre-

op) CT imaging and navigated endoscopy.

1.2 Correlating Medical to Histopathology Images

Comparisons between the ground truth of histopathology images and the medical images used

for tumour delineation are useful for validating the accuracy of imaging modalities and to

promote the development of new imaging modalities that allow more accurate cancer detection

and localization.11-13

1.2.1 Routine Pathology Practice

Pathology practice is crucial for assessing margin in surgically resected sample and to assist with

the treatment decision of disease. Formalin-fixation, paraffin-embedding (FFPE) is the standard

method for tissue handling in almost all hospitals around the world.14

Both FFPE and

intraoperative frozen-section (FS) evaluation of surgical margins present challenges for accurate

correlation between pathology and medical imaging used for tumour delineations.11

During

routine pathological practice, a surgically resected specimen is fixed in a 10% Neutral Buffered

3

Formalin (NBF) solution for about 12 to 24 hours to preserve tissue morphology and prevent

degradation.15

Specimens then go through a gross examination following a piecewise

sampling/sectioning from the areas of interest. Next, the sectioned specimens will be sent for

paraffin embedment, microtome cutting and staining for evaluations of specimen margins.16

The

power of imaging the stained histology slides at extremely high resolution (~ 5 microns) enables

direct visualization of tissue structures at cellular levels.

1.2.2 Challenges for Correlative Pathology

Direct correlations between histopathology and medical images, however, are influenced by

some limiting factors, such as tissue deformation because of surgical manipulation, tissue

shrinkage during fixation or processing, and difficulties in obtaining consistent section thickness

and angles. Registration from flat 2D microscopic slides back to a full 3D tumour can also be

challenging.11

1.3 Thesis Statement

The overall objective of this thesis is to develop the best methods for performing correlative

pathology and to test the accuracy of registering the pathology samples to volumetric images (i.e

CT, MRI) of the test samples. For that purpose, the hypothesis states that by using whole mount

pathology techniques pathology findings of head and neck surgical samples can be correlated to

1) the resected samples and 2) the pre-operative images of patients before surgery, with

registration accuracy of less than 2 mm. Based on the margins currently selected for RT, this

level of accuracy is particularly desirable.

1.4 Relevant Literature for Correlative Pathology

Different methods have been studied to reduce the impact of factors stated in subsection 1.2.2

and to allow for a more accurate comparison between the histopathology and medical images.

The techniques can be categorized into two main parts of work: i) customized sectioning

apparatuses to reduce the tissue distortion during the process of specimen orientation,

embedment and sectioning, ii) registration techniques to correct for sample tissue distortion

during image processing.11

4

Whole-mount histopathologic processing is an important research method for observing cancer

biology and structure in 3 dimensions12, 13, 17

and allows the cellular level features to be related

back to medical imaging (i.e. MRI, CT and PET).6, 12, 13, 18

Studies comparing histopathology and

medical images have been conducted in different anatomical sites, such as head and neck,4,6,19

prostate and lung.13, 20

To the best of our knowledge, 3D registration of the images with the

pathology in tongue and mandible were not performed in any of the studies. The feasibility of

correlative pathology in laryngeal and hypopharyngeal cancer, however, was investigated

previously.13

Shrinkage artifact is often a source of error in co-registration studies and mainly results from

fixation and histologic processing of the cancer specimen. Studies have shown that the origin of

tissue also influences the magnitude of shrinkage and a specimen may remain unchanged, shrink

or even grow depending on the site of resection.12

Adequate fixation will enhance firmness, which can be an added benefit during sectioning but

inevitably causes tissue shrinkage, which leads to errors with any subsequent registration.11

In

response, Jhavar et al. developed a technique for cutting fresh prostate specimen that allows

tissue samples to be used for both diagnostic and molecular analysis study. However, the slices

tended to be uneven due to the force applied due to the semisolid consistency of the fresh

prostate.21

In a study conducted by Lam et al., each glossectomy specimen was pinned on a foam

board during formalin fixation to prevent shrinkage of the tissue. This technique was found to be

ineffective as discrepancies between the pathology and medical images were still observed

despite immobilizing the tissue during fixation.22

Several groups have studied various techniques to be able to match the orientation of the resected

specimen with its in vivo plane while sectioning the tissue. Use of patient-specific 3D printed

prostate molds based on pre-operative imaging, as an example, has been investigated.23, 24

It was

found that this technique may not always lead to a perfect fit of the prostate into the mold. For

example, if extracapsular extension was suspected extra tissue surrounding the prostate may be

resected or if the time between surgery and resection was long, the prostate may be larger than

the mold printed. Shrinkage and toughening of the prostate after formalin fixation can also cause

the prostate to not perfectly fit in the mold and become unstable during sectioning.23

Other

factors, such as the time and the cost associated with the production of 3D printed prostate-

5

specific molds, have also added to the limitations of using this technique.24

Other approaches

used image-guided specimen slicing technique based on placing fiducial markers inside the

prostate in combination with a magnetically tracked probe to enable the acquisition of

histopathology images parallel to the in vivo imaging plane.25-27

The technique may not be

clinically applicable as it requires about 11 hours of extra-clinical processing time to collect data

for image registration.28

Other groups have used a variety of gels, tested at different concentrations, to support the

specimen during the sectioning process.2, 10, 13, 29

The gel and concentration selected based on

providing adequate tissue support and maintaining a good adhesion to tissue during slicing.10

The

use of gel enabled researchers to introduce fiducial markers in the gel surrounding specimens to

estimate the accuracy of 3D specimen reconstruction, which was then co-registered with the

volumetric images.13, 30

Registration methods are often laborious and a number of different factors must be considered.

However, the accuracy of the registered images between histology and in-vivo datasets relies

mainly on the available landmarks because of the deformation that results from tissue

preparation after surgery.11

Since the specimen undergoes changes from after the surgery until

the preparation of the histology slides, a one-step registration process to map histology images to

the in vivo volumetric imaging will not be supported by the common information being shared

between the two image sets. Therefore, use of intermediate stages of high information content

imaging, is required to compensate for the needed degree of freedom (DOF) necessary to map

the two datasets.31

For example, taking high resolution images from block faces just before the

slice of interest is cut with microtome will provide enough information for the resulting histology

slice to be deformed back into its original geometry.31, 32

1.5 Overview of Image Registration

This section provides an introductory of image registration topic based on the most relevant

information to this thesis document.

The goal of image registration is to reliably find the geometric transformation such that the target

images can be aligned with the reference image. 33, 34

In medical applications, the image

registrations are typically done for three-dimension (3D) and sometimes two-dimension (2D)

images. Nature of transformation in image registration is divided into rigid and non-rigid

6

techniques. Rigid registrations consider linear transformation and use rotation and translation to

match a target image with a source image,35

while non-rigid registrations consider non-linear

transformation and normally apply to deformed structures (i.e. soft tissue).34, 36

Basis of

registration is categorized into extrinsic and intrinsic methods. In extrinsic methods visible

artificial markers are attached to the patient so that they could be easily detected in all the

imaging modalities. In contrast, intrinsic methods use information provided by the patients

including anatomical landmarks and voxel property in each image. Voxel property based

methods use mathematical or statistical criteria to align the intensity patterns of the target image

with those of the reference image.36

The most commonly used voxel similarity metrics include

mean squared intensity difference (MSD), cross correlation (CC) and mutual information (MI). 37

MI does not require prior segmentation; it is also referred to as the most accurate and robust

measure for 3D image registration, 36,37,38

especially for multimodal registration, where the

images are acquired from different imaging modalities.35, 38, 39

Therefore in this thesis document

we used mutual information based registration for the cases where we performed the registration

using the intensity of our images. We also used manual point-based rigid registration for the

majority of the cases. In addition, in some cases the combination of both methods were used to

perform manual initial alignment followed by optimizing the registration using the intensity

based rigid and non-rigid methods.

1.5.1 Evaluation Metrics

Metrics used to assess the registration accuracy of the registration error were fiducial registration

error (FRE), target registration error (TRE) and in some cases mutual information (MI).

FRE is the root mean square distance between the corresponding fiducial points after

registrations, where the fiducial points are used for the point-based registration process.40

TRE is

the root mean square distance between the corresponding target points after the registration,

where target points refer to points not used in the registration optimization but rather as a

validation of the registration accuracy.40

Mutual Information (MI) was used to evaluate how well the two images aligned.37

The method,

which was proposed by Viola et al.41

and Collignon et al.,39

is based on the maximization of the

statistically-based measure of voxel intensities.42

In other words, the alignment of images will be

such that they contain the maximum amount of information about each other.43

The mutual

7

information of images A and B derived from probabilistic measures of the intensity values and is

defined as:

𝐼 (𝐴, 𝐵) = ∑ 𝑝(𝑎, 𝑏)𝑙𝑜𝑔𝑝(𝑎, 𝑏)

𝑝(𝑎)𝑝(𝑏)𝑎,𝑏

Where 𝑝(𝑎) and 𝑝(𝑏) are the individual probability density functions (pdfs) and 𝑝(𝑎, 𝑏)is the

joint pdf of the gray values in the overlapping zone of the two data sets.38, 43

The method is a

measure of dependence between the gray values and assumes that when the images are correctly

aligned there is a maximal dependence between them. Similarly, the measure decreases if the

images aren’t well registered.43

Advanced Normalization Tools (ANTs),37

which is an open source command-line driven medical

image analysis platform (built on an Insight Toolkit (ITK) framework), was used, in this thesis,

to measure the MI criterion between the image pairs. ANTs’ implementation partly relates to the

work conducted by Mattes et al.,17

where they applied the negative of mutual information to

measure image discrepancy.37, 44

Therefore if the images are well aligned the mutual information

criterion between the target and the reference image would reach its minimum value.42

1.6 Thesis Organization

For this thesis a set of aims were specified to assess and reduce the challenges for tissue handling

and correlating histology images back to the pre-operative imaging. For that purpose, two

different sample types from pig oral cavities were considered: tongue and mandible. The

specimens were harvested from non-survival pig studies from the STTARR’s animal operating

room. Each aim will present a separate chapter of this thesis as described below.

In Chapter 2, the shrinkage rate for each of the sample types after fixation and decalcification is

assessed and the impact on registration error is calculated. Chapter 3 presents the design of a

tissue slicer apparatus that enabled quantitative sectioning of the specimens such that spatial

correlation of each slice with its corresponding slice in other imaging modalities was enabled. .

Chapter 4 demonstrates methods for reducing tissue deformation that occurs because of factors

such as specimen sectioning, surgical operation, and change of shape occurred during formalin

fixation. In addition, a method to expedite the co-registration between 3 CT scans of a mandible

8

specimen after each of the fresh, fixed and decalcified condition was tested. Finally, Chapter 5

presents the methods used for completing the registration process to map histology images back

to the pre-operative radiological imaging.

1.6.1 Image Acquisitions for Tongue Specimens

In this section, we describe the image acquisition methods in Chapter 4 and 5 that were further

used for image registrations.

The pre-operative and post-operative scan of two tongues were acquired using a 1.5 Tesla MRI

system using two different sequences, which varied over the course of studies as an attempt to

improve image resolution and contrast. The first acquisition included a transverse, coronal and

axial T1-weighted 2-D TSE sequence (repetition time (TR)/ echo time (TE) = 750/11 ms) with

voxel resolution of 0.8×0.8×2.6 mm3. The second improved MRI acquisition was a coronal T1-

weighted 3-D VIBE (repetition time (TR)/ echo time (TE) = 30/2.71 ms) with an isotropic voxel

size of 0.8 mm. For simplicity, whenever the MR sequences used in the text they will be

referred to as the 2-D and 3-D MRI, respectively.

For the ex vivo MRI scans the same 1.5 T machine was used. Also for both tongue cases the

sequence included a coronal T1-weighted 3-D VIBE (TR/TE = 40/3.12 ms) with an isotropic

voxel size of 0.4 mm.

1.6.2 Image Acquisitions for Mandible Specimens

In Chapter 5, the scans for pre-operative and post-operative of a mandible specimen were

acquired using a C-arm Cone Beam CT (PowerMobil, Siemens). CBCT reconstructions were

256×256×192 at 0.786 mm voxel size.

In both Chapter 4 and 5, the ex vivo scans of the mandible were acquired using a CT scanner

(eXplore Locus Ultra MicroCT, GE Healthcare) with volume size of 0.154 mm and acquisition

parameters of 80 kV and 50 mA.

9

Chapter 2 Shrinkage Assessment

Shrinkage is an inevitable change that happens as a result of formalin fixation and tissue

processing of specimens after resection. It is acknowledged as a source of error in co-

registration12

of medical images that may also lead to underestimation of tumour staging.45

Shrinkage rate has shown to be different depending on the tissue types and even the anatomical

sites where the same specimen is originated from. 12, 46

Several studies on head and neck,45

breast,47

esophageal,48

prostate,49

and cervical50

tumours have reported variations of shrinkage

rates after formalin fixation. A study investigating the shrinkage rate after formalin fixation on

100 head and neck cancer specimens, 49 of which were taken from oral cavity, reported an

average decrease in length, width and depth of 4.40%, 6.18% and 4.10%, respectively.45

In this chapter, we studied the shrinkage rates after formalin fixation and bone decalcification for

tongue and mandible specimens and estimated their influence on the co-registration errors. For

this purpose, volumes of the specimens following resection, formalin fixation and bone

decalcification were acquired using a CT scanner and compared.

2.1 Materials and Methods

2.1.1 Method for Assessing Tongue’s Shrinkage

Two freshly resected pig tongues collected from non-survival studies were divided into 4

quadrants. As shown in Figure 2.1, each quadrant was assigned a number (from 1 to 4) so that its

change can be followed relative to its position. In less than an hour after pigs’ death, the CT of

the fresh specimens were acquired using a CT scanner (eXplore Locus Ultra MicroCT, GE

Healthcare) with volume resolutions of 0.154 mm and acquisition parameters of 80 kV and

50 mA. Then, they were placed in 10% Neutral Buffered Formalin (NBF) (Sigma-Aldrich) for

fixation. Considering a 4 mm per hour penetration rate for formalin51

and given the small sizes of

our tissue samples (i.e. <45 mm along the largest dimension), the specimens were rescanned at

10 hours post-fixation. Then, another scan was obtained after 26.5±0.5 hours to be consistent

with the minimum number of 24 hours, for which the specimens are normally kept in formalin

solution during a routine pathology practice. ITK-SNAP,52

which is an open source software

10

application for medical image segmentation, was used to calculate the volume of each specimen

from its corresponding CT-scan using semi-automatic active contour segmentation technique.

Figure 2.1- Tongue specimens on CT scanner: a) fresh at 0 hour, b) fixed at 10 hours, and

c) fixed at 26.5 ± 0.5 hours

2.1.2 Method for Assessing Mandible’s Shrinkage

As a routine pathology practice in Toronto General Hospital, it was observed that bony

specimens were fixed for 2-3 days followed by decalcification for an average of 3 more days. In

this section, to assess the impacts of fixation and decalcification on volume, the measurements

were calculated after different time points of keeping the specimens in the aforementioned

solutions. For this, five mandibles were resected and carefully removed from the soft tissues

surrounding them. The bones were CT-scanned in less than an hour after resection and labelled

as CT-Fresh. Two of the specimens were placed in 10% Neutral Buffered Formalin (NBF)

(Sigma-Aldrich) for 3 days, another two were retained for 4 days, and one was stayed in the

solution for 5 days. After that, a second CT-scan was acquired (CT-Fixed) from each specimen.

Then, the specimens were rinsed with water and placed in a plastic container with RDO Rapid

Decalcifier (Apex Engineering Products Corporation), which is a strong decalcifier containing

hydrochloric acid. The choice of the decalcifier solution was purposely made to be identical with

the one routinely being used at Toronto General Hospital’s Surgical Pathology department. The

solution was poured until the specimens were covered, then after 3, 4, 5 and 6 days in RDO, a

third CT was obtained (CT-Decal). To confirm that full decalcification had taken place, samples

were physically tested to ensure they were flexible and soft. Further confirmation for proper

decalcification was observed from CT-Decal images. Figure 2.2 presents the changes in

appearances of different states of mandible from the corresponding single CT slice of each.

Then, ITK-SNAP was used to calculate the volume of the mandibles at each of the fixed, fresh

and decalcified stages.

11

To examine the validity of cellular morphology of the samples after decalcification, a sample

after 3 days of fixation and 5 days of decalcification was sent for paraffin embedment,

microtome cutting and H&E staining.

Figure 2.2- CT images of a pig’s mandible at a) fresh, b) fixed, and c) decalcified states

(The contrast adjustments for all three images were set at: Window: 5912 and Level: 2589)

2.1.3 Estimating the Maximum Registration Error for Mandible

The calculation was only done for the results that were obtained from keeping the samples in the

aforementioned solutions according to a routine pathology practice. As such, only the volume

changes after 3 days of formalin fixation and 3 days of decalcification were considered. The

dimension of the specimen after resection was calculated using ITK-SNAP. The overall

percentages of the volume change was obtained by calculating the changes of the specimen from

the fresh to fixed and the fixed to decalcified states. Then assuming that the relative change was

the same in each (x, y, z) direction, the new volume of the specimen post decalcification was

estimated. For this the average size of the two was considered as the size of the fresh specimen.

Then the percentage of the change in volume for maximum fixation and maximum

decalcification period was calculated. Next, the overall percentage change was calculated by

summing the obtained values, which then was used to calculate the new dimension. Based on

these changes in dimensions, the change in the distance between points opposite side of the

tissue sample was calculated using the root of the sum of squares (RSS). The RSS was used to

estimate the possible registration error due to changes in mandible volume.

a) b) c)

12

2.2 Results

2.2.1 Shrinkage Evaluation of Tongue

The shrinkage results for the tongues’ samples are provided in Figure 2.3 and Table 2.1.

Table 2.1- Volume changes for total of n=8 tongue samples

Conditions: Volume change percentages (mean ±SD) :

From fresh to fixed (10 hours) -1.16 ±0.02

Between fixed states (10 hours to 26.5±0.5

hours)

-0.82 ±0.01

From fresh to fixed (26.5±0.5 hours) -1.99 ±0.01

2.2.2 Evaluating Impacts of Fixation and Decalcification on Mandible

Figure 2.4 and Table 2.2 illustrate results of volume changes after 3, 4, 5 days of fixation, and 3,

4, 5 and 6 days of decalcification.

0

1000

2000

3000

4000

5000

1 2 3 4 1 2 3 4

Pig 1 (Post Formalin Volumes) Pig2(Post Formalin Volumes)

Vo

lum

e (

mm

3 )

Volume Changes for Tongue Samples

CT_Fresh (0 hours) CT_Fixed (10 hours) CT_Fixed (26.5±0.5 hours)

Figure 2.3- Volume changes post fixation after 10 hours and 26.5 ± 0.5 hours on tongue

specimens

13

Figure 2.4- Effects of fixation and decalcification at different times for total of n= 5 samples

Table 2.2- Percentage changes in volumes of mandibles after fixation and decalcification

for total of n= 5 samples

Conditions N1 N2 N3 N4 N5

From fresh to fixed -0.94% -6.93% -2.60% -1.45% -7.40%

From fixed to decalcified -11.91% -4.93% -4.73% -3.48% -2.74%

From fresh to decalcified -12.74% -11.52% -7.20% -4.88% -9.94%

0

10000

20000

30000

40000

50000

N1 N2 N3 N4 N5

4 Days NBF-3Days RDO

4 Days NBF-4Days RDO

3 Days NBF-5 DaysRDO

5 Days NBF-6Days RDO

Vo

lum

e (

mm

3 )

Shrinkage after Fixation and Decalcification

Fresh

Fixed

Decalcified

14

Figure 2.5 and Figure 2.6 illustrate the impacts of fixation and decalcification on mandible

volumes separately.

Figure 2.5- Volume changes with time after fixation of mandibles

Figure 2.6- Volume changes with time after decalcification of mandibles

15

Figure 2.7 represents a histology result after 5 days of decalcification followed by a 3 days of

fixation.

Figure 2.7- Histology images after 5 days of decalcification in RDO: a) shows the cellular

content of the bony region (H&E staining, magnification ×10), b) the arrow points at the

area where the normal squamous cell mucosa is expected to be seen; prolonged

decalcification created artifacts, as the blue dots, corresponding to the cell nuclei, are not

visible in this region (H&E staining, magnification ×20)

2.2.3 Calculating the Effect of Shrinkage on Registration Error for Mandible

Table 2.3- The effect of shrinkage of registration error for mandible

Condition Average Dimension between N1 and N3 (L × W × H)

Fresh Mandible 34.5mm × 43mm × 15mm

Post-decalcified Mandible 32.77mm × 40.85mm × 14.25mm

Registration Error (RSS) 2.86 mm

a) b)

16

2.3 Discussion

2.3.1 Impacts of Fixation on Pigs’ Tongue Samples

The 8 tongue samples from the two pigs showed a small overall shrinkage of 1.99 ±0.01% after

26 hours in 10% NBF. Studies on humans’ tongues, however, reported the shrinkage on tongues

that contained tumour to be significantly larger than what we obtained from pigs’ healthy

tongues. For example, D. Brotherstone et al. who compared tumour contours on freshly cut agar

blocks with their corresponding histology slides has reported a range of 12.48-33.80% of

shrinkage.12

Another example of such difference is a study conducted by Cheng et al, which

measured the intraoperative margin with the histopathology margin of tongue tumour and

reported 42.14% of shrinkage.53

One reason for such discrepancy in our finding with the

published results could be due to the differences in sample types and anatomies between the two

tongue models which can contribute to different shrinkage rate. This issue can be further

investigated by evaluating the shrinkage of different tongue samples taken from other large

animals (i.e. cows, monkeys). Also the difference between our processing methods for shrinkage

evaluation comparing to the other two studies can impact these variations as well. In our method

the volume difference was compared between the entire volume of each tongue sample pre and

post fixation, whereas, D. Brotherstone et al. compared the tumour contours between fresh slices

of agar blocks and their corresponding histology images.12

In contrast, Cheng et al, compared the

margins of the tumour between the intraoperative and histopathology measurements which

reported an even higher shrinkage rate.53

Another source of discrepancy could be due to the lack

Figure 2.8- Decalcified mandible after 3 days in RDO Rapid Decalcifier. The white spots

shown by arrows indicate that the mandible is not yet fully decalcified.

17

of tumour in our samples, while other studies had tumours in their tongue specimens. This might

be due to the development and growth of disorganized blood vessel networks in tumours that are

fundamentally different from normal tissue’s vascular network.54

2.3.2 Impacts of Fixation and Decalcification on Pigs’ Mandible Samples

The impact of formalin was investigated after 3, 4 and 5 days. According to Figure 2.4, Figure

2.5 and Table 2.2, the changes after 3 days of fixation for two of the samples were 2.60% and

1.45%. Then, 4 days of fixation resulted in 0.94% and 6.93% of shrinkage for two of the other

samples, while a higher 7.40% of shrinkage was experienced for the sample which stayed for 5

days in NBF. Therefore results show that the shrinkage rate of the specimens increased as they

stayed longer in formalin solution. Therefore to reduce the registration error caused by shrinkage

it is not suggested to keep the specimen for more than 3 days.

To the best of our knowledge, shrinkage rate as a result of prolonged decalcification of large

bony specimens (i.e. mandible) using RDO had not been reported previously. Considering a

routine pathology practice, the shrinkage rate was estimated to be 2.86 mm after 3 days in RDO,

while the mandible wasn’t yet fully decalcified, as showed in Figure 2.8. To further investigate

the shrinkage caused by decalcification with time, as well as the impacts of the solution on our

samples, we also tested samples after 4, 5 and 6 days in RDO. The results were illustrated in

Figure 2.4, Figure 2.6 and Table 2.2. Thus, as counter-intuitive as it may seem, the rate of

shrinkage decreases with prolonged decalcification. However prolonged decalcification by RDO

is strongly discouraged as it can cause serious deterioration of stainability, especially of nuclear

chromatin.55

The H&E stained histology results from our samples also showed artifacts due to

the prolonged amount of stay in RDO. The cell nuclei that are normally seen as blue dots under

H&E histology image aren’t present in the squamous cell mucosa of Figure 2.7b. This confirms

that the prolonged decalcification has affected the stainability of the cells. These images will be

uninterpretable to pathologists especially if there is a tumour involved. Therefore for future

reducing the time of decalcification is recommended, even though may not fully decalcify the

specimen. In addition, bone decalcification using RDO Rapid Decalcifier is not suitable for

immunohistochemistry (IHC) analysis as DNA may not be successfully retrieved as a result of

the treatment.55

An alternative method that can be used to circumvent this issue is to use EDTA

18

(ethylenediaminetetra-acetic acid), which is a chelating agents for decalcification. Alers et al.

and Liu et al. compared several decalcification agents and confirmed that EDTA has little or no

effect on tissue morphology, thus is a preferred method for decalcification. The disadvantage of

such technique, however, is the time-consuming process especially for large sample sizes, which

can take up to several weeks.55, 56

Therefore, for the planned clinical trial it is suggested to limit the time for formalin solution to a

maximum of 3 days and utilize EDTA instead of RDO for maintaining tissue morphology.

19

Chapter 3 Design and Assembly of a Robust Tissue Slicing Apparatus

Specimen sectioning from areas of interest is a part of routine pathology practice, however there

is a lack of spatial correspondence with respect to the pre-operative imaging. We designed a

slicing apparatus that generates consistent sections with known thicknesses from the whole

specimen to enable correlations with volumetric medical and histopathology imaging. Each

sliced section consists of a specimen and a gel that helps to maintain the orientation of the

specimens and reduces the deformation throughout the cutting action. The average thickness of

the cuts is 3 mm to provide stability during sectioning. Breen et al.57

and Orchard et al.58

have

also designed slicing apparatus that provided consistent sectioning. We included a similar built-

in photo-capturing unit as Breen et al.’s design, and have added a remote controlling unit to it. In

addition, we improved our device by designing an extra unit, that enables tissue embedding

separately.

3.1 Materials and Methods

The apparatus was designed using SolidWorks, which is a solid modeling computer-aided design

(CAD) software, and printed using Dimension 1200es SST 3D Printer located in Guided

Therapeutics Lab (GTx-LAB).

3.1.1 Design Specifications

The design specifications were provided in Table 3.1 below.

Table 3.1- Design specifications for our tissue slicer

Generated Gel Block

(L × W × H)

60 mm × 50 mm × 50 mm Ensuring the gel block is compatible

with the scanners’ sizes*

Slice Thickness 3 mm Provides stability during sectioning

Knife’s Spine

thickness:

0.9 mm Sharp and thin to reduce tissue

tearing during slicing

Camera-mount

adjustments: 360° Rotation, 30 mm Z

translation

Centering the specimen in camera’s

field of view (FOV)

Additional feature Detachable parts for deep cleaning

Additional feature Designated spaces for

inserting fiducial rods inside

the Gel/tissue box

Allowing registration of optical to ex

vivo imaging by aligning the

corresponding points identified in

both data sets

20

* CT scanner (eXplore Locus Ultra MicroCT, GE Healthcare) FOV = 14 cm in-plane and 10.2

cm axial; 1.5 T MRI (Aera, Siemens) bore diameter = 70 cm

The design choices were indicated in Table 3.2 below.

Table 3.2-Design choices for our tissue slicer

Dimensions

(L × W × H):

Tissue Box 80 mm ×70 mm ×70 mm Ensuring the gel block is

compatible with the

scanners’ sizes

Entire

Apparatus

460 mm × 68 mm × 160 mm Constituting other parts

Materials: ABSplus- P430

Thermoplastic

Available in the lab

Maximum traveling range of

the translation stage

14 mm -

Allowable size of fiducials: Diameter = 3mm, Length >

80 mm

Length: To be compatible

with the tissue box

An allowable number of

fiducials:

Up to 4 Allowing an “N” shape

configuration that enables

better identification of

corresponding slices

3.1.2 Design Components

The design was made up of 3 main compartments: 1) tissue embedding, 2) tissue slicing, and 3)

tissue imaging sections.

3.1.2.1 Tissue Embedding Section

The tissue embedding part consisted of a Gel/Tissue Box, which

had two Removable Walls functioning as its two sides (Figure

3.1). Once the walls were removed one could easily slide out the

gel block that contained the specimen. The walls included holes

for placement of up to 4 rods with diameters of 3 mm as fiducial

markers. Figure 3.2 shows two views of the tissue box for a better

clarity. The spaces for the fiducials could hold two straight and

two diagonal rods forming a horizontal “N” shape if observed

from each side. For the purpose of this thesis, we only used the two straight fiducials for the

Figure 3.1- Gel/Tissue Box

for embedding specimens

21

tongue and one straight fiducial during the mandible gel embedment. Before gel preparation,

these markers were inserted in their designated places. Then they were removed after the gel that

contained the specimen solidified in the box. As a result the formed cavity fiducials were either

left empty so they would show up in optical images (in case of the mandible) or filled with

contrast agents to provide additional MR visibilities (in case of the tongue specimens). The

cavities were filled with a mixture of Ultrasound Gel (Pharmaceutical Innovations, Inc., New

Jersey, USA) and Gadovist (Bayer Inc., Ontario, Canada). The recommended ratio of Gadovist

(=0.1 ml per body weight) was used, which was calculated to be about 0.6 microliters for 6

grams of ultrasound gel. The mixture provided good visibility of the fiducials under the T1-

weighted MR sequence59, 60

which was acquired in our study as described in section 1.6.1. The

purpose of these fiducials was to assist with matching the MR imaging planes with their

corresponding planes of optical images. In addition, the straight fiducials were used to quantify

the accuracy of the 3D stacking of the optical images.

3.1.2.2 Tissue Slicing Section

The tissue slicing part consisted of the following: 1) Base, 2) Translation Stage, 3) Cutting Bed,

4) Cutting Guides, 5) Gel-Block Advancer, and 6) Removable Wall, Figure 3.3 and 3.4.

a) b)

Figure 3.2- Illustration of the tissue embedding section from SolidWorks. Both removable

walls and spaces for fiducial placements are shown in a). The assembled view of the box is

also provided in b).

22

Figure 3.4- The assembled view of the apparatus in SolidWorks

The Base was designed large to be able to contain enough space for attaching a clamp for

securing the apparatus, while providing extra space for the operator’s hands to maneuver. The

two edges of the Cutting Guides were leveled with the edge of the Translation Stage (DTS25/M,

Figure 3.3- The exploded view showing the components of tissue slicing and tissue imaging

sections

Camera Mount

Extension 1

Extension 2

Removable Wall

Cutting Bed

Base

Gel-Block Advancer

Cutting Guides

Translation Stage Camera

Adjustment

Figure 3.5- 3D printed representation of the designed tissue slicer apparatus

23

Thorlabs Inc., New Jersey, USA), where the Cutting Guide was mounted on. That enabled the

relative movement of the two, which was controlled by an Adjustable Knob on the translation

stage to achieve the intended 3 mm slice thickness. The Translation Stage had a travel range of 1

mm for each full revolution and a precision of 0.3 mm which was measured by comparing the

actual and the expected values. Two cutting knives (CellPath Ltd.) with blade lengths of 250 mm

and 150 mm were used for slicing the gel blocks containing tongue and mandible specimens,

respectively. The Cutting Bed, that was compactly located in between the two Cutting Guides,

provided a secure place for slicing as the guides held the block firmly in place during the cutting

action. Figure 3.6 illustrates the process of generating tissue sections and imaging them. The

Removable Wall at the front of the tissue block provided an additional support during the slicing

action (Figure 3.6 b). Once removed (Figure 3.6 c), it allowed the operator to obtain pictures

(Figure 3.6 e) of the cut planes after sliding away each sectioned slab (Figure 3.6 d). The Gel-

Block Advancer manually advanced the gel block after each sectioned slab was removed such

that the block was positioned for making succeeding cuts (Figure 3.6 f).

a) b) c)

d) e) f)

Figure 3.6- Illustrating a series of actions from a) to f) that are used to generate and

image a single tissue slab: a) the tissue block was loaded into the slicer, b) a 3 mm cut was

made, c) the Removable Wall was removed, d) the generated section was also carefully

removed, e) An optical image was acquired from the exposed block face, f) the Gel-Block

Advancer pushed the remaining block forward for the next cut.

24

3.1.2.3 Tissue Imaging Section

The tissue imaging part, as shown in Figures 3.3 and 3.7,

consisted of the Camera Mount and the Extensions. The

length of the Extensions, which connected the Camera

Mount to the tissue slicing part, was drawn out based on a

few trials and errors so that the best field of view (FOV)

was achieved by the camera. Other components of this

section included a Canon DSLR (digital single-lens reflex)

camera, which was directly connected to a computer and

remotely controlled using the camera’s software application

called EOS Utility (Figure 3.7). This assumed there was no

camera movement that could be influenced by pressing any

button on the camera. The Camera Mount provided a

secure position for holding the camera, while enabling

rotation and n linear translation in Z axis to obtain a

centered view by the camera. The rotation was done using a

70 mm screw (shown in Figure 3.5), which was attached

to the camera from one end, also adjusted and secured by

the user from the other end. Camera calibration for scaling

the tissue images was done using a checkerboard which was attached to the front of the Gel-

Block Advancer, as shown in Figure 3.8 a) and b). The calibration was performed at the

beginning, before the cutting action started.

Canon DSLR

Camera

Live view

(EOS

Utility

Software)

Remotely

controlling the

camera

Figure 3.7- Tissue slicer setup

including the tissue imaging system

25

3.2 Results

To assess the uniformity across the entire range of sections, the thickness of each section was

measured using a caliper. The measurements were performed from 6 points on each generated

slab (as illustrated in Figure 3.9). Similarly the device thickness, from both sides, was also

measured prior to starting the cutting actions for every tissue block (Figure 3.9 b).

Therefore, the mean and standard deviation of 120 points from a tissue block, consisting of 20

tissue slab, was 2.74 ± 0.25 mm. Table 3.3 illustrates these variations. The table also includes the

average and standard deviation from every point on each side and from individual tissue slabs.

Figure 3.8- Shows a) the checkerboard for scaling tissue images, and b) an illustrative

example of a tissue image as seen from the camera

b) a)

Figure 3.9- a) Measuring each block thickness was done using the location of arrows followed

by taking their mean and standard deviation across the whole block. The device thickness was

also measured from the same locations to ensure 3 mm thickness as shown in b).

Gel/tissue section S

ide 1

Sid

e 2

a) b)

26

The average device thickness for 6 points on the machine was also 3.11 mm. The device

precision from the middle point measured on Side 1 was 0.02 mm and 0.18 mm from Side 2.

Due to the plastic property of the machine there were variations when measuring the device

thickness. The visual consistencies of the sections are also provided in Figure 3.10.

Table 3.3- Thickness measurements from the entire sections of a tissue block

Slice Thicknesses (mm)

Section

Numbers

Side 1

(below)

Side 1

(Middle)

Side 1

(Top)

Side 2

(Below)

Side 2

(Middle)

Side 2

(Top)

Avg SD

1 2.91 3.2 3.08 2.86 3.34 3.19 3.10 0.18

2 2.86 2.8 2.61 2.89 3.01 3.07 2.87 0.16

3 2.57 2.53 2.37 2.65 2.43 2.61 2.53 0.11

4 2.73 2.63 2.59 2.72 2.67 2.62 2.66 0.06

5 2.22 2.17 2.24 2.45 2.19 2.38 2.28 0.11

6 2.76 2.79 3.02 2.73 2.46 2.51 2.71 0.20

7 2.86 2.69 2.72 2.49 2.5 2.38 2.61 0.18

8 2.64 2.46 2.71 2.6 2.43 2.51 2.56 0.11

9 2.66 2.5 2.16 2.82 2.75 2.9 2.63 0.27

10 2.77 2.95 2.62 2.61 2.74 2.52 2.70 0.15

11 2.87 3.02 3.08 2.66 2.67 2.71 2.84 0.18

12 2.7 2.87 2.77 2.72 2.72 2.64 2.74 0.08

13 2.5 2.64 2.87 2.58 2.67 3.03 2.72 0.20

14 2.55 2.41 2.36 2.6 2.51 2.61 2.51 0.10

15 2.76 2.73 2.68 2.76 2.81 2.51 2.71 0.11

16 2.83 2.76 3.25 2.77 2.66 2.87 2.86 0.21

17 2.85 2.92 2.89 2.97 3.15 3.18 2.99 0.14

18 2.88 2.97 3.15 2.8 2.92 3.19 2.99 0.15

19 2.98 3.13 2.97 2.72 2.96 3.17 2.99 0.16

20 2.61 2.72 2.53 3.04 3.04 3.21 2.86 0.28

Avg 2.73 2.74 2.73 2.72 2.73 2.79

SD 0.18 0.25 0.31 0.15 0.28 0.30

27

3.3 Discussion

The whole-mount gross sectioning and imaging using the designed tissue slicer can be done

faster and easier than using the methods stated in some of the previous studies. Previous methods

required setting up the camera separately to obtain pictures from each of the sections after they

were cut.10, 13, 30

That required performing an additional transportation step to move the sections

from the slicing platform to the imaging platform to acquire the photos. The practice is not only

time-consuming, but may also require additional image registration step to stack and align the

images for 3D reconstruction. By contrast, our design makes use of a single platform that would

enable operators to perform the photo acquisition of the block faces in their fixed positions,

hence making the process much faster and more efficient. In addition, the pathology knives that

were used to section the blocks were more accessible and easier to operate as opposed to the

conventional meat slicers, which were utilized in some of the past studies.13, 30

One of the sources of inspiration for the creation of this design was a work conducted by Breen

et al..57

The two designs shared some similarities in slicing and imaging platforms, but include

major differences. For example, the cutting mechanisms were different. Unlike the tissue block

in our design, which was able to move forward using a Gel-block Advancer, their tissue block

was stationary and glued to the tissue slicing platform, so a linear translation stage was used

every time to bring the specimen forward. The second difference in their cutting mechanism was

the lack of an additional support at the front of the tissue block during the slicing action, which

could had been the cause of their experience of excess movement and tissue tearing during

slicing.57

Another difference was the non-existence of a separate tissue box with which we used

to obtain ex vivo MR imaging. The relatively small size of the tissue box also enabled us to

Cutting Knife

Generated Tissue Sections

Figure 3.10- Illustrating uniformity across tissue sections using the designed tissue slicer

28

obtain ex vivo imaging by using a microCT which had a smaller bore size. Finally, the

photographing section was not the same. We added to the robustness of the system by connecting

the camera to a computer and taking advantage of the software that allowed for features such as

remote shooting/controlling and live-view image displaying.

Also a design by Orchard et al.58

was another source of inspiration due to its proper specimen

support to prevent specimens from moving during the cutting action. In addition, the importance

of being able to disinfect the parts was emphasized in this design, which was also taken into

account in our design. The design, which is also commercially available, focused on improving

the precision of dissection and ensuring good surgical grossing practice.58

The commercially

available device wasn’t too sophisticated for comparison between medical imaging and histology

images, mainly because it lacked the ability to maintain the orientation of the specimens during

slicing.

In conclusion, our designed tissue slicer provided consistent quantitative sectioning, as shown in

Figure 3.10. The thickness, that was measured from 120 points from all the sections of a tissue

block (Table 3.3), was 2.74 ± 0.25 mm (mean ± SD), which was generated from the average

device thickness of 3.11 mm. The precision from both sides of the device was not the same (0.18

mm vs. 0.02 mm), which implies that the cutting guides were not accurately leveled. The

thickness variations from the measuring points on each side are higher at the top and lower at the

bottom of the tissue slices which could be due to the slicing action that gets distant from the

cutting guides as the operator cuts towards the bottom. Further improvements are needed to

reduce the thickness variations of each section to ensure accurate registration of the stacked

optical images to the ex vivo images (which will be further described in Chapter 5); one

suggestion is to machine our device using a more robust material such as metal to make sure that

the cutting space is separated uniformly throughout the cut lines from both sides. Another way

could be to motorize the cutting action by adding an electromechanical design to the system.

This way the thickness will not be influenced by the subjective force of the operator or the

flexibility of the knife during the sectioning process.

29

Chapter 4 Developing Fixative Techniques to Enhance Registration

Accuracy

Tissue deformation is an inevitable process that occurs in preparing tissue samples for pathology

analysis as a result of factors such as slicing the specimen during a grossing process, manual

forces applied during surgical operation and changes in the shape of the specimen after placing

in a container61 for formalin fixation. Deformations have shown to increase the registration

error62

, therefore being able to reduce tissue deformations during the handling process is

important to improve the registration accuracy. Section 4.1 presents a method for immobilizing

the specimen by using gels during sectioning with the designed tissue-slicer apparatus. Next,

section 4.2 illustrates the use of a fixative mold to reduce the influence of surgical operation on

deforming the outer-boundaries of the tongue. Then Section 4.3, demonstrates the design of a 3D

printed tongue-specific mold to reduce the deformation of the outer boundaries after resection.

In addition, a method was tested to facilitate the co-registration of successive ex vivo CT scans of

a mandible. Co-registration of images using intensity-based registration requires sufficient initial

alignment that is normally achieved using point-based rigid registration. The point-based

method, however, demands substantial time for manual interaction of an expert to identify the

landmarks.35

The proposed method expedites the registration performance by using a fixed-

position to scan the specimens every time. This method allowed the use of intensity based

automated registrations without the need for using point-based registration method initially.

4.1 Immobilizing Specimens during Slicing

4.1.1 Materials and Methods

Different concentrations of agar,10,12

alginate,29

and agarose30,13

were tested to generate whole-

mount specimen slices with 3 mm thickness. Bacteriological Grade agar (Bioshop, Burlington,

Ontario, Canada) was used with two different concentrations of 3% and 5%, separately. The

water was brought to its boiling point and then powder was added. The mixture was continuously

stirred by a magnetic bar while using a low-speed stirring mechanism to avoid foam formation.

Once the melting point of agar (i.e. 85-88°C) passed, the mixture was removed from the heater

and allowed to cool at the room temperature. After reaching 45-55°C, 10, 13, 17

it was poured into

30

the tissue box, followed by embedding the specimen in it. The tissue box was then placed inside

a 4°C cooler until the gel solidified. The same methodology was used for preparing a 5%

Biotechnology Grade agarose (Bioshop, Burlington, Ontario, Canada), while the melting range

for agarose was slightly different (i.e. 87-89°C). To improve the contrast between the gels and

the specimens, Zarrow et al. added food colors to the mixture.30

Following that idea, 2 drops of

blue tissue dye were also added during the mixing process.

For the preparation of Cavex CA 37 alginate (Unique Dental Supply Inc., Concord, Ontario,

Canada), which is commonly known as fast-setting dental impression material, 3 concentrations

at room temperature were tested, starting with the instructions provided by the manufacturer, as

shown in Table 4.1. The goal was to find a concentration that allowed enough time for the

embedment process while exhibiting a low viscosity for easy pouring into the mold. All of the

prepared gels were compared based on their rigidity, preparation time, and adhesion strength to

the specimen during slicing.

Table 4.1- Trials for different alginate gel preparations

Trial ID Powder (g) Water (ml)

Alginate (1) 21.2 46

Alginate (2) 21.2 60

Alginate (3) 21.2 80

4.1.2 Results & Discussion

The comparisons of the results between the gels are provided in Table 4.2. Numbers from 1 to 5

were assigned to quantify the rigidity and tissue adhesion between different gels, with 1

indicating the lowest and 5 the highest quality observed. Figure 4.1 shows some visual examples

of the best results obtained.

31

Table 4.2- Fixative Gels Tested for Tissue Embedding and Slicing

Gels Rigidity Preparation/

Setting Time

Tissue

Adhesion

Types of Specimens

Tested on

Viscosity

Level

3% Agar 2 >1 hour 3 Fixed tongue Low

5% Agar12

3 >1 hour 3 Fixed & fresh tongues Low

5%

Agarose13

5 >1 hour 5 Fixed & fresh tongues

and decalcified

mandible

Low

Alginate(1) Not tested ~1 minutes Not tested Gel only High

Alginate(2) Not tested < 5 minutes Not tested Gel only High

Alginate(3) 5 < 5 minute 4-5 Fixed and fresh

tongues

Low

Whole-mount tissue sectioning using diverse gel materials had been performed by several studies

in the past. Agarose, 2, 13

alginate29

and different concentrations of agar10, 12, 17, 18

had shown to be

the preferred media for embedding larynx, brain, tongue, breast, and lung. The gel preparations

are summarized in Table 4.2 with assessments of whether they provided adequate rigidity and

tissue adhesion in the lowest amount of time possible. Different concentrations of alginates were

also compared based on their low viscosity and setting time. The possibilities for immediate

embedment of the specimens after resections were also explored by testing a few samples in their

8 × 17 mm

b)

32 × 20 mm

d)

35 × 10 mm

c)

12 × 30 mm

a)

Figure 4.1- Results of tissue embedding gel-media for specimen sectioning. A) and b) show

fixed and fresh tongue specimens embedded in 5% agarose, while c) and d) show fixed and

fresh tongue samples embedded in alginate. Arrows in b) and d) show specimen

detachments from the gel.

32

fresh states. The freshly cut specimens can be useful in cases where techniques such as

cryosectioning and autoradiography are required.63

A 5% agar showed a better rigidity than its 3% concentration, while their adhesive abilities to the

tissues were the same. Due to the poor rigidity of the gel when tested on a fixed tongue, the 3%

agar was not further explored on a fresh sample.

5% agarose and a more diluted form of alginate, labeled as alginate (3), performed best in

rigidity during specimen sectioning. The assessments were performed qualitatively with a few

examples illustrated in Figure 4.1. Figure 4.1d showed some alginate detachments, pointed by an

arrow, as the knife pulled down on the fresh tissue during the sectioning process, while the

agarose achieved a better adhesion to the fresh tissue, as seen in Figure 4.1b. The size of the

fresh tissue embedded in the alginate, however, was larger than that in the agarose. This

difference in size could also have contributed to a weaker adhesion of the alginate to the tissue.

A practical drawback of the agarose was the substantial time needed to prepare the gel solution.

In addition to the time it takes for preparing the solution, the tissue embedment should be

delayed until the gel temperature drops to 45 to 55°C.10, 13, 17

Therefore for cases when

researchers would choose agarose for embedding fresh samples, the readiness of the gel must be

precisely coordinated with the completion of the surgery. On the other hand, alginate might be a

preferred solution because of its cold nature29

and fast-setting characteristics. The viscosity level

of the alginate as shown in Table 4.1 and Table 4.2 can be modified by the amount of water

added. In addition, the setting time of the alginate can be reduced or increased by adding hot or

cold water, respectively.29

Although the performance of alginate for embedding mandible

samples was not tested, it is expected to be the same, since the mandibles will be cut once they

are soft and decalcified.

33

Figure 4.2- Showing the mold as it is

positioned in the mouth during pre-

op and post-op MR scans to hold the

boundaries of the tongue

The Mold

4.2 Reducing a Tongue’s Boundary Deformations Before and After Surgery

4.2.1 Materials and Methods

4.2.1.1 Mold Preparation

Prior to pre-op imaging, alginate (1) with the amounts

shown in Table 4.1 was prepared. The mixture was then

poured onto aluminum foil that covered a flat, wide tray

that would fit into a pig’s mouth. Immediately after, the

tongue was laid gently on the tray and pressed against the

gel by closing the mouth. The gel (which we will refer to

as “mold” in this section) solidified in ~1 minute, after

which it was removed from the tray (i.e. detached

completely from the aluminum foil) and kept in the pig’s

mouth. An MRI scan was performed on the sample using

the 3D MRI sequence as described in subsection 1.6.1..

The pig then underwent a partial glossectomy followed by a post-operative (post-op) MRI scan

while keeping the mold in the mouth (Figure 4.2).

For comparison, the surgery was repeated on a second pig, but this time, the fixative mold during

the pre-op and post-op imaging wasn’t used. The pre-op and post-op MRI scan used a 2-D MRI

sequence as described in subsection 1.6.1. For simplicity, the first surgery where the mold was

used during the imaging will be referred to as Case 1 while the second surgery which was done

without the mold will be denoted as Case 2.

4.2.1.2 Image Co-Registration

The registrations were achieved in a two-step process using 3D Slicer64

and Elastix,65

which are

open source image registrations software platforms. Metrics used to assess the registration

accuracy included Fiducial Registration Error (FRE), Target Registration Error (TRE) and

Mutual Information.

34

Figure 4.3- Illustrations of the pre-op (Left) and the post-op (Right) MR images of a pig’s

tongue before and after resection while immobilized using the mold during imaging (also

referred to as Case 1)

The Mold

Tongue

before

Resection

The Mold

Tongue

after

Resection

For the tongue samples, each image pair was rigidly registered using a point-based registration of

coordinate systems in 3D Slicer. The points used for the registration were six corresponding

points on the teeth located on the lower jaw of each image. Next, using Elastix, the aligned

images were further refined by intensity-based rigid and deformable registration methods using

mutual information. Regions of interest on the pre-op images were masked to allow a more

accurate alignment by focusing the registration around the tongue regions and excluding other

tissue. The points for TRE were localized using ITK-SNAP,52

an open source software for 3D

medical image applications. Using this software, 10 additional points were visually identified

from the overlay of each pair of the image after registration. The points, which were selected

around the tongue boundaries, were used for calculating the TREs after each of the rigid and

deformable registrations. To allow a better comparison between the accuracy of alignments

before and after using the intensity-based method, the same points for TRE were selected after

each of the rigid and deformable registration.

4.2.2 Results

Two corresponding slices from the coronal views of the pre-op and post-op T1-weighted

sequence MR images were selected. Figure 4.3 shows the pre-op and post-op MR images that

were acquired while the tongue was fixed in the mold, labeled as Case 1. Figure 4.4 shows the

same image pairs from a different pig that was obtained without fixing the tongue (Case 2).

35

Tongue

before

Resection

Tongue

after

Resection

Figure 4.4- Illustrations of the pre-op (Left) and the post-op (Right) MR images of a pig’s

tongue before and after resection without using the mold during imaging (also referred to as

Case 2)

For both of the above cases, Table 4.3 provides the values for FRE after point-based rigid

registration (R.R.) and TRE after point-based and intensity-based rigid and deformable

registrations (D.R.) using mutual information. An illustrative example of the location of the

points is provided in Figure 4.5 and 4.6. Based on the lower TRE values for the rigid registration,

it is readily apparent that use of the pre-operative mold reduces the image registration error

between the pre-op and post-op images.

Figure 4.5- An example of selecting fiducial points from pre-op (top row) and post-op

(bottom row) for performing the registration. Each point corresponds to a sharp edge of a

tooth in the lower jaw (teeth are not visible clearly).

36

Figure 4.6- An example of selecting 10 TRE points from the boundaries of the tongue after

registering post op ( bottom row) to the pre-op (top row) images.

Table 4.3- Mean and standard deviations of FRE and TRE values after point-based and

intensity-based registrations. The teeth are chosen as fiducials for calculating the FREs and

the points on tongues’ boundaries are chosen for TRE calculations

Cases for

Registration

No. of points Evaluation Metrics Point-

Based R.R.

(mm)

Intensity-

Based R.R.

(mm)

Intensity-

Based

D.R.(mm)

Case 1 N=6 FRE 0.97

N=10 TRE 2.73±1.62 1.30±1.12 1.74±1.09

Case 2 N=6 FRE 1.61

N=10 TRE 4.05±2.71 3.56±2.83 1.65±1.55

The overlay results after point-based rigid registration for each of the two above cases are

provided in Figure 4.7a and Figure 4.7b, respectively.

37

Similarly, the intensity based alignments for both rigid and deformable registrations are provided

in Figures 4.8 and Figure 4.9, respectively.

Figure 4.7- Point based rigid registration of post-op on pre-op images, a) with and b)

without using the fixative mold inside the mouth. The gray regions in both images indicate

the pre-op image, while the green and red regions refer to the post-op images for Case 1

and Case 2, respectively.

Large

Deformation

of Post-Op

Tongue

a) b)

Pre and Post-Op Boundaries

Mainly Conform The

Mold

Figure 4.8- Intensity based rigid registration of post-op on pre-op images, a) with and b)

without using the fixative mold inside the mouth. The gray regions in both images indicate

the pre-op image, while the green and red regions refer to the post-op image for Case 1 and

Case 2, respectively

a) b)

Deformation

Still Exists but

Improved

Boundary

Conformation

Further Improved

The

Mold

38

4.2.3 Discussion

In order to identify the actual area which was resected during the surgery, an accurate

registration of post-op on the pre-op image is necessary. The resection area obtained from this

step will then be used in later steps for a more accurate registration of histology to pre-op

images. Registrations of soft tissues like tongue, however, are a challenge because of

deformation. To reduce this deformation, we imprinted the tongue on a mold prior to the surgery

and kept the mold in the mouth during imaging. We then compared the registration results with

the case where the mold wasn’t used. Pre-operative and post-operative image pairs of Case 1

and Case 2 were displayed in Figure 4.3 and Figure 4.4, separately. The selected anatomical

points for initializing the alignment between the two images were 6 teeth from the lower jaw of

both pigs. The FREs then were calculated to be 0.97 mm for Case 1 and 1.61 mm for Case 2. The

higher FRE that was achieved for Case 2 can be explained by the difference in a voxel size of the

image which was 2.6 mm in one dimension as opposed to 0.8 mm in all directions for Case 1. As

shown in Table 4.3, the mean and SD for TRE after rigid registration was smaller for Case 1

(=2.73±1.62 mm) than for Case 2 (=4.05±2.71 mm). This indicates that the use of the mold to

hold the tongue before and after surgery can reduce the deformation, resulting in lower

registration error.62

Figure 4.7a also confirms minimized post-operative deformation and a better

Figure 4.9- Intensity based deformable registration of post-op on pre-op images, a) with

and b) without using the fixative mold inside the mouth. The gray regions in both images

indicate the pre-op image, while the green and red regions refer to the post-op image for

Case 1 and Case 2, respectively

Excess warping in

areas that were

previously

conformed

Deformation

Still Exists but

Improved

a) b)

39

outer boundary conformity with the pre-op image, while a large post-operative deformation is

shown in Figure 4.7b. The registrations were then further refined by mutual information-based

rigid and non-rigid registration. After the rigid registration, the TREs were calculated using the

same boundary points as selected before. As expected, the reduced TRE values for both cases, as

shown in Table 4.3, indicates improved alignments after intensity-based rigid registration, while

the TRE for Case 1 is still lower since its boundary deformation was successfully inhibited by

the mold. Figure 4.8 also shows the improved boundary conformity for both cases after the

intensity based rigid registration. After the nonrigid registration, however, the TRE value for

Case 1 increased, while that for Case 2 decreased, (Table 4.3 and Figure 4.9). In Case 1, the TRE

is already quite low and any further changes may be adding to the noise in the image, suggesting

that in this case rigid registration may be sufficient. It may also be due to poorly controlled

distortion during the deformable registration.66

The registration could be improved by exploring

different deformable registration techniques to find a method where the user has more control

over areas that are desired for deformation.66

Furthermore, considering extra points around the

boundary when calculating the TRE for both cases can provide a better estimate of the

registration error since the registration accuracy improves with the number of fiducials.67

In

addition, the TRE evaluation was only done based on the corresponding points along the

tongues’ boundaries, which may not have been selected accurately. Since tongues do not possess

any landmarks within them, implanting fiducial markers pre-operatively can help with

performing and increase the reliability of the registration accuracy. Although pig tongues

exhibited large deformations in our experiments, the amount of deformation in human tongues

wasn’t investigated in our study. Other studies, however, referred to the human tongue as a

highly deformable organ.68

We demonstrated the feasibility to reduce the deformation of the

tongue such that the resected area can be identified more accurately which will ultimately aid in

performing a more accurate registration performance.

In order to use the method successfully during clinical trials, fabrication of a tray compatible

with the size of the human oral cavity will be necessary. In addition, to reduce the localization

error in selecting the fiducial landmarks it is suggested to use isotropic image acquisition

protocols that can be achieved using 3D image sequences of MRI scanners. Also, since TRE

varies throughout the volume of the image, to reduce the TRE for point-based rigid registration,

use of as many fiducial points as possible is suggested. 67, 69

To pick more reliable points, adding

40

synthetic fiducials within the tongue in the lateral direction (i.e. side to side) is also suggested.

Chapter 5 will discuss the insertion of the fiducials in more details.

4.3 Reducing Boundary Deformations of a Resected Tongue Using Mold Fabrication

4.3.1 Materials and Methods

4.3.1.1 Mold Fabrication

Using the 3-D MRI sequence of the pre-operative image of the pig’s head, as described in

subsection 1.6.1, , an area considered for resection was approximately identified and segmented

using ITK-SNAP. The segmentation then was used to make a two compartment mold for

enclosing the specimen during formalin fixation. Since there was no visible tumour in our pre-

operative tongue sample, the actual size of the resected specimen, as shown in Figure 4.10a, was

measured to identify the resection area on the pre-op image.

The segmented volume was larger than the actual size of the specimen by 6 mm, such that it was

expanded along the lateral and anterior-posterior direction of the tongue along which the surgical

cuts took place, Figure 4.10 (b) and (c). The segmentation along the superior-inferior direction

kept the same. The purpose of making a larger mold was to expedite the process of mold

fabrication. Typically the final step before making use of a functional 3D printed object using

fused deposition modeling (FDM) technology is to immerse the printed structure inside Sodium

Hydroxide solution for several hours to dissolve the support material that filled up between the

curvatures during the printing process. To eliminate the need for spending extra time for this to

a) b) c)

Figure 4.10- Showing the maximum dimensions of the specimen in a) that were used to

segment the resection area while assuming larger by 6 mm in b) x and c) y direction of the

pre-op imaging (Note: the specimen was flipped in a))

41

happen, the segmented volume of the tongue was increased so that a proper fit would be

achieved with the support material still in place.

The mold fabrication was achieved using OpenSCAD, an open-source script-based 3D CAD

(computer-aided design) software. The “parametric two-part mold generator” was originally

written by Jason Webb and made available through https://www.thingiverse.com/thing:31581 for

download. The script was then modified by adding openings that would allow for the penetration

of liquid (i.e. formalin) inside the mold. The dimensions of the mold were set to 50 mm×40

mm×30 mm. The 30 mm height allowed us to manually detach the mold from the support

material that was attached to the printing bed, without the need for immersing the object in the

Sodium Hydroxide solution to be detached from the bed. After the segmentation was completed,

it was exported as a surface mesh into ITK-SNAP52

and saved as a stereolithography (STL) file.

The STL file was then imported into Meshmixer (Autodesk, Inc.) to smooth the surface of the

tongue, as shown in Figure 4.11a. Then the surface model was imported into OpenSCAD to

complete the design, as shown in Figure 4.11b.

During the mold fabrication process, the resected specimen was kept in 0.9% Sodium Chloride,

commonly known as normal saline (Baxter Corporation, Mississauga, Ontario, Canada), which is

a near isotonic solution for clinical use (i.e. IV injection). This was done to keep the specimen

moist while expecting minimal volume change. To calculate the percentages of volume changes

on the tongue samples, two trials with 8 tongue samples were conducted, in advance. For that,

two pig tongues were used, labeled as Tongue 1_Test and Tongue 2_Test. Each tongue was cut

into 4 quadrants and soaked in normal saline over 30 and 29 hours, respectively. During these

Figure 4.11- Screenshot of the 3D representations of a) the tongue model and b) the two

part mold designed based on the tongue model in OpenSCAD

a) b)

42

times, the volume change was monitored at different intervals by CT acquisitions (eXplore

Locus Ultra MicroCT, GE Healthcare, London, ON, Canada) with 80 kV and 50 mA parameters

and 0.154 mm voxel size.

The overall time from segmentation of the pre-operative tongue until printing the mold took

about 24 hours. Although the cavity inside the mold was printed larger than the actual size of the

specimen, the 3D printed mold still required to stay in Sodium Hydroxide for an extra 7 hours to

achieve a proper fit. Despite our attempt to avoid this step, we believe this shouldn’t be an issue

during an actual clinical trial because normal saline will not be used. Instead, the specimen will

be placed in formalin directly after the surgery. After a total of 32 hours, the specimen was

removed from normal saline and CT scanned, using the same parameter as mentioned above. The

scan, labeled as Post-Saline Volume, was compared with the Fresh Volume, which was obtained

immediately after resection. All the CT scans in this section were performed using the same

parameters as mentioned above. Then the specimen was removed and placed in the mold, which

was now larger in x and y-direction, as shown in Figure 4.12a. The z-direction, however, which

represented the depth of the specimen, was sufficiently tight. This happened because we didn’t

initially enlarge the specimen in the z-direction so it provided adequate support to hold the

specimen in place. Therefore the specimen was placed such that its outer boundary conformed to

the outer boundary of the mold before the other half of the mold was closed. The mold was then

taped to ensure it remained close and immersed into formalin solution, as shown Figure 4.12b.

a) b)

10% NBF

Enclosed Mold

Figure 4.12-The mold fabrication technique to reduce the boundary deformation of the

tongue during formalin fixation process: a) the two-part 3D printed tongue mold and b) the

enclosed mold holding the tongue in a 10% formalin container. Note that the parallel slots

designed in the mold allow for penetration of formalin inside the tongue.

43

The tongue inside the mold was kept in formalin for 16 hours. Then, the mold was gently

removed from the solution and opened to confirm that the outer boundary of the tongue was still

conforming to the outer boundary of the mold during fixation. Next, the specimen was removed

and CT scanned to calculate the volume, which was labeled as Post-Formalin Volume. Next,

using the amounts specified for alginate (3), in Table 4.1, the tongue specimen was embedded in

a Cavex Creamy Alginate (Unique Dental Supply Inc., Concord, Ontario, Canada) inside our

designed Gel/Tissue Box and scanned using the ex vivo MRI scan sequence as described in

subsection 1.6.1.

For comparison, another partial glossectomy was done on a second pig following a pre-operative

MR scan using the 2-D MRI sequence as described in subsection 1.6.1. This time, however, the

specimen was CT-scanned to calculate the Fresh Volume measurement. Then it was placed

directly into formalin solution without the use of any fixative mold. After 48 hours the specimen

was embedded in a 5% agarose gel as described in section 4.1.1, and MRI scanned using the

same ex vivo MRI sequence as described in subsection 1.6.1. The volume calculated from the

scan was also labeled as Post-Formalin Volume. For simplicity, the first method where the

specimen was kept in a 3D printed mold during formalin fixation was referred to as Case 3,

while the second method was denoted as Case 4.

4.3.1.2 Estimating Registration Error and Image Co-Registration

The maximum registration error due to the volume changes was estimated by assuming that the

relative tissue expansion or shrinkage was the same in each (x, y, z) direction. Based on these

changes in dimensions, the change in the distance between points opposite side of the tissue

sample was calculated using the root of the sum of squares (RSS). The RSS was used to estimate

the possible registration error due to changes in tissue volume. The dimensions and volume

changes of the specimen after each of the post-saline and post-formalin states were calculated

using ITK-SNAP.

The two different tissue handling methods were compared by co-registering their ex vivo to their

pre-operative MR images. The registrations were performed in 3D Slicer64

using fiducial based

rigid registration. The landmarks to perform the alignments were selected to be the four edges

found along the cut lines. To ensure that the closest locations for selecting the landmarks were

picked, each ex vivo image was segmented using the semi-automatic segmentation feature in

44

ITK-SNAP52

to obtain a 3D representation of the specimens. The edges of the specimens from

the tip, left and right, were then identified on their 3D segmentation. Consequently, they were

localized in the 2D representation of the image in each of the coronal, axial and sagittal direction.

Figure 4.13a illustrates the 3D segmentation of the specimen along with the locations of the

edges, which were identified by white arrows. Figure 4.13b shows an example of localizing an

edge location (i.e. the tip) in a 2D coronal view corresponding to the cursor location (blue dotted

lines) selected in its 3D image.

3D Slicer was used to perform the landmark registrations, with the pre-op image selected as the

baseline image and the ex vivo image chosen as the moving image. The landmarks selected for

this section were the edge points of the tongue. The edge points, which defined at the

intersections between the outside of the tongue and the cut lines, were simply recognized in the

ex vivo image. One of the edge points, which was easy to identify in both images, was selected as

the first landmark and considered as the reference point (i.e. the tip).Next, in ITK-SNAP the

number of the slice counts between that reference and a second edge point was calculated in the

ex vivo image. Then, that number was used in 3D Slicer to calculate the length of the ex vivo

specimen from the reference to the second point. Hence, by knowing the length between the two

points and the slice thickness of the pre-op image the location of the second point on the pre-op

image can be calculated and selected. Figure 4.14a shows the selection of one of the edge points

in the pre-op, and Figure 4.14b represents its corresponding location in the ex vivo image. The

Figure 4.13- Illustrating a 3D segmentation of the specimen that helps to identify the edges

along the cut lines in a), and the 2D coronal representation of the same specimen on b). In

both images, the crosses and the white arrows show the identified tip in that image.

a) b)

Tip Tip

45

registered images are also shown in Figure 4.14c. Similarly, the locations of the other three

points were found in 3D Slicer. Then the distance between the homologous points after

registration was calculated and reported as the FRE. The point selection to align the 2 images,

however, was repeated 3 more times to calculate the mean and standard deviation for the FRE.

4.3.2 Results

The impact of normal saline on volume change was studied for two test-tongues, each of which

was cut into 4 quadrants. Figure 4.15 and Figure 4.16 illustrate the results for Tongue1_Test and

Tongue2_Test, respectively.

a) Pre-Op

a) Ex-Vivo

C) Registered

Figure 4.14- The point selection in 3D

Slicer from each of the axial view of a)

pre-op and b) ex-vivo images. The window

to display the overlay during the selection

process is shown in c). Arrows show the

selected corresponding point in pre-op and

and ex vivo images.

46

Figure 4.15- Illustrating the changes in volume of 4 tongue samples harvested from Tongue

1_Test, over ~ 30 hours in normal saline

Figure 4.16- Illustrating the changes in volume of 4 tongue samples harvested from Tongue

2_Test, over ~ 29 hours in normal saline

Also, Table 4.4 and Table 4.5 show the numerical results as percentages of volume change for

each of the Tongue 1_Test and Tongue 2_Test, respectively.

0

1000

2000

3000

4000

Sample 1 Sample 2 Sample 3 Sample 4

Vo

lum

e (

mm

3)

Tongue 1 Samples

Impacts of Normal Saline on Volume Change for Tongue_1

0 hour

4 hours, 25 min

9 hours, 25 min

21 hours, 25 min

30 hours, 20 min

0

1000

2000

3000

4000

Sample 1 Sample 2 Sample 3 Sample 4

Vo

lum

e (

mm

3)

Tongue 2 Samples

Impacts of Normal Saline on Volume Change for Tongue 2_Test

0 hour

9 hours, 15 min

18 hours, 45 min

29 hours, 20 min

47

Table 4.4- Impacts of Normal Saline as percentages of volume change (mean ± SD) for a

total of n=4 tongue samples, collected from Tongue 1_Test over ~ 30 hours. The percent

changes for all the samples are compared with the initial volume at 0 hours.

Duration Percentages of Volume Change (mean ± SD) for n = 4 samples

4 hours and 25 min 1.30±0.02

9 hours and 25 min 0.48±0.02

21 hours and 25 min 3.37±0.02

30 hours and 20 min 5.45±0.02

Table 4.5- Impacts of normal saline as percentages of volume change (mean ± SD) for total

of n=4 tongue samples collected from Tongue 2_Test, over ~29 hours

Duration Percentages of Volume Change (mean ± SD) for n = 4 Samples

9 hours and 15 minutes 6.48±0.01

18 hours and 45 min 8.96±0.01

29 hours and 20 min 14.48±0.02

4.3.2.1 Calculating the Registration Error based on Volume Change and Image Registrations

Table 4.6 shows the volume changes that our samples experienced due to the placements in

saline and formalin fixation solutions. Case 3 stayed 32 hours in saline followed by 16 hours in

formalin solution, while Case 4 directly placed in formalin for 48 hours.

48

Table 4.6- Changes in the volume of the specimens from fresh to each of the Post-Saline

and Post-Formalin along with the percentages of the volume change

Conditions Case 3 Case 4

Fresh Volume (mm3) 3725 4620

Post-Saline Volume (mm3)- after 32 hours 4195 -

Post-Formalin Volume (mm3)- after a total of 48 hours

post- resection

3921 5083*

Volume Change from Fresh to Post-Saline (%) 12.62% -

Volume Change from Post-Saline to Post-Formalin (%) -6.53% -

Overall Volume Change from Fresh to Post-Formalin

(%)

5.26% 10.02%

*This value was calculated from the ex vivo MR scan, while the other volume calculations were

based on CT scans.

The maximum registration error as a result of the final volume change along with the mean and

standard deviation of the FREs are shown in Table 4.7 below.

Table 4.7- Volume changes, estimated maximum registration error caused by volume

changes and FRE between the fresh and post-formalin conditions.

Conditions Case 3 Case 4

Fresh (Maximum Dimensions) 35 mm × 23mm × 14mm 31.25 mm × 23.37 mm ×

16.61 mm

Post-Formalin (Maximum

Dimensions)

35.6mm × 23.40mm ×

14.24 mm

32.26 mm × 24.13 mm ×

17.15 mm

Registration Error (RSS) 0.76 mm 1.37 mm

FRE (mm) (N=4) 3.17±0.30 4.12±0.63

49

Figure 4.17 shows a) the pre-op and b) the ex vivo MR images of Case 3 after the registration,

separately. Figure 4.18 shows a) the pre-op and b) ex vivo image of Case 4 whose specimen was

immersed freely in a formalin container during fixation. Both of these ex vivo images, as

displayed, are registered in their pre-operative reference frame.

Figure 4.19 and Figure 4.20 show the overlay of the ex vivo on the pre-op image for both cases,

separately. In each of those figures, the white dots indicate the outer boundary of the underlying

pre-op image, whereas the red dots in Figure 4.19 and the blue dots in Figure 4.20 indicate the

outer boundary of the corresponding ex vivo images.

a) b)

Figure 4.18- Pre-operative and ex vivo images of Case 4, where the specimen was freely

immersed in the formalin fixation container. The ex vivo image in b) is registered and

showed to be in the reference frame of the pre-op image in a). The square around the

specimen in b) is due to the gel that the specimen was embedded in.

a) b)

Figure 4.17- Pre-operative and ex vivo images of Case 3, after the specimen was fixed in the

3D printed mold during formalin fixation. The ex vivo image in b) is registered and showed

to be in the reference frame of the pre-op image in a). An artifact is shown in a). The square

around the specimen in b) is due to the gel that the specimen was embedded in.

Artifact

50

Figure 4.20- Registered ex vivo on pre-op image of Case 4. The quality of the registration

was compared based on the alignment of the white dots and the blue dots which

represented the pre-op and ex vivo outer boundaries, respectively.

Figure 4.19- Registered ex vivo on pre-op of Case 3. The overlay quality of the pre-op and

ex vivo boundary is compared based on the alignment of the white dots and red dots,

respectively. An indentation which is shown by the yellow dotted circle was an artifact,

hence was ignored in our assessment.

Artifact

51

4.3.3 Discussion

The impact of normal saline on tissue volume over time was tested on 8 samples that were

harvested from two different pig tongues. The results, as displayed in Figure 4.15 and Figure

4.16, indicate that as the resected specimens stayed longer in normal saline, the volume of the

specimens increased. Table 4.4 and Table 4.5 show volume expansions of 5.45±0.02% for

Tongue 1_Test and 14.48±0.02% for Tongue 2_Test over ~30 and ~29 hours, respectively. The

difference between the expansion rates of the two tongues was large, hence more tongue samples

from different pigs were needed to confidently make statements about the expansion rate caused

by saline. Although, tongue samples expanded, which means an additional volume change

besides formalin solution, this shouldn’t have any negative impact for the planned clinical trials

because as a routine pathology practice large specimens after surgery are directly transferred into

formalin solution for fixation. For our experiment, however, since the pre-operative image of the

pig tongue prior to the date of the surgery wasn’t available, we used normal saline to retain the

moisture of the specimen until the fabrication of the mold was completed.

The volume for the ex vivo specimen in Case 3 expanded by 12.62% after 32 hours in normal

saline and shrank by 6.53% after 16 hours in formalin solution, as shown in Table 4.6. The post-

saline expansion of the Case 3 was close to the Tongue 2_Test expansion results after 29 hours.

The volume change for Case 4 also showed a 10.02% expansion after formalin fixation.

Although in Chapter 2 we demonstrated insignificant shrinkages (~2%) of tongue samples as a

result of formalin solution, the 10.02% of expansion that we obtained for Case 4 contradicts the

previous findings. This inconsistency can be the result of not using the same imaging modality

for both measurements. Initially, Case 4 was CT scanned to calculate the volume of the fresh

specimen, but after formalin fixation, the embedded specimen inside the gel-block was MR

scanned. Semi-automatic segmentation then was used for both images to calculate the volume.

For future studies it is highly suggested to use the same imaging modality when calculating the

volume, as the reliability and quality of the result of segmentation also depend on the imaging

modality used besides other factors.70

Assuming a uniform volume change across the specimens, the maximum registration error due to

the change in volume was estimated for both cases. As shown in Table 4.7, the resulting RSS

values were 0.76 mm and 1.37 mm for Case 3 and Case 4, respectively. The mean and standard

52

deviation of the fiducial registration error are also shown in Table 4.7. Although a more reliable

evaluation metric for calculating the registration error would be TRE,67

we only reported FRE as

tongues do not possess any reliable anatomical landmarks within them. In addition, since the

landmarks selected to perform the registration were the 4 edges of the tongue that formed as a

result of the surgical cuts, their selection was subject to errors. Therefore, to approximate the

variations in calculating the FRE based on the edges, the registration was repeated 4 times. After

each time the FRE was calculated, and the final FRE was reported as the mean and standard

deviation of the 4 FREs. Selecting the fiducials in Case 4 resulted in higher variations than in

Case 3. This could be because of the larger slice thickness of Case 4 which consequently made

the FREs larger for some than the other. Also the mean FRE for Case 3 was lower than that for

Case 4. This could be an indication that the deformation of the outer boundary of the tongue was

reduced by using the tongue mold, and therefore the distance between the corresponding points

was smaller in Case 3. Since volume change also affects the one-to-one correspondences

between the two images,46

its influence on the FRE for each case was then compared. The results

show that the FRE of 3.17± 0.30 mm for Case 3 was contributed by the volume change of 0.79

mm, while the FRE of 4.12 ± 0.63mm for Case 4 was influenced by 1.37 mm of volume change.

Therefore the effect of volume change on the mean FRE was higher for Case 3, than Case 4.

This indicates that the influence of other factors such as tissue deformation resulted in a higher

registration error62

for Case 4. Assuming the 2% shrinkage rate as obtained in Chapter 2, instead

of the 10.02% expansion rate, to be true for Case 4, the RSS value will change to 0.28 mm,

which further confirms that the higher fiducial registration error in Case 4 is mainly due to the

tissue deformation rather than tissue shrinkage.

Registration quality was also visually confirmed for each case. Figure 4.19 shows the alignments

between the outer boundaries of pre-op and ex vivo images in Case 3 using the white and red

dotted lines, respectively. Figure 4.20 represents the pre-op and ex vivo registration of Case 4,

where the outer boundaries are shown by white and blue dotted lines, separately. The close

distance between the white and red dotted lines in Figure 4.19 indicates a much better conformity

of the ex vivo boundary with its pre-op image for Case 3. On the contrary, the large distance

between the white and the blue dotted lines in Figure 4.20 indicates that the outer boundary of

the two images wasn't well aligned. This can be explained by deformations or elongation

experienced by the specimen after the surgery. An artifact, visible in both Figures 4.17 and

53

Figure 4.19, was formed as a result of inserting pre-operative sutures that were soaked with an

MR contrast material inside the tongue. Since the focus of this chapter was to emphasize the use

of the fixative techniques to help with the registration, the impact of sutures will be discussed in

more details in the next chapter of this thesis. Although the results, following a simple rigid

registration technique, indicated a success in reducing deformation of the tongue, the registration

error was still higher than our objective which was 2 mm. This could be further improved by

adding landmarks that can help with performing the registration and validating the registration

accuracy. Moreover, the deformations that occur in the inner boundary of the tongue along the

cut lines can’t be controlled using the 3D printed tongue-mold technique. For that issue,

deformable registration methods that would allow local rigidity constraint to avoid unrealistic

distortion need to be considered.66, 71

4.4 Fixing the scan orientation of the successive ex vivo mandible specimens

4.4.1 Materials and Methods

4.4.1.1 ex Vivo Mandible Imaging

In this section, a method was developed and tested to keep track of the position of ex vivo

mandible CT scans to facilitate their co-registrations. For this purpose, the fast-setting alginate

(1) was prepared with the amounts shown in Table 4.1. The gel then was poured into a non-

sticky container (i.e. a 500 ml plastic beaker), that was slightly larger than the length of the

specimen. After that, a freshly resected mandible was gently pressed on the gel to make an

imprint. The gel was removed from the container after 1-2 minutes or once it solidified. In

addition, to better maintain the position of the specimen the crossed pattern of laser lights, which

was emitted from the CT scanner, was drawn on the mandible with a surgical skin marker. The

drawing was then made permanent to adhere on the specimen after suspension in formalin and

RDO solutions. This step was done by redrawing the pattern using a blue ink and fixing it by

spraying a 5% diluted acetic acid, which was supplied by MarginMarker’s ink and fixative

system (Vector Surgical LLC, Waukesha, WI). The drawn pattern then was aligned with the

emitted laser lights before each successive CT scan, as shown in Figure 4.21a After acquiring the

CT scan of the fresh mandible, denoted as CT-fresh in this section, the mandible was removed

from the gel and placed in a 10% formalin solution for fixation. The imprinted gel, labeled as the

54

Figure 4.21- Techniques for creating the same scanning location for each of the ex vivo

images to facilitate their co-registrations: a) Aligning the CT emitted lights drawn on

the specimen before each scan, and b) Using the imprinted reference plate during each

of the fresh, fixed and decalcified CT acquisitions

a) b)

Laser lights aligned with its

corresponding drawn pattern

reference plate, which is shown in Figure 4.21b, was kept in a plastic bag until the next scan, to

avoid evaporation of water content and shrinkage of the gel. The same scanning procedure was

followed for the fixed then the decalcified specimen, denoted as CT-fixed and CT-decal,

respectively. Immediately after each CT scan that we obtained using this method, a second CT

scan was obtained without the gel. For that process, the specimen was removed from the

reference plate and placed back on the CT bed, where the reference plate was initially positioned.

For simplicity, the CT scans without using the gel are referred to as mandible-alone-CTs in this

chapter. This method helped to locate the specimen in a known and fixed position for each of the

successive fresh, fixed and decalcified CT scans.

4.4.2 Results

The brightness of the mandibles and their attached reference plate was very close and the use of

a distinct threshold number to separate the two using semi-automatic segmentation technique

wasn’t possible. Sagittal images of the CT-Fresh, CT-Fixed, and CT-Decal images of the

mandible obtained with the underneath reference plate are shown in Figure 4.22a-c, respectively.

55

Therefore, the registration was only performed on the mandible-alone-CTs, where the reference

plate wasn’t used. Figure 4.23 and Figure 4.24 show the unregistered overlay of the decalcified

and fixed images on their corresponding fresh images both with and without the reference plate.

The purpose was to show that both plate and non-plate cases have reduced the initial error

between the image sets. Therefore, in terms of automating the registration, using the mandible-

alone-CTs was also possible.

The registration was performed using the rigid registration using mutual information in Elastix,65

an open-source command-line-driven platform for image registration. Also the registration

accuracy was quantified using on MI and TRE metrics.

Fresh Fixed Decalcified

Reference Plate Reference Plate Reference Plate

a) b) c)

Figure 4.22-Showing CT scans of the a) fresh, b) fixed and c) decalcified states of a

mandible, which were obtained while positioned on the reference plate (The contrast

adjustments for all three images were set at: Window: 5912 and Level: 2589)

Figure 4.23- Unregistered overlay of a) fixed to fresh and b) decalcified to fresh

mandible CT scans with reference plate. The gray area shows the fresh mandible in

both cases

a) b)

56

Rigid registration by maximizing the mutual information was then performed for mandible-

alone-CTs. In that process, each of the fixed and decalcified mandible images was registered

with the corresponding image of the fresh mandible, as shown in Figure 4.25a-b. Figure 4.26

also shows the landmarks selected for TRE calculations.

Figure 4.25- Illustrating the resulting mutual information based rigid registration

of a) the fixed on the fresh and b) the decalcified on the fresh mandible images. The

fixed image is shown as yellow in a) while the decalcified image is represented by

red in b). In both a) and b) the CTs of the fresh mandible are displayed as gray and

are pointed by the arrows to show the misalignments.

a) b)

Figure 4.24- Unregistered overlay of a) fixed to fresh and b) decalcified to fresh

mandible CT scans without the reference plate. The gray area shows the fresh

mandible in both cases

a) b)

57

Table 4.8 shows the quantification of the registration error based on TRE and mutual information

metrics between the image pairs

Table 4.8- measurements for quantifying registration accuracy

Similarity Measure Fresh on Fresh Fixed on Fresh Decal on Fresh

MI (Rigid) 0.326* 0.307 0.253

TRE - 0.743 mm 1.150 mm

*Represents best possible MI score

4.4.3 Discussion: Successive Mandible CT Scans

The CT scans of the mandible which were obtained by using the reference plate to maintain the

imaging orientation were shown in Figure 4.22. However, in order to co-register the mandibles,

the underlying gel reference plate must be ignored in the registration process. An attempt to

segment the mandible from the reference plate was made by using the semi-automatic technique

in ITK-SNAP. However, due to the similarity in brightness between the mandible and the

reference plate, as shown in Figure 4.22, a distinct threshold value for segmenting the mandible

wasn’t found. In addition, the time-consuming process of manual segmentation was found to be

impractical. Therefore, mandible-alone-CTs, which were almost in the same scanning window,

as shown in Figure 4.24, were used for performing the co-registrations. The approximate

scanning position of the mandibles allowed us to automate the registration using the intensity-

based technique without the need for performing fiducial registration for creating an initial

a) b) c)

Figure 4.26- TRE point selections on a) fresh, b) fixed and c) decalcified

mandible images

58

alignment. The well-registered images are displayed in Figure 4.25. The misaligned areas, which

are more visible in Figure 4.25b, are due to the shrinkage of the specimen as the result of

formalin fixation and RDO decalcification. The quality of the registration was then analyzed

using mutual information similarity metric as well as TRE. The points chosen for calculating

TRE were shown in Figure 4.26.

Table 4.8 shows the mutual information measure as well as TRE between the image pairs.

According to Thevenaz et al., if the images are perfectly aligned, the mutual information

criterion will be at its minimum.42

The MIs in Table 4.8 reported as positive numbers so that the

highest value indicates the best measure. Then, to find the value for the best alignment the image

discrepancy measure was first calculated between the CT images of the fresh mandible by itself.

Next, the transformed fixed and decalcified images were compared with the reference fresh CT,

separately. The MI value for the Fixed on Fresh was higher than the MI value for the Decal on

Fresh. This result was expected, because as illustrated in Figure 4.25b, the size of the decalcified

specimen, due to the loss of bony features, was smaller which consequently resulted in more

misalignment and a lower MI value than the fixed specimen. The TRE calculation was also

consistent, as the higher value obtained from decal to fresh indicates higher misalignments

between the two images, as the distance between the corresponding points are higher.

Therefore, we successfully performed direct intensity-based rigid registration, by reducing the

misalignment between the successive CT scans of the mandible. The technique allowed us to

save substantial time in performing the registration because the manual landmark alignment

process needed to bring the images in the same coordinate system wasn’t necessary anymore.

The use of the reference plate was also shown to be redundant. Keeping track of the CT lights

by marking them on the specimen was sufficient to provide a good initial alignment between the

images, therefore following that simple step is suggested for future studies to facilitate the

registration performance. The transformation matrices will then be used to complete the steps of

mapping from the histology images back to the pre-operative CT image of the pig.

59

Registering the CT scans of the mandible will mainly provide information about the tumours

invaded inside the specimen. In addition, to account for tumours that are located superficially on

the gingiva or inner part of the lip, we tested a method that can be used. For this, we separated

the bone from the soft tissue after formalin fixation and substituted it with gel material to

maintain the stability of the soft tissue during slicing as well as retaining the original shape of the

specimen for registration (Figure 4.27).

Removing the bone will eliminate the need for applying the decalcification on the whole

specimen, and that’s a procedure that is followed as a routine practice when RDO is used to

decalcify the bone. In that case, the mucous membrane lining the outside of the mandible, where

the tumour is presumably located, must also be removed. Before removing the mucosa, markings

using permanent markers (i.e. MarginMarker’s dye and fixation system) should be made on the

mucosa and its underlying bone such that the corresponding locations can be identified later.

Alternatively, if EDTA is used, however, the soft tissue as well may stay in the solution during

the decalcification process. It was also advised by Pathology Research Program to change EDTA

every day and to acquire an X-ray to ensure if the end point of decalcification has reached. Due

to the given time constraints we were not able to test the theories as mentioned above but we

were able to demonstrate the feasibility of removing the bone, and correlating the optical image

with its corresponding CT slice, as shown in Figure 4.28. In future a model similar to oral cavity

of human (i.e. monkey) is needed to be able to better assess and verify this method before using

for a clinical trial.

Figure 4.27- Bone removal process. a) gel is used to imprint the soft tissue + mandible.

b) mandible is removed and it got substituted using the purple gel. c) after a few minutes

the gel is set and the block is ready for cutting.

a) b) c)

60

To conclude, based on the results we obtained in Chapter 4, the following points are

recommended for the planned clinical trial:

1) The formalin-fixed specimen should be embedded in alginate inside our designed tissue box,

to perform ex vivo imaging followed by serial sectioning.

2) During the pre-operative and post-operative imaging of the patient the mold should be used to

imprint the tongue. It is recommended to perform the pre-operative imaging close to the date of

the surgery to ensure the size of a tumour (hence the tongue) hasn’t changed significantly. The

mold also has to be kept in a fully enclosed container until the date of surgery to avoid shrinkage.

3) Before proceeding with 3D fabrication of the tongue mold for the planned clinical trial, it is

suggested to perform a test where normal saline is not used. For that, acquiring a pre-operative

imaging of the tongue at least a day prior to the surgery is required. This enables us to

understand the true impact of the mold in reducing the outer deformation of the tongue, without

any influence from normal saline. Because normal saline may also help with reducing the

deformation since based on our observation on one sample the boundary deformation of the

specimen was already reduced after placed in normal saline. The test also allows us to recognize

possible improvements and modifications that may be needed on our design of the mold to

increase its efficacy in reducing the deformation.

4) The ex vivo imaging of the mandible specimens can be done by marking the CT emitted lights

on the specimens and aligning the markings before each acquisition. This will allow automated

co-registration of the ex vivo specimens and eliminates the need for performing rough alignment,

Figure 4.28- Matching CT scans of the original mandible before and after removing the

bone in a) and b). The corresponding optical image after removing the bone is also

shown in c).

a) b) c)

61

initially. It is also suggested to use EDTA instead of RDO, as a decalcifying agent. In cases

where RDO needs to be used, the bone and soft tissue must be separated, for which conducting

an additional test on a more similar anatomy to human’s mandible and gingiva is required.

62

Chapter 5 Developing a Registration Workflow and Verification Technique

In correlative pathology, accurate image registration is necessary to find correspondences

between the pre-operative volumetric imaging and the set of 2D histology slides.72

This chapter

presents preliminary results on performing all registration steps between the pathology sampling

and the original pre-operative radiological imaging. The method and results presented in this

chapter are exploratory, with preliminary results demonstrating the full registration process. The

process can be divided into 4 distinct steps by employing intermediate ex vivo and optical

imaging such that the deformations induced during histology processing can be separated from

those that occurred during surgery or tissue handling.72

Figure 5.1 shows a graphical

representation of the whole registration process, where the transformation matrices obtained after

each registration process are indicated by letter T. Following the registration steps, as indicated

in the image, allows the histology images to be registered back to the pre-operative volumetric

imaging.

Different registration techniques were employed for each step and the accuracy of the

registration was tested where possible. The feasibility of the complete registration path was

demonstrated in our work, while also identifying areas that require further improvements.

Pre-op

Imaging

Post-op

Imaging

Ex vivo

Image(s)

Optical

Imaging

Histology

Imaging

TE-P TO-E TH-O

Figure 5.1- Illustrating a pipeline for histology to pre-operative image registration

63

5.1 Materials and Methods

5.1.1 Post-op to Pre-op Registration

In order to register the histology with the pre-operative images,

knowledge of the resected volume is required. This can be

achieved by directly registering the ex vivo to the pre-op image

for rigid specimens that contain identifiable landmarks, such as the mandible with sharp teeth.

The tongue, however, lacks landmarks (except for the tip in our case) that can help orient the ex

vivo specimen such that it matches with the resected volume on the pre-op image. To achieve

proper alignment in the case of the tongue, the post-op was first registered on the pre-op image.

The two data sets were aligned using 4 landmark sutures visible in both images which were

implanted prior to the pre-op acquisition. An illustrative example for selecting one of the

landmarks is provided in Figure 5.2.

Figure 5.2- An illustrative example of selecting a suture point in 3D slicer. The point in

each of the corresponding axial, sagittal and coronal view is shown in both pre-op (top) and

post-op (bottom) images.

Pre-op

Imaging

Post-op

Imaging

64

5.1.2 Ex vivo to Pre-op Registration

For the mandible data, registration of

images of ex vivo samples to the pre-op

images was performed by selecting 4

corresponding points in each image set and

calculating the rigid body transformation

between these points. These steps were

performed using an in-house registration

system, GTx-Eyes (Figure 5.3).

For the soft, deformable tongue samples, knowledge of the resected volume as obtained from the

previous section was required as an aid in registering the ex vivo tongue specimen to the pre-op

images. The resultant image obtained from post-to-pre-op registration was imported into ITK-

SNAP where the resected volume was contoured. The largest extent of the contour was

compared with that of the ex vivo image. The comparison showed that the size of the resected

volume was shorter than that of the ex vivo image This could be due to susceptibility artifacts

that shaped as multiple cavities in the pre-op image that limited our ability to draw an accurate

mask from the resection area. Because of the difference in size, additional slices were added to

the contour of the resected volume until it matched the size of the resection with the ex vivo

Pre-op

Imaging

Post-op

Imaging

Ex vivo

Image(s)

TE-P

Figure 5.3- Selecting the point correspondences from the surface rendering between

fresh ex vivo (left) and pre-op image (right). The points for performing the registration

and for validating the registration accuracy are shown by green and red, respectively.

65

image. The contour was then converted into a surface mesh and saved as a stereolithography

(STL) file. In the next step, surface registration was performed between the resected and the ex

vivo image surface mesh contours using the 4-points congruent sets (4PCs) algorithm73

. This

allowed us to see the matching points on the surface of the two images after registration. The

resultant surface registration is shown in Figure 5.4.

Figure 5.4- Surface registration performed using 4PCs algorithm. The resultant image is

shown from different angles, where the gray areas represent the area of resection as

obtained from the post-op to pre-op registration and the yellow regions show the ex-vivo

image.

The matching regions in Figure 5.4 guided the selection of the appropriate points when

performing the point-based registration between ex vivo and pre-op image. Three surface-point

pairs were selected on the surface meshes and the same points were chosen in the image sets

(within 3D Slicer) to superimpose ex vivo images on the pre-op image set.

5.1.3 Optical to ex vivo Registration

In the next registration step, optical images of the tissue

sections (as shown in Chapter 3) were registered to the ex

vivo images. As an aid in this registration, cylindrical

cavities were created in the gel surrounding the tissue

which were visible in both the CT/MR images of the tissue

samples and the optical images of the tissue sections.

In the first step in this registration process, the digital

optical images first were stacked on each other to form a 3D volume. The stacking was

Ex vivo

Image(s)

Optical

Imaging

TO-E

66

performed using the image resolution information calculated from images of the checkerboard

obtained during photographing the tissue slices. This image stacking was performed using 3D

Stacker, saving the image resolution for each slice (mm/pixel) and average slice thickness with

the stacked volumetric image set. The optical data axes were oriented such that they aligned with

their corresponding ex vivo data sets. The optical image stacks were then viewed in 3D Slicer

(Figure 5.5) to verify the quality of the stacking by positioning the cursor on each of the cavity

fiducials in the axial direction such that the straight length of the cavity was seen in sagittal and

coronal orientations.

The stacked optical images of the tongue were then registered with the ex vivo datasets using 4

tissue landmarks along with two cavity fiducials visible in both the optical and CT/MR images.

The locations of the landmarks were confirmed by visual inspection of the correspondence

between the content of both data sets on each slice. An illustrative example of picking two of the

corresponding landmarks is shown in Figure 5.6. Mandible specimen, however, lacked the

fiducials that were visible in both imaging modalities (i.e. optical and microCT). Therefore a

total of 24 points were used across all the slices to perform a more accurate alignment.

67

Fiducial 1

Fiducial 2

Axial Sagittal Coronal

a)

b)

c)

Fiducial

Figure 5.5-The quality of the stacked optical images is shown by verifying the straightness

of the cavity fiducials in sagittal and coronal views. Both a) and b) show the optical stacking

for tongue samples while c) shows the stacking for a mandible specimen. Axial views

display the location of each of the corresponding fiducials as seen from the camera’s view

point, by red arrows.

68

Figure 5.6- Aligning the optical and ex vivo tongue images using the cavity fiducials that are

filled with MR contrast agents and ultrasound gel to be visible in both modalities (shown

by red lines). The blue lines show the corresponding suture points used to calculate the

TRE after performing the registration.

5.1.4 Histology to optical registration:

One histology slice with the thickness of 4 microns was

generated from the surface of each tissue slab using a

Shandon Finesse ME+ microtome (Thermo Scientific™)

in the STTARR pathology lab. The histology slices were

then mounted on glass microscopic slides, H&E stained

and imaged at 20× magnification using an Aperio

Scanscope brightfield scanner (Leica Biosystems Inc.,

Ontario, Canada), located on the 15th

floor of the Toronto Medical Discovery Tower. The

resolution of the histology images were 0.504 μm, which were 29.55 and 37 times larger than the

resolutions of the optical tongue and mandible images, respectively. Therefore the histology

images were scaled down using a program called Sedeen Viewer (Pathcore Inc.) to the

appropriate resolution of their corresponding optical image prior to performing 2D to 2D

registrations. Next, MATLAB was used to perform point-based registration by selecting 3-4

landmarks from each of the corresponding histology and optical images. Two examples are

shown in Figure 5.7 below. After each histology image was registered to its corresponding tissue

Histology

Imaging

Optical

Imaging

TH-O

69

section optical image, the histology images were then stacked together to form a 3D volume

using similar methods used to stack the optical images of the tissue sections.

Figure 5.7- Illustrative examples showing point selections on unregistered histology and

optical for tongue (top) and mandible (bottom) images.

5.1.5 Histology to Pre-op Registration:

With all intermediate registration steps completed, registration of the histology images to the pre-

operative image could be completed. The transformation matrices that were obtained from the

intermediate steps were composed in MATLAB and then applied to the stack of the histology

images, hence registering each histology slice back to the pre-operative imaging. The overall

registration error then was calculated using the root of the sum of square errors (RSS).

The summary of the registration workflow for tongue and mandible along with the metrics used

to evaluate the registration at each step is provided in Table 5.1 and 5.2, respectively.

70

Table 5.1- Summary of the registration steps for the tongue

Moving/

Fixed

Image

Registration

Parameter

Number of

Points Selected

for

Initialization

Software used Measurements

Post-op to

pre-op

- Manual

- Point-based

registration

4 - 3D slicer - Qualitative

Ex vivo to

difference

pre-op

- Automatic

surface

registration

None - 4 PCs

- Qualitative

Ex vivo to

pre-op

- Manual

- Point-based

registration

(using the points

identified from

the surface

registration)

3 - 3D Slicer - FRE

Optical

(3D) to ex

vivo

- Manual

- Point-based

registration

4 - 3D slicer - FRE

- TRE from 5

suture points

Histology

(2D) to

optical

(2D)

- Manual

- Scaling prior to

registration

- Point-based

registration

3-4 points per

slice to slice

pairing

- MATLAB - FRE

- TRE from 5

suture points

Histology

to pre-op

- None None - MATLAB for

composing the

transformations

obtained from

previous steps

- ITK-SNAP for

applying the

composed

transform

- Qualitative

71

Table 5.2-The summary of the registration steps for the mandible

Moving/

Fixed

Image

Registration

Parameter

Number of

Points Selected

for

Initialization

Software used Measurements

Ex vivo-

Fresh to

Pre-op

- Manual

- Point-based

registration

- Automatic

- Intensity-based

rigid registration

- Mutual

information

4 - GTxEyes for

initialization

- ITK-SNAP for

automatic

intensity-based

rigid registration

- FRE

- TRE from 4

front teeth

(Fig.5.3)

Ex vivo-

Decal to

Ex-vivo-

Fresh

- Automatic

- Intensity-based

rigid registration

- Mutual

Information

None - Elastix or ITK-

SNAP

- Mutual

information

(Section 4.4)

- TRE (3 points)

Optical

(3D) to ex

vivo Decal

- Manual

- Point-based

registration

24 - 3D slicer - FRE

Histology

(2D) to

optical

(2D)

- Manual

- Scaling prior to

registration

- Point-base

registration

3-4 - MATLAB - FRE

72

5.1.6 Role of Implanted Suture Fiducials

Suture fiducials inserted inside the tongue were used to provide reliable landmarks that can be

tracked in all the imaging modalities and used for performing and validating the registrations.

The fiducial sutures consisted of three strands of GS832 SOFSILK™ Size 3-0 USP (2 Metric),

30 inches (75 cm) BLACK on V-20 Needle (Medtronic, MN, USA) infused with a ratio of 1:80

Gadovist (Bayer Inc., Toronto, Ontario), and 2 drops of green tissue marking dye (Bradley

Products, Inc.). A ratio of 1:40 Magnevist was successfully used in a study for registering ex vivo

prostate specimen to histopathology images.28

Since the concentration of Gadovist is twice that

of Magnevist, the proportion of Gadovist used in these studies reduced by a factor of 2, to 1:80.

After deciding on the area of resection, 3 strands of sutures were placed perpendicular to the

tongue surface. An additional 3 strand sutures were infused with 1:80 ratio of Gadovist and

inserted laterally such that they would intersect with the cut lines. It was expected that this

alignment would result in more points available to aid in performing the registration. Both

suture configurations are shown in Figure 5.8. In addition, two different approaches for suture

representation were examined under histology images. For this, one suture was kept inside the

tongue while the rest were removed prior to paraffin embedment and microtome cutting.

Figure 5.8- Configurations used for inserting the two types of suture fiducials inside the

tongue

73

5.2 Results

5.2.1 ex vivo to Pre-op Registrations

The results of the ex vivo to pre-op registration for both mandible and tongue are provided in

Figure 5.9, where a) and b) correspond to the pre and post optimization results for the mandible

and c) shows the point-based registration result of the tongue.

Figure 5.9- ex vivo to pre-op registration results from axial, sagittal and coronal viewpoints,

where a) and b) correspond to the point-based and the mutual information based rigid

registrations of the mandible and c) shows the point-based registration result of the tongue

Axial Sagittal Coronal

a)

b)

c)

74

5.2.2. Optical to ex vivo Registration

Two illustrative examples from different viewpoints in 3D Slicer for tongue and mandible are provided in

Figure 5.10 and 5.11, respectively.

Figure 5.10- Optical to ex vivo registration of tongue specimen using the fiducial landmarks

placed in the gel (the cavity fiducials are not shown in this picture).

Figure 5.11- Registered optical to ex vivo image of the mandible specimen using landmarks

identified within each corresponding slice

a) Ex vivo

b) Optical

c) Registered

Axial Sagittal Coronal

75

5.2.3. Histology to Optical Registration

Two example overlays of the histology to optical registration for tongue and mandible are

provided in Figure 5.12 and Figure 5.13, separately.

Figure 5.13- Histology to optical registration of the mandible specimen. The overlap in a)

shows two missing pieces that are marked by dashed circles, while b) shows some degree of

shrinkage shown by a dashed oval and a fold which is pointed by an arrow.

Figure 5.12- Histology to optical registration of the tongue specimen. Overlay in a) shows a

larger area of histology than the underlying optical due to not cutting along the exact cross

section as the optical image, while b) shows minor missing pieces from the histology slides

that are identified by dashed ovals.

a) b)

76

An illustrative example of the suture fiducials on a histology image is provided in Figure 5.14 b)

and c). These sutures were used to calculate the TREs.

Figure 5.14- Suture fiducial representations on a histology image in a), where b) and c)

show the magnified (×5.1) non-removed and removed suture landmarks from the specimen,

respectively. The green dye is also visible around both markings in b) and c).

77

The transformations obtained from ex vivo to pre-op and optical to ex vivo were composed and

applied to the optical stack to map them back to the pre-operative image, as shown in Figure

5.15. In addition, Figure 5.16 shows the registered pathology on pre-operative image.

Figure 5.15- Final optical to pre-op registration.

Figure 5.16- Final histology to pre-op registration.

78

5.2.4 Registration Evaluation

Table 5.3 below shows the results of the registrations for each step.

Table 5.3- Registration Evaluations

Tongue Mandible

Registrations FRE (mm) TRE (mm) FRE (mm) TRE (mm)

Ex vivo to Pre-op 1.72 (3 points) Unknown-

localizing the

sutures inside the

pre-op image was

difficult

0.29 (4

landmarks)

Pre-

optimization=

0.68

Post-optimization

= 0.90*

Ex vivo decal to

Ex vivo fresh

N/A N/A The registration

was performed

using automatic

intensity based

mutual

information

1.15

Optical to Ex vivo 0.85 (4

landmarks from

cavity fiducials)

0.59 (5 sutures) 0.88 (24

landmarks)

Unknown-there

were no truthful

landmark to pick

Histology to

Optical

0.30 (average

from all the

corresponding 4

slices)

0.72 (5 sutures) 0.55 (average

from all the

corresponding 10

slices)

Unknown- there

were no truthful

landmarks to pick

Overall

Registration

accuracy (RSS)

1.94 Unknown 1.07 Unknown

79

*This value is higher due to inaccuracies in picking the same points. The large voxel size (low

spatial resolution) of the pre-op image produced fuzzy boundaries which made the bone appear

larger than in the ex vivo image (Figure 5.3).

5.3 Discussion

Since there were no landmarks on the tongue the ex vivo to pre-op registration wasn’t performed

directly. Even though suture fiducials were added pre-operatively, they were not sufficiently

visible to match the two data sets. Identifying the resection area on the deformed tongue would

not be easy, but previously we were able to reduce the deformation as explained in section 4.2.

Therefore registration of the post-op to the pre-op image using the lateral suture fiducials was

achieved to provide information about the area of resection. The result from this step was then

used to register the ex vivo to the pre-op image. This was done using 4PCs algorithm which is a

surface registration technique to find the matching points between the ex vivo and the resected

region (Figure 5.4). After the matching points were identified, the ex vivo image was directly

registered to the pre-op by manual point-based rigid registration. The FRE was then calculated,

while the calculation of the TRE wasn’t possible since the inserted sutures weren’t visible as

they were much smaller (=0.2 mm) than the voxel sizes of the two datasets. Therefore, in order

to be less prone to the resolution, it is suggested to use a larger diameter suture type that

preferably has the same thickness as the voxel size of the pre-op image. Additionally, measuring

the length of the sutures before insertion and making some equally spaced knots on each suture

will be necessary for a more accurate localization of each point along the suture lines.

The ex vivo mandible specimen was registered on the pre-op image using the 4 teeth fiducials as

shown in Figure 5.3. Then the TRE was calculated pre and post-optimization as described in

section 4.4. The results in Table 5.3 show a larger TRE for post optimization than the pre-

optimized version. This, however, contradicts the visual verification after the registrations in

Figure 5.9 a) and b). This discrepancy can be explained due to the indistinct boundaries that

existed as a result of the lower spatial resolution of the pre-op image. Figure 5.3 illustrates the

surface rendering of the pre-op and ex vivo fresh mandible. It is evident that although the

threshold of the pre-op image was changed so that the thicknesses of the teeth would match those

of the ex vivo image, selection of the points were still not accurate as the teeth in the pre-op

image appeared larger and interconnected. We can obtain a more accurate TRE calculation by

80

attaching a few pointy surface fiducials on the area of resection pre-operatively. According to

West et al. the best location for these points would be at the centroid of the landmarks that have

already been selected to perform the registration.69

The added surface fiducials could be in the

form of suture knots infused with CT contrast agents (i.e. barium sulfate, iodine, etc.) that could

be placed prior to acquiring the pre-operative image of the specimen. An initial test needs to be

done to see how long the contrast would stay visible on the suture. There might be a need for

reapplying a small amount of the contrast on the suture after fixation and decalcification of the

mandible right before each of the microCT imaging.

To maintain consistency in the imaging orientation and to make sure that images are scanned

along the same data axis, the ex vivo specimens must be oriented such that they are close to the

alignment of the pre-op imaging. This can be achieved by marking the orientation of each

specimen with respect to the pre-op positioning using tissue dyes after the resection; these

markings can be followed for later scan(s). Similarly, the slicing orientations on the gel/tissue

block must be aligned with the axial planes of the ex vivo imaging, with cuts must made

perpendicular through the cavity fiducials in the gel.

The quality of optical stacking in Figure 5.5 a) and b) indicates that there might be slight

movements within the soft gel due to the cutting action while c) shows a higher angulation of the

cavity rod. That was a special case where the user manually restacked the gel/tissue slices and

imaged them again to correct some imaging issues that occurred during the first round of

imaging. Due to this manual interaction the slices weren’t stacked perfectly straight towards the

two ends of the cavity rod.

Several issues were noted in the optical to ex vivo registration of the mandible. For example,

after the registration, the width of the mandible in the optical stack was shorter than that in the

decalcified image by about 8 mm. Besides the previously mentioned manual interaction during

the restacking of the slice images, this could also be due to the influence of two other factors: 1)

the average slice thicknesses of the slabs were assumed to be the same as the average slice

thickness for the tongue (=2.84 mm); it wasn’t separately calculated for the mandible, and 2)

mandible possibly experienced some rotation inside the gel during the tissue embedment process.

These factors can be improved by adding a digital readout to the tissue slicer to measure the slice

thickness of the cuts before sectioning every tissue block and by measuring the thickness for

81

every generated slice to ensure the average thickness is recorded. In addition, keeping the

reference plate, as described in section 4.4, during the slicing and photographing action is

required to prevent rotation of the specimen during the gel embedment process so that the optical

imaging planes would match with the ex vivo imaging planes more closely. For this, the

reference plate is only needed during the decalcified microCT imaging so that it could be

registered to the fresh microCT image without the need for segmenting out the gel. An initial

rough alignment may be needed followed by optimizing the registration using intensity based

techniques. To facilitate this, however, both specimens should be placed within the same

coordinate system as described previously. After performing optical to ex vivo registration, the

FRE results for both tongue and mandible were 0.85 and 0.88, respectively. The TRE for the

tongue was also calculated using 5 of the suture fiducials at the center (Figure 5.6). The TRE for

the mandible imaging wasn’t calculated due to the lack of good corresponding landmarks

between the two data sets. Twenty-four points had already been selected as valid landmark

points for performing the registration and calculating the FRE. This may not be an issue if the

optical image is scaled properly such that the registration can be confidently performed with

fewer points. Also having an actual visible disease within the specimen may help to find the

target points for calculating the registration error.

Histology images tend to shrink, fold, tear or expand during processing which makes them

difficult to correlate with other imaging modalities.74

Figure 5.12 and 5.13 show 2D to 2D

histology to optical registrations of tongue and mandible using point-based rigid registration

technique. Direct co-registrations of the histology and optical images of the tongue (Figure 5.12a

and b) didn’t show significant shrinkage, which was also consistent with our findings in Chapter

2. Therefore, the reason for the insignificant shrinkage rate comparing to the human tongue

samples can be explained by the difference in sample type and lack of tumour in our samples.

Figure 5.12a presents some misalignment due to not cutting along the exact cross section as the

optical image. Minor disintegrations in histology images of the tongue (Figure 5.12b) and

mandible (Figure 5.13a) were also detected. One way to prevent specimens from getting brittle

during microtome sectioning is to place the specimens back in 10% NBF and not in alcohol

fixatives after serial sectioning. The specimens also need to stay moist (i.e. in formalin) to avoid

formation of drying artifacts. Other histology artifacts observed were fold and shrinkage in

Figure 5.13b. The shrinkage rate for the histology sections of the mandible was about 10-15 %

82

across all the slides. As shown in Figure 5.13b, mandible’s structure is not as dense as the

tongue’s structure after being decalcified. Therefore the mandible had more spaces to shrink as a

result of losing water content during dehydration phase in the tissue processor. Other factors

such as stretching the thin microtome cut sections on a water bath, followed by spreading them

on glass slides and staining72

contribute to further distortions of the histology slides, which

require the need for a reliable technique for validation of the registration accuracy.75

Although

some specimens have anatomical structures that can be used as landmarks, still no reliable

landmark can be identified in some of those specimens as they may not be easily detected

through the whole volume.74

Shojaii et al. developed and tested multi-modality fiducial markers

that can be detected in volumetric imaging as well as in histology images.75

Those fiducials,

however, were not sterile and not capable of being inserted pre-operatively in the operating

room. In this thesis we developed a new multi-modality fiducial marker with the capability of

being inserted preoperatively. Figure 5.14 b) and c) demonstrates the appearances of these

markers under magnified histology images. Although both configurations represented good

visual landmark-points, we will remove the sutures from the specimen for future studies as the

presence of sutures during microtome cutting may disrupt tissue cutting or cause mechanical

damage to the tissue during sectioning.25

In addition, if the green dye needs to be omitted from

the protocol due to not being sterile to be placed pre-operatively, the sutures soaked with contrast

still would be detected as their marks on histology results can be differentiated from the

surrounding cellular structures. This, however, requires providing the pathologists with the

optical photographs from the insertion of the sutures to avoid any misinterpretations. The TRE

result for the 2D to 2D registration of the histology to optical tongue specimen was then

calculated, although that for the mandible wasn’t computed because reliable anatomical

landmarks for the mandible were not easy to find. To solve this, implanting some fiducial

landmarks post-decalcification needs to be tested. The fiducials can be 3 strands of sutures

soaked with 25% of barium sulfate and green tissue dye. A preliminary result showing the

appearance of sutures soaked with 25% of barium sulfate is shown in Figure. 5.17.

The calculated registration error available in each step was provided in Table 5.3. Results show

that ex vivo to pre-op for the tongue sample and optical to ex vivo for the mandible specimen

provided the highest FRE errors. The overall FRE calculation for both mandible and tongue

showed to be less than 2 mm, which seems to satisfy our thesis objective. This, however, is not a

83

good indication alone because the FREs represent the goodness of fit between the fiducials but

they are not reliable indicator of registration accuracies. Therefore calculations of TREs are

required. 67

The TRE calculated for ex vivo decal to fresh was quite large. One way to reduce

these errors is to utilize deformable registration methods to correct for the misalignments due to

shrinkage or deformation. Utilizing a proper deformation technique can then reduce the TRE in

each step.

Finally we were able to use the transformations obtained from the previous steps to register each

of the optical and histology images on the pre-operative volumetric imaging, respectively. The

illustrations are shown in Figure 5.15 and 5.16 and indicate the feasibility of performing this

registration pipeline. There are still areas for improvements such as correction for the

deformations and/or shrinkage in the steps needed. Moreover more points need to be added to

calculate a more accurate registration error.

In conclusion, we demonstrated the feasibility of the full registration path and provide several

recommendations for any clinical trials as listed below:

1) The suture fiducials in tongue need to be as thick as the voxel size so they can be detectable

under the imaging. Adjusting the contrast is needed so that these markers are visible without

producing image artifacts.

Figure 5.17- Testing the appearance of suture fiducials soaked in 25% diluted barium

sulfate under microCT imaging

84

2) The ex vivo imaging orientation of the specimen needs to be close to the in vivo imaging

orientation. Also since the optical images are stacked along the z-direction, to facilitate the

optical to ex vivo registration, the slicing direction of the specimen should be along the axial axis

of the ex vivo imaging while perpendicular to the cavity fiducials in the gel.

3) Adding a digital readout to the tissue slicer for a more accurate reading of the slice thickness

and measuring the generated tissue slabs for every block is necessary to obtain an accurate slice

thickness that can be used for optical stacking.

4) In order to prevent the rotation of the mandible such that the generated optical slices are in-

plane with the ex vivo microCT slices, a reference plate should be kept under the specimen

during the slicing and photographing action.

5) To avoid formation of drying artifacts in the histology samples, specimens should be placed in

formalin fixation and stay moist at all the time.

6) The sutures that were placed for fiducial landmarks must be removed prior to paraffin

embedment and microtome cutting to avoid tissue damage during slicing and damaging the

microtome.

7) For more accurate calculations of ex vivo to pre-op target registration error, placement of

surface fiducials soaked with CT contrast pre-operatively is suggested on mucosa covering the

mandible specimens. In addition the TRE for ex vivo to optical and optical to histology image

pairs can be calculated by implanting suture fiducials soaked with barium sulfate and green

tissue dyes post decalcification. This way the sutures would be detected in microCT, optical and

histology images.

8) Photographs must be taken and given to pathologist from the positioning of the sutures inside

the tongue, to avoid misinterpretation of the pathology slides.

85

Chapter 6 Conclusions

The principle goal of this work was to develop methods for performing correlative pathology

from histology to preoperative imaging such that the methods can be utilized during a planned

clinical trial with the focus of validating a new imaging platform to improve tumour contouring

in HNCs. To achieve this, we tested on specimens from pig’s oral cavity: tongue and mandible.

We then planned our experiments based on four aims, for each a chapter of this thesis was

assigned to.

In Chapter 2, we studied shrinkage rates of the specimens after fixation and decalcification and

assessed their influence on the registration error. The results didn’t show significant shrinkage in

tongue samples, while it showed that mandible specimens shrank significantly after 3 days of

fixation and 3 days of decalcification. In addition histology results after 5 days of decalcification

had poor quality images mainly due to the reduced stainability of the nuclei in mucosa. Therefore

the use of RDO for the purpose of clinical research is not suitable. EDTA on the other hand, is

known for being safe on nuclear staining and therefore is recommended.

In Chapter 3, we designed a tissue slicer that can be used as a substitute for conventional meat

slicer to generate consistent whole-mount tissue blocks for large specimens. These blocks act as

an intermediate step between histological and radiological imaging and enable performing step-

wise registration such that the deformation and changes from histology to optical and from

optical to ex vivo medical imaging can be identified and corrected against.72

In Chapter 4, methods were proposed to reduce the deformation of the specimen. Use of the

supporting gel materials for embedding the tissue specimens during slicing the tissue sections

with our designed apparatus was successfully achieved. In addition, methods to reduce the

deformation of the tongue as a result of mechanical forces during the surgery or deformations

applied to the resected tongue during formalin fixation were proposed. Finally a method was

tested to maintain the orientation of a resected mandible specimen such that their CT scans after

resection, fixation and decalcification can be automatically co-registered using mutual

information intensity-based rigid registration.

86

In Chapter 5, the registration workflow with preliminary results was shown. The process of

registering from histology to pre-operative imaging through a 4 series of registration step was

explored. We also tested the use of fiducials for the tongue to help with performing and

validating the registration. In future, the fiducials need to be modified for better visibility in the

medical imaging. In addition, inserting fiducial markers in mandible specimens is necessary for a

more accurate validation of registration performance.

In summary, we demonstrated the feasibility of performing the registration from histology back

to the pre-operative MRI/CT volumetric imaging of tongue and mandible specimens. In doing

so, we were able to identify some of the challenges and limitations such as shrinkage,

deformation, lack of landmarks, and the need for maintaining close to pre-operative orientation

to perform the registration steps. We were also able to reduce tongue deformation during and

after the surgery by utilizing certain tissue handling techniques. Moreover, correlating the

resected specimen with the pre-operative and histology imaging was achieved by our tissue slicer

design. Additionally using the animal model that we had we were able to make recommendations

to reduce the shrinkage of mandible due to formalin fixation. Although ex vivo to pre-operative

fiducials required additional modification and improvement, we successfully demonstrated their

role in calculating registration error between histology to optical and optical to ex vivo image

registrations. In addition, the need for having additional landmarks in mandible was recognized.

To further reduce the registration error due to deformation, exploring registration methods that

would allow local rigidity constraint to avoid unrealistic distortion need to be considered.

To conclude, by utilizing the tissue handling and registration techniques mentioned in this thesis

document we were able to correlate pathology images of surgical samples to 1) the resected

sample and 2) the pre-operative images before surgery. We also realize that there might be

limitations in using some of these techniques during surgical operations, but they could still be

utilized on animal studies, followed by obtaining Ethic’s approval, for validation of the proposed

imaging platform using endoscopic contouring registered with CT imaging.

87

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