Imaging in Radio-Oncology - SASRO · Windowing 2 Exemple de la prostate à insérer HN-1000 0 1000 2000 3000 L/W : -600, 1600 Pulmonary window L/W : 50, 400 Mediastinal window L/W

•1

FMH resident physics training course in RO, PSI, 3/09/2007

La Chaux-de-Fonds

PD Dr Jean-François Germond

SSRMP Medical Physicist

Service de radiothérapie du DPO

Imaging in Radio-Oncology :

FMH resident physics training in RO, PSI, 3/09/2007 : J.-F. Germond

Sometimes imaging = miraging

Can you find the position of the camels?


1. Historical introduction

2. Anatomical imaging in RO localization

3. Functional imaging in RO localization

4. Immersion into 3D

5. 4D imaging in RO localization

6. Virtual simulation imaging

7. 3D guidance imaging

Objectives


Medical imaging

Electromagnetic WavesEM Potentials

MechanicalWaves

g Rays

Scinti-graphy

Radio-graphy

Endo-scopy

Thermo-graphy

Magnet. Reson.

E-M-graphy

Echo-graphy

Stetho-scopy

LightInfra-red

Radio-Waves

Biological Signals

Ultra-sound

Sound

Lowenergies

High energies

X Rays

Usage of imaging in medicine 1/2

All types of waves


Usage of imaging in medicine 2/2

Well established in diagnostic

Extensively used for tumor detection and staging

Used throughout radio-oncology:

– for planning

– for irradiation

– for verification


Reference imaging

Guidance imaging

2006

1960

1970

1980

1990

2000CT

Simulator

Portal imaging

PET-CT

4D CT

MRI

Cone beam

Historical evolution of imaging in RO

•2


Imaging in conventional simulation 1/4

X-Ray tube

Collimator

Digital camera

Therapy

table

Simulated beam

Conventional simulator 1960


Simulator radiographs

are used for drawing

beams aperture

Only based on

– Bony structures

– Air cavities

– Contrast agent in

specific organs

Only 2D


Widthjaw

Heig

ht

jaw

Blo

ck B

lock

D

D



Simulation film Verification film

Verification by portal film


Still in use for palliative treatments => 30% of patients

Still in use for pre-treatment verification of ports

Reference image = Simulator image

Portal film or electronic image used for verification



The 4 cornerstones of modern radio-oncology

Years

2000

Mu

ltim

od

al i

ma

gin

g

Years

2000

Ima

ge

gu

ida

nce

Years

90

Inte

nsity m

od

ula

tio

n

Vir

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l sim

ula

tio

n

Years

80

Workflow

3/4 of workflow

is imaging


Features of imaging in RO

1. RO is image guided (IGRT) in three aspects:

a. For the definition of volumes during planning (localization).

b. For the setup of fields in simulation (virtual simulation).

c. For the verification of the ballistic during treatment (guidance).

2. Imaging for RO is multimodal (CT,MRI, PET, …)

3. Images RO must be stored, transferred and linked

(DICOM)

•3


GTV : Gross Tumor Volume

CTV: + subclinical envolvement

ITV: + Internal margin

PTV: + Setup margin

Paradigm of target volumes definition

ICRU 50 & 62

GTV and CTV are

oncological concepts

based on a frozen

anatomy


Main issues of imaging in RO

1. Does the imaging modality allow to distinguish the target

volume from its environment?

• Adjacent tissues with similar electronic densities in CT exams

(atelectasy)

2. Does the imaging modality reflect the true anatomy?

• Artefacts

3. Does the image display allows the observer to perceive

the target volume?

• JND index


Visual perception of imagesDefinition:

The Just Noticeable Difference (JND) is the luminance difference that the average human observer can just perceive at a specified luminance level and viewing conditions

• Human eye is more

sensitive in the low

luminance range

(Fechner law)

• Delineate in rooms

with reduced ambient

light (15- 60 lux)

• DICOM GSDF

conforming displays

can compensate for

this effect


1 time

Several times

Major steps in the RO workflow

Localization

Virtual

simulation

Dose

planification

Guidance

Irradiation



Localization

Virtual

simulation

Dose

planification

Guidance

Irradiation


Localization in RO

Goal:

Precisely define the position, shape and volume of organs

– Target (tumor, lymph nodes, tumor bed, …)

– At risk (spinal cord, lungs, bladder, rectum, …)

Material:

All 3D imaging modalities

– CT, MRI, PET, SPECT, MRS, …

– Multimodalities registration and fusion

Method:

Organs delineation

– Manual contouring

– Automatic (thresholding, deformation, interpolation, atlas, …)

•4


Information characteristics of imaging in RO

Anatomical imaging => Structures and morphology

Functional imaging => Biological and molecular

abnormalities in tumors

From Smith A. and K.S. Clifford Chao, Radiation Research, 2005






PTV: + Setup margin


ICRU 50 & 62

Anatomical imaging in

RO is extensively used

for delineating the GTV

An

ato

mic

al im

ag

ing


Reference imaging

Guidance imaging

2006

1960

1970

1980

1990

2000CT

Simulator

Portal imaging

PET-CT

4D CT

MRI

Cone beam

Historical evolution of imaging in RT


CT equipment for RO

Large gantry

aperture

Movable

lasers

Flat table

top

Software +

protocols

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CT

Artist view, courtesy of Philips Medical Systems


Acquisition in helical (spiral) mode

Mode of acquisition

(L) length nCollimatio

(d) rotation 360 over shift Table Pitch

Full sampling for

360° recontruction

Full sampling for

180° recontruction

More complex for

multislices CT

Pitch = 1

d = 1 x L

Pitch = 1.5

d = 1.5 x L

Pitch = 2

d = 2 x L

Axial

scan

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CT

•5


CT data acquisition

Transmission profile

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CT


Sinogram

Ga

ntry

an

gle

CT data acquisition

Transmission profile

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CT


Reconstruction by backprojection

0

180° 24°

15°

Filtered Sinogram

24°

15°

Transverse image

Example of a point object

D pretense of reality only!

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CT


The usefulness of images is affected by several of their characteristics:

– Artefacts

– Contrast

– Resolution

– Noise

The image characteristics depend strongly on modalities.

Image qualityL

oc

aliza

tio

nw

ith

CT


Different

structures

seen

Different resolution

Different noise

CT PET

Lo

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CT

Image charateristics

Different

structures

seen

From F. Schoenahl , Cours CFPFTRM, 2005


Definition:

An artefact is any visible structure which does not reflect the

reality of the patient anatomy (wrong CT numbers)

Artefacts

Artefacts may be patient related:

a. Metallic objects inside the body (prothesis, clip, dental filling,…)

b. Patient voluntary or involuntary motions

c. Field of view smaller than patient size (obese patients)

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CT

•6


Artefacts

Double hip prothesisdental filling

Example of streaks due to metal inside the patient:

Workaround: Reduce pitch or use special protocols

Lo

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CT

HNEHNE


Artefacts

Skin markers used for breast tangential fields virtual simulation

Reconstructed below the skinD

Example of shifts due to metal taped to the skin:

Workaround:

Use special non metallic skin markers

Lo

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CT

HNEHNE


Hounsfield numbers (HN) = Tissue absorption coefficients

compared to water

=> Normalized scale

Hounsfield scale

Water

WaterTissueHN

*1000

-1000

-800

-600

-400

-200

0

200

400

600

800

1000

Eau-4

+4

Air-1000-990

Poumons

Os

spongieux

50

200

-950

-550

-100

-80

Os

compact

Graisse

250

0

10

20

30

40

50

60

70

80

Reins

Pancréas

Sang

Foie

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CT


Windowing

2 Exemple de la prostate à insérer

HN

-1000

0

1000

2000

3000

L/W : -600, 1600Pulmonary window

L/W : 50, 400

Mediastinal window

L/W : 1000, 2500Bone window

Increase contrast by mapping to 256 greyscale (8 bits)

Choice of the level (L) and the window (W) from definite protocols

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CT


Contrast adaptationHN profile

L/W: 1000, 2000 (full range)

1. Dispay a full profile

2. Zoom in on VOI

3. Set L/W to average,

range of VOI HN’s

L/W: 0, 200 (range in ROI)

%13 10

))90(40(

10

)HGTV

(HN

%Contrast :Calcul

gSurroundin

N

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CT

HNE


1000

100

10

1105310.5

0.7

57

Object size in mm

Contrast

Limited resolution at high constrast

Resolution at low constrast

Resolution and contrast

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CT

•7


Multiplanar views

Transverse slice

coronal slice

sag

gital slic

eI worst resolution in

cranio-caudal

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CT


Partial volume effect

Definition:

The partial volume effect is the part of an organ which has a reduced constrast to finite extension in the cranio-caudal direction

Correct HN

Reduced contrast

Slice thickness

Org

an

1

Org

an

2

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CT


Partial volume effect

Consequences:

Small objects like lymph nodes have too low contrast

Organ borders can be blurred

Example of fuzzy

separation between

right kidney and liver

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CT

HNE


-Vessie - Rectum

(Organs at risk, ICRU 50)

-GTV: Gross Tumor Volume

(Target volume, ICRU 50)

Transverse slice

Coronal reconstruction

Organs delineation on CT3-D paintbrush/eraser paradigm

HNE

HNE

Lo

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CT


Reference imaging

Guidance imaging

2006

1960

1970

1980

1990

2000CT

Simulator

Portal imaging

PET-CT

4D CT

MRI

Cone beam



Lo

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MR

I

MRI equipment for RO

Magnetic field

Courtesy of Philips Medical Systems

Antenna

Flat table top

Movable table

Movable lasers

•8


MRI technics of spatial acquisition

Freq.

Freq.

1. Excite one plane

2. Select one raw

3. Select one column

z gradient

Y g

rad

ien

t d

uri

ng

wa

itin

g p

ha

se

X gradient during reading phase

Phase Yi

Frequence Xi

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MR

I


Contrast by T-weighting

Relaxation times measured by special sequences

– T1: Longitudinal = spin-lattice

– T2: Transverse = spin-spin

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MR

I

Specific to tissue types


Prostate example

Better definition (apex)

Need training in fine

anatomy details (nerves,

muscles, …)

Different volumes

Courtesy of HUG

D

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MR

I


Examples of MRI artefacts

Black hole in dental filling

Distortion at field edges

Courtesy of HUG

Courtesy of HUG

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MR

I

FMH resident physics training in RO, PSI, 3/09/2007 : J.-F. Germond FMH resident physics training in RO, PSI, 3/09/2007 : J.-F. Germond

Modalities other than CT are mostly used as

complementary in RT:

Question: How to used them combined for

localization?

Answer: by 2 successive electronic manipulations:

1. Registration of the 2 sets of images by

a) Rigid method (ex: chamfer matching)b) Deformable method (ex: mutual information)

2. Display of the registrered images:

– Overlay of the 2 sets into one combined data set (fusion)

– Contour delineation on one modality and report in the other

– Constrained delineation

Ima

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Fusion of images

•9


a) Rigid 3D registration

Injected CT

HNE

CT data set

CHUV

T2 weighted

MRI data set

3 translations

3 rotations

Finds the best rigid transformation between 2 modalities

(chamfer matching for bones)

Ima

ge

fu

sio

n


Image of the day

Minimal cost

Reference image

Contours of interest

Cost function

)( refIBoneppCN

shiftIsocenter :

)(1

cost

T

rTIN

NSp

day

)(ref rI

)(rIday

Change T

)()( min rIrTI refday

ite

rati

on

Mathematics of rigid registration

Ima

ge

fu

sio

n

Chamfer matching

algorithm


CT data set MRI data set

b) Deformable 3D registration

Maximalize similarity measure

(mutual information)

HUGHUG

Indications:

Morphological changes

Respiratory movements

x Rectum filling

morphing

Ima

ge

fu

sio

n


Display of 2 data sets by colors superposition

Example of CT- MRI prostate fusion:

Usages:

Manual registration

Quick check of

registration quality

---

HUG

Ima

ge

fu

sio

n


Display of 2 data sets by colors addition

Modality 1: greycale mapped to RGB pink = (255,0,255)

Modality 2: greycale mapped to RGB green = (0,255,0)

Overlay on screen mapped to the sum of pixel intensities:

– Only modality 1 = pink

– Only modality 2 = green

– Identical : (255,0,255) + (0,255,0) = (255,255,255) = white

Localization CT in pink

CBCT of the day in green

Changes in

rectum filling

Usages:

Visualization of

morphology changes

Example of CT- CBCT fusion:

HNE

Ima

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fu

sio

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Display of 2 data sets by B&W + colorExample of PET- CT fusion:

Usages:

Assignement of CT

segmentation to tumor

“Tumor flashing”

Image from S. Senan S and D. De Ruysscher, Oncology Hematology, 2005

Ima

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•10


Display of 2 data sets side by side

Example of CT- MRI prostate registration:

Usages:

Synchronized windows

Sharing cursor

Simultaneous delineation

HUG HUG

Ima

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fu

sio

n


Organs delineation on CT - MRI

CT data setMRI data set

Example of prostate :

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MR

I

From J. Dipascale et al., SASRO meeting,Geneva, 2004

HUG HUG



Example of H&N :


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I



Example between different institutions :

Time evolution of edema ?

Geometrical distortions ?Adapt CTV margin

CHUV 10/3/06 HNE 7/4/06

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MR

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PTV: + Setup margin


ICRU 50 & 62

Functional imaging in

RO can be used for

delineating the GTV and

possibly the CTV

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•11


Technics able to detect specific compounds of tissue other than

water and fat (choline, creatine, N-AcetylAspartate)

Gives information about the level of alteration of metabolites in

tumor

MRS spectroscopy in gliomas

Peak Cho >Cr and

NAA in brain tumors

[Chang, Med.Phys.06]

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MR

S


MRS spectroscopy in prostate

Dose m

axim

aliz

ation

TumorREF

High concentration of choline inside the prostate =

tumor signature

Used for dose painting

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MR

S


SPECT equipment

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SP

EC

T

Photo HNe

Head 1

Head 2

Rotation

H&N mask system


Ga

ntry

an

gle

SPECT data acquisition

Emission profile

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SP

EC

T


Ga

ntry

an

gle


Emission profile

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tio

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SP

EC

T



Emission profile

Ga

ntry

an

gle

Sinogram

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SP

EC

T

•12


Example in H&N (Parathyroid Adenoma) :

SPECT- CT fusion

Lenox Hill Hospital, NY

Need specific calibration for quantitative use

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SP

EC

T


Example in glioma:

Tc-mici

Organs delineation on SPECT - CT

Recidive not seen on CT

GTV delineated on mici captation volume

SPECT GTV mapped to CT data set

HNEHNE Tc-mici

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SP

EC

T


Perfusion withTc-99m

High value of perfusion = lung zone OK

Volume to spare in dose calculation

Mc Guire et al. (2006)

Perfusion segmentation on SPECT

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SP

EC

T


Reference imaging

Verification imaging

2006

1960

1970

1980

1990

2000CT

Simulator

Portal imaging

PET-CT

4D CT

MRI

Cone beam



PET- CT equipment

CT gantry

PET gantry

Lo

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PE

T


Flat table top

± movable lasers


Ga

ntry

an

gle

PET data acquisition

Emission profile

Sinogram

Positron emission and annihilation

Lo

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PE

T

•13


PET – CT fusion

Topography of structures are difficult to localize on pure PET images

but much easier to read on PET- CT fused images

Source: R. Bridwell, PETLinQ, 2006

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PE

T


Example of glioma:

FDG

Organs delineation on PET - CT

Cavity correctly mapped between PET and CT

GTV delineated on CT correspond to FDG fixation

Increase CTV to involve all the FDG fixation volume

GTV ?

CHUV HNE

But boundary depends

on grey level intensities

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PE

T


Semiquantitative index based on ROI values

Formula:

SUV = 1 if radiotracer is uniformly distributed within the

organism

Calculation of SUV requires corrections for:

– Photons attenuation and scatter

– Organ motion

– Partial volume effect

Present recommandations for GTV delineation are

– SUV > 2.5

– SUV > 40% of maximum SUV

Standart Uptake Value (SUV)

weightpatient activity / Injected

ROI) of Volume / ROI in(Activity SUV

Lo

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PE

T

But sites and

technics dependentD


Comparison between PET and CT scales

Example for lung tumors:

PET :

Standard Uptake Value SUV

Concentration of radiotracer

Scale: 0 to 14

CT :

Houndsfield numbers HN

Tissue absorption coefficients

Scale: -1000 to + 1000

Images from S. Senan S and D. De Ruysscher, Oncology Hematology, 2005

FDG

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PE

T



Example in oropharynx :

Organs delineation on PET - CT

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PE

T


Limitation of delineation on PET - CT

Images from U. Nestle et al., J. Nuclear Medicine, 2005

SUV 2.5

SUV 40%

CT

Example for lung tumors:

FDG

D Corrections for the determination of radiotracer

concentration (FDG)

DModelisation of the fixation metabolism (FDG different

from glucose)

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PE

T

PET-CT is not yet the panacea for delineationD

•14


3D virtual patient

D frozen

3D model of images

Slice séparation

3D virtual patient

Voxel definition

Example:

100 images, 512 * 512 pixels

= 26.2 millions of voxels !!

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3D


Surface rendering

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3D


• The contoured organs

are becoming 3D objets

• The isocenter

(barycenter) of the target

volume (GTV) is defining

the position of the objects

system

• The isocenter is spotted

by an orthogonal system

of coordinates

Isocenter

3D model of contours L

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tio

nin

3D


The lasers system

mimics the orthogonal

system of coordinates

The patient is tattoed at

the lasers intersections

with the skin

Patient marking

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3D


•15





PTV: + Setup margin


ICRU 50 & 62

4D

im

ag

ing

4D imaging in RO can

be used for assessing

the ITV


Respiratory motion artefacts

Helical CT: 1 turn / s

Frozen virtual patient

Inter-slices artifacts

4D

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2D MPR 3D rendering


Courtesy of Philips Medical SystemsCourtesy of Philips Medical Systems

4D

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Internal organs movements

Respiration affects the localization of many organs:


Reference imaging


2006

1960

1970

1980

1990

2000CT

Simulator

Portal imaging

PET-CT

4D CT

MRI

Cone beam



How to manage respiratory artefacts?

4D

Lo

ca

liza

tio

n

Slow scanning technics

Blurring

PET

4D scanning

Prospective (gating)

Retrospective (sorting)

Requires the

measurement of the

respiratory phases


4D

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Pneumatic bellow RPM from Varian

Spirometer Dyn’R Spirometer ABC Elekta

Equipment for measuring respiratory phases

•16


Multislices axial 4D-CT

CT images sorted by

respiratory phases

Example of lung tumor

Colors = time spent in

this position

90%

10%

4D

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Organs delineation on 4D-CT


Low pitch spiral 4D-CT

1 GTV per respiratory phase

90%

10% Example of lung tumor

Internal Target Volume(ITV)


CT images sorted by

respiratory phases

4D

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Organs delineation on 4D-CT



Localization

Virtual

simulation

Dose

planification

Guidance

Irradiation

See also delivery and

verification session


Virtual simulation in RO Goal:

Find the optimal balistic for irradiation

– which cover the target volume,

– Which spares the organs at risk.

Material:

Computer softwares(3D virtual simulation)

– Digitally Reconstructed Radiographs (DRR)

– Beam Eye View (BEV)

Method:

Beams conformation to target volume

– Choice of gantry angles

– Adaptation of the multileaves collimator (MLC)

Vir

tua

l s

imu

lati

on


Absorption :Curved integration

Windowing :Remapping LUT table

Ray tracing :

Siddon’s method

Interpolation :Trilinear or cubic

Reconstruction algorithm:Abrams et Goitein, 1983

Technics of DRR’s reconstruction

Digitally Recontructed Radiographs(DRR)

Vir

tua

l s

imu

lati

on


Absorption :Curved integration

Windowing :Remapping LUT table

Ray tracing :

Siddon’s method

Interpolation :Trilinear or cubic

Reconstruction algorithm:Abrams et Goitein, 1983

i

iii dlA exp

wateri

i

HN

1

1000

LUTi

i voxeli

numbers Hounsfield iHN

D Pure mathematics

Technics of DRR’s reconstruction

Digitally Recontructed Radiographs(DRR)

Vir

tua

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imu

lati

on

•17


Beam Eye View method of virtual simulation

Anterio-Posterior beam

Example of conformation on the prostate :

L-R Lateral beam

DRR

MLC

GTV

Vir

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imu

lati

on

Fusion of the projection

of structures with DRR’s



Localization

Virtual

simulation

Dose

planification

Guidance

IrradiationSee treatment

planning sessions



Localization

Virtual

simulation

Dose

planification

Guidance

Irradiation

See also delivery and






PTV: + Setup margin


ICRU 50 & 62

Ima

ge

gu

ida

nc

e

Image guidance in RO can

be used for assessing the

setup margin


Image guidance in RO Goal:

Check the treatment position of the patient

– Position of the target volume

– Position of the organs at risk

Material:

Imaging inside the treatment room

– With the iradiation beam (portal images)

– With an additional 3D imaging system (Echography,

CBCT,…)

Method:

Registration with reference images

– DRR from virtual simulation(2D)

– CT slices from localization (3D)

Ima

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Various implementations of image guidance

Electronic portal imaging :

– Set of 2D orthogonal portal images

– Golden markers

– MV CBCT

Embarked kV imaging systems :

– Radiography

– Fluoroscopy

– CBCT

Topometrical positioning systems

Tomotherapy

Stereoscopic kV imaging

CT on rails

Echography

O-ring linac

MR-Linac

Ima

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ida

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•18


Reference imaging


2006

1960

1970

1980

1990

2000CT

Simulator

Portal imaging

PET-CT

4D CT

MRI

Cone beam



CollimatorFilter

am-Si panel Carbon fiber

table top

Elekta Synergy system in operation at HNE

X-ray tube

40-150kV

CB

CT

gu

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Cone Beam CT equipment


Rotation to 260°

CB

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Irradiation from 260° to 100°C

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Irradiation from 260° to 100°

CB

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CB

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•19



CB

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CB

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Filtration

Back-projection

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FDK algorithm

CBCT 3D reconstruction

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Skull H&N Lung

Bladder ProstateVerterbras

Clinical images from HNE

Examples of CBCT imagesC

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Setup margins verification:

PTVInter-fractions motion:

• translations

• rotations

• deformations

Intra-fraction motion

measured by 4D IGRT:

• breathing

ITV

Courtesy of AVL

Clinical uses of CBCT images 1/2

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Morphological changes :

Inter-fractions variations:

• Tumor response

• Weight loss

Intra-fraction variations

• gaz

• Swallowing

Clinical uses of CBCT images 2/2

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CT

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Localization

Virtual

simulation

Dose

planification

Guidance

Irradiation

See delivery and




Imaging is present in 75% of the RO workflow

Localization serves as reference for planning and

irradiation delivery

– Delineation by radio-oncologist

– ICRU as normative framework

– Beware of the intrinsic limitations of modalities

The evolution of localization involves:

– Fusion of modalities

– Functional imaging

– 4D imaging

Always use your judgment expertise to accept delineation

in fused set of data

Take home message 1/2


Imaging during treatment (guidance) involves the

registration of the image of the day with a localization

image used as reference

– 2D: matching of portal imaging with DRR’s

– 3D: registration between CBCT and CT

The evolution of guidance involves:

– Fusion of images

– Tracking of organs

– 4D guidance

Always use your judgment expertise to accept patient

setup adaptation

Take home message 2/2


Myriam Ayadi (CLB, Lyon)

Giovanna Pasquale (HUG, Genève)

Francis Verdun (IRA, Lausanne)

Frédéric Corminboeuf (Inselspital, Bern)

Markus Notter, Pascal Baudet (HNE, La Chaux-de-Fonds)

Stéphane Montandon (PMS, Gland)

Carlos Rodriges (PMS, Fitchburg)

Special acknowledgements


Sometimes imaging = miraging

Thank you for your attention?

Documents

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