Hanwei Chen1, Jinzhao Jiang, Junling Gao, Dan Liu, Jan Axelsson, Minyi Cui, Nan-Jie Gong, Shi-Ting Feng, Liangping Luo, Bingsheng Huang. 1. From the *Department of Radiology, Guangzhou Panyu Central Hospital; †Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou; ‡Department of Radiology, Peking University Shenzhen Hospital, Shenzhen; §Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong Special Administrative Region, China; ∥Department of Radiation Sciences, Radiation Physics, Umeå University, Umeå, Sweden; ¶Department of Radiology, Hospital of Stomatology, Guanghua School of Stomatology; #Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China; and **Shenzhen University, Shenzhen, China.
Abstract
OBJECTIVE: The objective of this study was to compare the accuracy of calculating the primary tumor volumes using a gradient-based method and fixed threshold methods on the standardized uptake value (SUV) maps and the net influx of FDG (Ki) maps from positron emission tomography-computed tomography (PET-CT) images. MATERIALS AND METHODS: Newly diagnosed patients with head and neck cancer were recruited, and dynamic PET-CT scan and T2-weighted magnetic resonance imaging were performed. The maps of Ki and SUV were calculated from PET-CT images. The tumor volumes were calculated using a gradient-based method and a fixed threshold method at 40% of maximal SUV or maximal Ki. Four kinds of volumes, VOLKi-Gra (from the Ki maps using the gradient-based method), VOLKi-40% (from the Ki maps using the threshold of 40% maximal Ki), VOLSUV-Gra (from the SUV maps using the gradient-based method), and VOLSUV-40% (from the SUV maps using the threshold of 40% maximal SUV), were acquired and compared with VOLMRI (the volumes acquired on T2-weighted images) using the Pearson correlation, paired t test, and similarity analysis. RESULTS: Eighteen patients were studied, of which 4 had poorly defined tumors (PDT). The positron emission tomography-derived volumes were as follows: VOLSUV-40%, 2.1 to 41.2 cm (mean [SD], 12.3 [10.6]); VOLSUV-Gra, 2.2 to 28.1 cm (mean [SD], 13.2 [8.4]); VOLKi-Gra, 2.4 to 17.0 cm (mean [SD], 9.5 [4.6]); and VOLKi-40%, 2.7 to 20.3 cm (mean [SD], 12.0 [6.0]). The VOLMRI ranged from 2.9 to 18.1 cm (mean [SD], 9.1 [3.9]). The VOLKi-Gra significantly correlated with VOLMRI with the highest correlation coefficient (PDT included, R = 0.673, P = 0.002; PDT excluded, R = 0.841, P < 0.001) and presented no difference from VOLMRI (P = 0.672 or 0.561, respectively, PDT included and excluded). The difference between VOLKi-Gra and VOLMRI was also the smallest. CONCLUSIONS: The tumor volumes delineated on the Ki maps using the gradient-based method are more accurate than those on the SUV maps and using the fixed threshold methods.
OBJECTIVE: The objective of this study was to compare the accuracy of calculating the primary tumor volumes using a gradient-based method and fixed threshold methods on the standardized uptake value (SUV) maps and the net influx of FDG (Ki) maps from positron emission tomography-computed tomography (PET-CT) images. MATERIALS AND METHODS: Newly diagnosed patients with head and neck cancer were recruited, and dynamic PET-CT scan and T2-weighted magnetic resonance imaging were performed. The maps of Ki and SUV were calculated from PET-CT images. The tumor volumes were calculated using a gradient-based method and a fixed threshold method at 40% of maximal SUV or maximal Ki. Four kinds of volumes, VOLKi-Gra (from the Ki maps using the gradient-based method), VOLKi-40% (from the Ki maps using the threshold of 40% maximal Ki), VOLSUV-Gra (from the SUV maps using the gradient-based method), and VOLSUV-40% (from the SUV maps using the threshold of 40% maximal SUV), were acquired and compared with VOLMRI (the volumes acquired on T2-weighted images) using the Pearson correlation, paired t test, and similarity analysis. RESULTS: Eighteen patients were studied, of which 4 had poorly defined tumors (PDT). The positron emission tomography-derived volumes were as follows: VOLSUV-40%, 2.1 to 41.2 cm (mean [SD], 12.3 [10.6]); VOLSUV-Gra, 2.2 to 28.1 cm (mean [SD], 13.2 [8.4]); VOLKi-Gra, 2.4 to 17.0 cm (mean [SD], 9.5 [4.6]); and VOLKi-40%, 2.7 to 20.3 cm (mean [SD], 12.0 [6.0]). The VOLMRI ranged from 2.9 to 18.1 cm (mean [SD], 9.1 [3.9]). The VOLKi-Gra significantly correlated with VOLMRI with the highest correlation coefficient (PDT included, R = 0.673, P = 0.002; PDT excluded, R = 0.841, P < 0.001) and presented no difference from VOLMRI (P = 0.672 or 0.561, respectively, PDT included and excluded). The difference between VOLKi-Gra and VOLMRI was also the smallest. CONCLUSIONS: The tumor volumes delineated on the Ki maps using the gradient-based method are more accurate than those on the SUV maps and using the fixed threshold methods.
Authors: Carryn M Anderson; Wenqing Sun; John M Buatti; Joan E Maley; Bruno Policeni; Sarah L Mott; John E Bayouth Journal: Jacobs J Radiat Oncol Date: 2014-09
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