Observer Study of Reconstruction Strategies for Detection of

Solitary Pulmonary Nodules Using Hybrid NeoTect SPECT

Images

Xiaoming Zheng, PhD.

20 October, 2004

Outlines

• Lung Cancer and SPECT/PET

• NeoTect in Lung SPECT

• Image Reconstructions: RBI vs FBP

• Hybrid Images: Clinical Reality

• Observer Studies: Human vs Numerical

• ROC: Receiver Operating Characteristics

• Results and Conclusions

180,570

110,669

76,03059,08855,704

328,365

 Lung

 Colon/Rectum

 Breast

 Stomach

 Prostate

Others

Leading Causes of Cancer Deaths

NSCLC: Non-Small-Cell-Lung-Cancer

• Surgery is providing the best chance of cure if tumor can be re-sected completely.

• If cancer has spread to contra-lateral lymph nodes or beyond the chest surgery alone is not useful. Chemotherapy and/or radiotherapy are usually applied. These measures are rarely curative

SPN: Solitary Pulmonary Nodule

• Approx. 30% of new cases of lung cancer are found as an SPN

• An SPN is defined as:– single pulmonary lesion– well defined borders– mean diameter not more than 3 cm

• Found in 1 : 500 chest X-rays

SPECT and PET

(With chest X-Ray)

NeoTect- SPECT

FDG - PET

Patients 114 89

Sensitivity 97% 98%

Specificity 73% 69%

Accuracy 91% 89%

NeoTect/SPECT vs FDG/PETF

DG

-PE

TF

DG

-PE

TN

eo

Sp

ec

tN

eo

Sp

ec

t P

P

L P

P

PL

P

NeoTect (99mTc-Depreotide)

• Binds to Somatostatin receptors, which are over-expressed in lung cancer (NSCLC and SCLC)

• Has a negative predictive value of up to 98% in combination with CT or chest X-ray for SPN

• Procedure is non-invasive

• 99mTc-labelled - readily available

• Procedure is easy

• Can be used wherever SPECT is available

Hcy-Val

(N-Me)Phe-Tyr

Lys

D-Trp

ON N

H2NSNH

OO

NH

NH2

O

H2N

O

NH2

Tc

O

Binding region for

SSTR*

- a small synthetic peptide- 10 amino acids, mol. wt. 1358 Da- binding region for the somatostatin receptor- radio-labeled with 99mTc

NeoTect

How NeoTect Works

–Malignant tumors over-express somatostatin receptors (SSTRs)

–NeoTect binds to and detects SSTRs

–Most benign lesions do not over-express SSTRs

Normal Transaxial SPECT Images

CT

72 yr female smoker, complaining of weight loss; chest x-ray: 2.5 cm LUL lesion; CT: LUL 2.0 cm spiculated mass; Histopathology (CT guided FNA biopsy): poorly-differentiated adenocarcinoma

Coronal SPECT

Transaxial SPECT

Aims of This Work

• Use hybrid images of lung tumor imaging agent Tc-99m NeoTect in Localization Receiver Operating Characteristic (LROC) studies to determine reconstruction parameters and whether iterative reconstruction with attenuation, scatter, and distant resolution compensation should replace FBP clinically.

Why Hybrid Images

• The Optimization of reconstruction parameters, and determination of whether iterative reconstruction should replace FBP clinically should be based on tasks which closely approximate the clinical application of the images

• The use of hybrid images or studies represents a practical alternative to the use of purely clinical acquisitions for observer studies.

How Hybrid Images Were Created

• Simulated lesions are added to know normal clinical acquisitions

• Monte Carlo simulation package SIMIND was used to simulate lesions.

• Nine normal patient’s projection data were used to create 162 tumors randomly distributed within the lung regions.

• Tumors were 1 cm in diameter which is the smallest tumor could be detected by CT.

NeoTect ProjectionsFrom Clinical 9 Patients

Tumor Source ProjectionsFrom Monte Carlo Simulation

Images Reconstructions

• Iterative Reconstruction: Rescaled Block Iterative Algorithm including attenuation, scatter, and distance resolution compensation. Parameters tested: iteration 1,3,5,7,10 and post Gaussian filter FWHM 0,1,2,3,4 pixels

• Filtered Back-Projection: Parameters tested: Butterworth filter cut-off frequencies: 0.10, 0.15, 0.20, 0.25 and 0.30 pixel-1

Filtered Back-Projection

Butterworth Filter and Cutoff Frequency

FBP Reconstructed Images

Iterative Reconstruction

Rescaled Block Iterative Reconstruction Algorithm

f fca

f

a HH

d Snk

nk rn

r

nk

r mnm

mnm S

m m

mr

1 1'

Hf k

c

H

Ha crn

mnm S

mnm

r rnr

; max

Attenuation Compensation

Scatter Compensation

S WCW

CW

' .

5 2

1

1

3

3

Resolution Compensation

RBI Reconstructed Images

Receiver Operating Characteristics

Images for Observers

Numerical Observers

Types of Channels

Human

Observer

Interface

RBI

Human

Observer

Interface

FBP

Numerical Observer Results: RBI

Numerical Observer Results: FBP

Human Observer Results

Conclusions

• Iterative RBI-EM including all corrections performs better than that of FBP.

• The best performance reconstruction strategy is RBI-EM with 5 iteration and 1 pixel FWHM in Gaussian post-filtering.

• Numerical observer with and without mean background subtraction set the upper and lower bounds achievable by human observer.

Acknowlegements

• This work was supported by a Charles Sturt University Special Study grant and a NIH research grant.

• The co-authors of this work are Prof Mike King, Dr Howard Gifford and Dr Hennie Pretorius at the University of Massachusetts Medical School.