Mai Kim1, Arifudin Achmad2, Tetsuya Higuchi3, Yukiko Arisaka3, Hideaki Yokoo4, Satoshi Yokoo5, Yoshito Tsushima3. 1. Department of Stomatology and Maxillofacial Surgery, Gunma University Graduate School of Medicine, Maebashi, Gunma, Japan Department of Diagnostic Radiology and Nuclear Medicine, Gunma University Graduate School of Medicine, Maebashi, Gunma, Japan kimmu@gunma-u.ac.jp. 2. Department of Diagnostic Radiology and Nuclear Medicine, Gunma University Graduate School of Medicine, Maebashi, Gunma, Japan Human Resource Cultivation Center, Gunma University, Kiryu, Gunma, Japan Department of Radiology, Faculty of Medicine, Gadjah Mada University, Yogyakarta, Indonesia; and. 3. Department of Diagnostic Radiology and Nuclear Medicine, Gunma University Graduate School of Medicine, Maebashi, Gunma, Japan. 4. Department of Human Pathology, Gunma University Graduate School of Medicine, Maebashi, Gunma, Japan. 5. Department of Stomatology and Maxillofacial Surgery, Gunma University Graduate School of Medicine, Maebashi, Gunma, Japan.
Abstract
UNLABELLED: The accurate depiction of both biologic and anatomic profiles of tumors has long been a challenge in PET imaging. An inflammation, which is innate in the carcinogenesis of oral squamous cell carcinoma (OSCC), frequently complicates the image analysis because of the limitations of (18)F-FDG and maximum standardized uptake values (SUV(max)). New PET parameters, metabolic tumor volume (MTV) and total lesion glycolysis (TLG), as well as (18)F-fluoro-α-methyltyrosine ((18)F-FAMT), a malignancy-specific amino acid-based PET radiotracer, are considered more comprehensive in tumor image analysis. Here, we showed the substantial effects of the intratumoral inflammatory process on (18)F-FDG uptake and further study the possibility of MTV and TLG to predict both tumor biology (proliferation activity) and anatomy (pathologic tumor volume). METHODS: (18)F-FDG and (18)F-FAMT PET images from 25 OSCC patients were analyzed. SUV(max) on the tumor site was obtained. PET volume computerized-assisted reporting was used to generate a volume of interest to obtain MTV and TLG for (18)F-FDG and total lesion retention (TLR) for (18)F-FAMT. The whole tumor dissected from surgery was measured and sectioned for pathologic analysis of tumor inflammation grade and Ki-67 labeling index. RESULTS: The high SUV(max) of (18)F-FDG was related to the high inflammation grade. The SUV(max )ratio of (18)F-FDG to (18)F-FAMT was higher in inflammatory tumors (P < 0.05) whereas the corresponding value in tumors with a low inflammation grade was kept low. All (18)F-FAMT parameters were correlated with Ki-67 labeling index (P < 0.01). Pathologic tumor volume predicted from MTV of (18)F-FAMT was more accurate (R = 0.90, bias = 3.4 ± 6.42 cm(3), 95% confidence interval = 0.77-6.09 cm(3)) than that of (18)F-FDG (R = 0.77, bias = 8.1 ± 11.17 cm(3), 95% confidence interval = 3.45-12.67 cm(3)). CONCLUSION: (18)F-FDG uptake was overestimated by additional uptake related to the intratumoral inflammatory process, whereas (18)F-FAMT simply accumulated in tumors according to tumor activity as evaluated by Ki-67 labeling index in OSCC.
UNLABELLED: The accurate depiction of both biologic and anatomic profiles of tumors has long been a challenge in PET imaging. An inflammation, which is innate in the carcinogenesis of oral squamous cell carcinoma (OSCC), frequently complicates the image analysis because of the limitations of (18)F-FDG and maximum standardized uptake values (SUV(max)). New PET parameters, metabolic tumor volume (MTV) and total lesion glycolysis (TLG), as well as (18)F-fluoro-α-methyltyrosine ((18)F-FAMT), a malignancy-specific amino acid-based PET radiotracer, are considered more comprehensive in tumor image analysis. Here, we showed the substantial effects of the intratumoral inflammatory process on (18)F-FDG uptake and further study the possibility of MTV and TLG to predict both tumor biology (proliferation activity) and anatomy (pathologic tumor volume). METHODS: (18)F-FDG and (18)F-FAMT PET images from 25 OSCC patients were analyzed. SUV(max) on the tumor site was obtained. PET volume computerized-assisted reporting was used to generate a volume of interest to obtain MTV and TLG for (18)F-FDG and total lesion retention (TLR) for (18)F-FAMT. The whole tumor dissected from surgery was measured and sectioned for pathologic analysis of tumor inflammation grade and Ki-67 labeling index. RESULTS: The high SUV(max) of (18)F-FDG was related to the high inflammation grade. The SUV(max )ratio of (18)F-FDG to (18)F-FAMT was higher in inflammatory tumors (P < 0.05) whereas the corresponding value in tumors with a low inflammation grade was kept low. All (18)F-FAMT parameters were correlated with Ki-67 labeling index (P < 0.01). Pathologic tumor volume predicted from MTV of (18)F-FAMT was more accurate (R = 0.90, bias = 3.4 ± 6.42 cm(3), 95% confidence interval = 0.77-6.09 cm(3)) than that of (18)F-FDG (R = 0.77, bias = 8.1 ± 11.17 cm(3), 95% confidence interval = 3.45-12.67 cm(3)). CONCLUSION: (18)F-FDG uptake was overestimated by additional uptake related to the intratumoral inflammatory process, whereas (18)F-FAMT simply accumulated in tumors according to tumor activity as evaluated by Ki-67 labeling index in OSCC.