PURPOSE: The aim of this study is to investigate the role of standard uptake values (SUVs) and metabolic tumor volume (MTV) in [(18)F]fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) to predict the short-term outcome of chemoradiotherapy (CRT) in patients with advanced non-small cell lung cancer (NSCLC). METHODS: A total of 37 patients were included in the prospective study. All patients were evaluated by FDG PET before and following 40 Gy radiotherapy (RT) with a concurrent cisplatin-based chemotherapy regimen. Semiquantitative assessment was used to determine maximum and mean SUVs (SUV(max)/SUV(mean)) and metabolic tumor volume (MTV). Short-term outcome using the treatment response evaluation was assessed according to the Response Evaluation Criteria in Solid Tumors. The receiver-operating characteristic (ROC) curve analysis was used to determine the diagnostic accuracy of (18)F-FDG PET in identifying responders. RESULTS: Changes in SUV(max), SUV(mean), and MTV were significantly more pronounced in responders than in nonresponders (p = 0.002, 0.002, 0.000). The thresholds of SUV(max), SUV(mean), and MTV changes defined by ROC curve analysis were 37.2, 41.7, and 29.7%, respectively. The sensitivity, specificity, and accuracy of SUV(max) change for predicting tumor response were 83.3, 84.6, and 84.9%, respectively. The sensitivity, specificity, and accuracy of SUV(mean) change for predicting tumor response were 79.2, 100, and 88.8%, respectively. The sensitivity, specificity, and accuracy of MTV change for predicting tumor response were 91.7, 84.6, and 92.3%, respectively. CONCLUSION: SUV and MTV changes from two serial (18)F-FDG PET/CT scans, before and after initial CRT, allow prediction of the treatment response in advanced NSCLC.
PURPOSE: The aim of this study is to investigate the role of standard uptake values (SUVs) and metabolic tumor volume (MTV) in [(18)F]fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) to predict the short-term outcome of chemoradiotherapy (CRT) in patients with advanced non-small cell lung cancer (NSCLC). METHODS: A total of 37 patients were included in the prospective study. All patients were evaluated by FDG PET before and following 40 Gy radiotherapy (RT) with a concurrent cisplatin-based chemotherapy regimen. Semiquantitative assessment was used to determine maximum and mean SUVs (SUV(max)/SUV(mean)) and metabolic tumor volume (MTV). Short-term outcome using the treatment response evaluation was assessed according to the Response Evaluation Criteria in Solid Tumors. The receiver-operating characteristic (ROC) curve analysis was used to determine the diagnostic accuracy of (18)F-FDG PET in identifying responders. RESULTS: Changes in SUV(max), SUV(mean), and MTV were significantly more pronounced in responders than in nonresponders (p = 0.002, 0.002, 0.000). The thresholds of SUV(max), SUV(mean), and MTV changes defined by ROC curve analysis were 37.2, 41.7, and 29.7%, respectively. The sensitivity, specificity, and accuracy of SUV(max) change for predicting tumor response were 83.3, 84.6, and 84.9%, respectively. The sensitivity, specificity, and accuracy of SUV(mean) change for predicting tumor response were 79.2, 100, and 88.8%, respectively. The sensitivity, specificity, and accuracy of MTV change for predicting tumor response were 91.7, 84.6, and 92.3%, respectively. CONCLUSION: SUV and MTV changes from two serial (18)F-FDG PET/CT scans, before and after initial CRT, allow prediction of the treatment response in advanced NSCLC.
Authors: P Therasse; S G Arbuck; E A Eisenhauer; J Wanders; R S Kaplan; L Rubinstein; J Verweij; M Van Glabbeke; A T van Oosterom; M C Christian; S G Gwyther Journal: J Natl Cancer Inst Date: 2000-02-02 Impact factor: 13.506
Authors: Hinrich A Wieder; Ambros J Beer; Florian Lordick; Katja Ott; Michael Fischer; Ernst J Rummeny; Sibylle Ziegler; Jörg R Siewer; Markus Schwaiger; Wolfgang A Weber Journal: J Nucl Med Date: 2005-12 Impact factor: 10.057
Authors: Giovanni L Ceresoli; Arturo Chiti; Paolo A Zucali; Marcello Rodari; Romano F Lutman; Silvia Salamina; Matteo Incarbone; Marco Alloisio; Armando Santoro Journal: J Clin Oncol Date: 2006-10-01 Impact factor: 44.544
Authors: Claude Nahmias; Wahid T Hanna; Lindi M Wahl; Misty J Long; Karl F Hubner; David W Townsend Journal: J Nucl Med Date: 2007-05 Impact factor: 10.057
Authors: Avani S Dholakia; Muhammad Chaudhry; Jeffrey P Leal; Daniel T Chang; Siva P Raman; Amy Hacker-Prietz; Zheng Su; Jonathan Pai; Katharine E Oteiza; Mary E Griffith; Richard L Wahl; Erik Tryggestad; Timothy Pawlik; Daniel A Laheru; Christopher L Wolfgang; Albert C Koong; Joseph M Herman Journal: Int J Radiat Oncol Biol Phys Date: 2014-04-18 Impact factor: 7.038
Authors: Matthew J Nyflot; Tzu-Cheng Lee; Adam M Alessio; Scott D Wollenweber; Charles W Stearns; Stephen R Bowen; Paul E Kinahan Journal: Med Phys Date: 2015-01 Impact factor: 4.071
Authors: Stephen R Bowen; Daniel S Hippe; W Art Chaovalitwongse; Chunyan Duan; Phawis Thammasorn; Xiao Liu; Robert S Miyaoka; Hubert J Vesselle; Paul E Kinahan; Ramesh Rengan; Jing Zeng Journal: Clin Cancer Res Date: 2019-05-29 Impact factor: 12.531
Authors: Christophe Van de Wiele; Vibeke Kruse; Peter Smeets; Mike Sathekge; Alex Maes Journal: Eur J Nucl Med Mol Imaging Date: 2012-11-14 Impact factor: 9.236