2010
DOI: 10.1016/j.ijrobp.2009.07.1681
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Comparison of 18F-Fluorothymidine and 18F-Fluorodeoxyglucose PET/CT in Delineating Gross Tumor Volume by Optimal Threshold in Patients With Squamous Cell Carcinoma of Thoracic Esophagus

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Cited by 65 publications
(61 citation statements)
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“…When imaging parameters are varied, larger differences in SUV test-retest variability were seen for 18 F-FLT than for 18 F-FDG, probably because of the lower SUV for 18 F-FLT. Previously, in a comparative study, it was shown that mean maximal SUV in all lesions was lower for 18 F-FLT than for 18 F-FDG (20).…”
Section: Discussionmentioning
confidence: 85%
“…When imaging parameters are varied, larger differences in SUV test-retest variability were seen for 18 F-FLT than for 18 F-FDG, probably because of the lower SUV for 18 F-FLT. Previously, in a comparative study, it was shown that mean maximal SUV in all lesions was lower for 18 F-FLT than for 18 F-FDG (20).…”
Section: Discussionmentioning
confidence: 85%
“…18 F-FDG uptake in locoregional lymph node metastases was significantly higher than 18 18 F-FLT also better delineated gross tumor volume for radiation treatment planning, with improved sparing of the lungs and heart (45). In another study, on 10 patients with biopsy-proven esophageal and gastroesophageal cancer, 18 F-FDG PET was able to detect all esophageal cancers whereas 18 F-FLT PET visualized the tumor in only 8 of the 10 patients.…”
Section: Gastrointestinal Cancersmentioning
confidence: 94%
“…Zaidi et al [50] used the Louvain LSCC data set [25] to compare the performance of nine algorithms including five threshold methods, a level set method, a stochastic expectationmaximization method, fuzzy clustering-based segmentation (FCM) and a spatial wavelet-based FCM (FCM-SW) and found FCM-SW to be most accurate. Markel et al [51] also used the Louvain LSCC data set [25] to evaluate a Fixed thresholds (SUV and % of maximum) [38,39,40] Adaptive threshold (signal-to-background ratio based) [25,46,50,52] Gradient [39,47] Fuzzy C-means [48,50] Active contours [49,50] Possibility theory [53] Multimodality using level sets [51] Esophagus Fixed threshold (SUV and % of maximum) [41,42] Visual [41,42] Non-small-cell lung cancer (NSCLC)…”
Section: Evaluation Of Pet Segmentation Methodsmentioning
confidence: 99%
“…Han et al [42] segmented their FLT PET images using visual delineation and several thresholds (SUV cutoffs of 1.3, 1.4, 1.5, and taking 20, 25 and 30 % of the SUV max ). For their FDG PET image segmentation they used: visual delineation, SUV 2.5, and 40 % of SUV max .…”
Section: Evaluation Of Pet Segmentation Methodsmentioning
confidence: 99%
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