observer study of reconstruction strategies for detection of solitary pulmonary nodules using hybrid...
Post on 19-Dec-2015
217 views
TRANSCRIPT
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 (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
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.
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
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
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.