OBJECTIVE: The purpose of this article is to evaluate the interreader agreement and variability of two (18)F-FDG PET parameters, metabolic tumor volume and total lesion glycolysis, in human solid tumors. MATERIALS AND METHODS: One hundred eleven patients (mean [± SD] age, 61.9 ± 12.5 years) with baseline staging FDG PET/CT scans were included. Two readers independently read the scans and segmented metabolic tumor volume and total lesion glycolysis using two fixed thresholds, 40% and 50% of the lesion's maximum standardized uptake value (SUVmax). The impact of the lesion's FDG avidity and location on reader agreement and variability was established. Intraclass correlation coefficient (ICC), precision, and Bland-Altman analysis were used to evaluate agreement and variability. RESULTS: The ICCs for 40% and 50% SUVmax segmentations of metabolic tumor volume between the readers were 0.987 and 0.995, and the corresponding values for 40% and 50% SUVmax segmentations of total lesion glycolysis were 0.987 and 0.986, respectively (p = 0.0001). The corresponding precisions were 0.5%, 0.2%, 0.5%, and 0.5%, respectively. The mean biases between the readers for 40% and 50% SUVmax segmentations of metabolic tumor volume were -1.78 ± 8.42 mL and -0.46 ± 2.1 mL and for 40% and 50% SUVmax segmentations of total lesion glycolysis were -7.3 ± 31.6 g and -2.97 ± 12.86 g, respectively. Subgroup analysis showed better precision and lesser variability for 50% SUVmax segmentations of metabolic tumor volume and total lesion glycolysis in patients with the highest and lowest FDG-avid primary tumors. The precision was highest and variability was lowest for lung tumors. CONCLUSION: There is excellent interreader agreement for measurement of metabolic tumor volume and total lesion glycolysis with 40% and 50% SUVmax threshold segmentations in human solid tumors.
OBJECTIVE: The purpose of this article is to evaluate the interreader agreement and variability of two (18)F-FDG PET parameters, metabolic tumor volume and total lesion glycolysis, in humansolid tumors. MATERIALS AND METHODS: One hundred eleven patients (mean [± SD] age, 61.9 ± 12.5 years) with baseline staging FDG PET/CT scans were included. Two readers independently read the scans and segmented metabolic tumor volume and total lesion glycolysis using two fixed thresholds, 40% and 50% of the lesion's maximum standardized uptake value (SUVmax). The impact of the lesion's FDG avidity and location on reader agreement and variability was established. Intraclass correlation coefficient (ICC), precision, and Bland-Altman analysis were used to evaluate agreement and variability. RESULTS: The ICCs for 40% and 50% SUVmax segmentations of metabolic tumor volume between the readers were 0.987 and 0.995, and the corresponding values for 40% and 50% SUVmax segmentations of total lesion glycolysis were 0.987 and 0.986, respectively (p = 0.0001). The corresponding precisions were 0.5%, 0.2%, 0.5%, and 0.5%, respectively. The mean biases between the readers for 40% and 50% SUVmax segmentations of metabolic tumor volume were -1.78 ± 8.42 mL and -0.46 ± 2.1 mL and for 40% and 50% SUVmax segmentations of total lesion glycolysis were -7.3 ± 31.6 g and -2.97 ± 12.86 g, respectively. Subgroup analysis showed better precision and lesser variability for 50% SUVmax segmentations of metabolic tumor volume and total lesion glycolysis in patients with the highest and lowest FDG-avid primary tumors. The precision was highest and variability was lowest for lung tumors. CONCLUSION: There is excellent interreader agreement for measurement of metabolic tumor volume and total lesion glycolysis with 40% and 50% SUVmax threshold segmentations in humansolid tumors.
Authors: Jérémie Calais; Bernard Dubray; Lamyaa Nkhali; Sebastien Thureau; Charles Lemarignier; Romain Modzelewski; Isabelle Gardin; Frederic Di Fiore; Pierre Michel; Pierre Vera Journal: Eur J Nucl Med Mol Imaging Date: 2015-02-14 Impact factor: 9.236
Authors: Abhinav K Jha; Esther Mena; Brian Caffo; Saeed Ashrafinia; Arman Rahmim; Eric Frey; Rathan M Subramaniam Journal: J Med Imaging (Bellingham) Date: 2017-03-03
Authors: Ray Y Chen; Lori E Dodd; Myungsun Lee; Praveen Paripati; Dima A Hammoud; James M Mountz; Doosoo Jeon; Nadeem Zia; Homeira Zahiri; M Teresa Coleman; Matthew W Carroll; Jong Doo Lee; Yeon Joo Jeong; Peter Herscovitch; Saher Lahouar; Michael Tartakovsky; Alexander Rosenthal; Sandeep Somaiyya; Soyoung Lee; Lisa C Goldfeder; Ying Cai; Laura E Via; Seung-Kyu Park; Sang-Nae Cho; Clifton E Barry Journal: Sci Transl Med Date: 2014-12-03 Impact factor: 17.956
Authors: Andreas G Wibmer; Michael J Morris; Mithat Gonen; Junting Zheng; Hedvig Hricak; Steven Larson; Howard I Scher; Hebert Alberto Vargas Journal: J Nucl Med Date: 2021-01-08 Impact factor: 10.057