INTRODUCTION: PET/CT plays an important role in cancer diagnosis. Recently, novel metabolic parameters in PET/CT such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG) have been reported to be diagnostic and prognostic biomarkers of various cancers. We evaluated the diagnostic value of these metabolic parameters in colorectal cancer (CRC). METHODS: The study included 138 patients who underwent surgical resection of CRCs between August 2012 and March 2014. The MTVs and TLGs of tumors were measured using various SUV thresholds. The diagnostic abilities of the metabolic parameters were analyzed using ROC curves and classification and regression trees. RESULTS: The AUCs of the MTVs and TLGs for predicting T stage (0.881-0.892) were significantly higher than the AUC of the SUVmax (0.824). In the M stage, the AUCs of MTVs and TLGs (0.688-0.723) were significantly higher than that of the SUVmax (0.606). Recursive partitioning applying classification and regression trees demonstrated that the optimal cutoff values of the most important variables for discriminating T, N, and M stages are MTV2.5 = 9.35 and 63.33 mL, TLG50% = 328.1, and TLG50% = 94.81, respectively. CONCLUSION: Metabolic tumor volumes and TLGs in PET/CT are reliable diagnostic biomarkers. Using these parameters, more accurate preoperative diagnoses for CRC can be made.
INTRODUCTION: PET/CT plays an important role in cancer diagnosis. Recently, novel metabolic parameters in PET/CT such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG) have been reported to be diagnostic and prognostic biomarkers of various cancers. We evaluated the diagnostic value of these metabolic parameters in colorectal cancer (CRC). METHODS: The study included 138 patients who underwent surgical resection of CRCs between August 2012 and March 2014. The MTVs and TLGs of tumors were measured using various SUV thresholds. The diagnostic abilities of the metabolic parameters were analyzed using ROC curves and classification and regression trees. RESULTS: The AUCs of the MTVs and TLGs for predicting T stage (0.881-0.892) were significantly higher than the AUC of the SUVmax (0.824). In the M stage, the AUCs of MTVs and TLGs (0.688-0.723) were significantly higher than that of the SUVmax (0.606). Recursive partitioning applying classification and regression trees demonstrated that the optimal cutoff values of the most important variables for discriminating T, N, and M stages are MTV2.5 = 9.35 and 63.33 mL, TLG50% = 328.1, and TLG50% = 94.81, respectively. CONCLUSION:Metabolic tumor volumes and TLGs in PET/CT are reliable diagnostic biomarkers. Using these parameters, more accurate preoperative diagnoses for CRC can be made.
Authors: Barbara Juarez Amorim; Angel Torrado-Carvajal; Shadi A Esfahani; Sara S Marcos; Mark Vangel; Dan Stein; David Groshar; Onofrio A Catalano Journal: Mol Imaging Biol Date: 2020-10 Impact factor: 3.488
Authors: E J van Helden; Y J L Vacher; W N van Wieringen; F H P van Velden; H M W Verheul; O S Hoekstra; R Boellaard; C W Menke-van der Houven van Oordt Journal: Eur J Nucl Med Mol Imaging Date: 2018-08-09 Impact factor: 9.236
Authors: Shih-Hsin Chen; Kenneth Miles; Stuart A Taylor; Balaji Ganeshan; Manuel Rodriquez; Francesco Fraioli; Simon Wan; Asim Afaq; Robert Shortman; Darren Walls; Luke Hoy; Raymond Endozo; Aman Bhargava; Matthew Hanson; Joseph Huang; Sherif Raouf; Daren Francis; Shahab Siddiqi; Tan Arulampalam; Bruce Sizer; Michael Machesney; Nicholas Reay-Jones; Sanjay Dindyal; Tony Ng; Ashley M Groves Journal: Eur J Nucl Med Mol Imaging Date: 2021-04-10 Impact factor: 9.236