Xubin Li1, Kun Zhang1, Yan Shi2, Fengkui Wang1, Xiangfu Meng3. 1. Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin, China. 2. Department of Radiology, Guiyang First People's Hospital, Guizhou, China. 3. Department of Radiology, Linyi Traditional Chinese Medicine Hospital, Shandong, China.
Abstract
PURPOSE: To investigate the correlations between the minimum and mean apparent diffusion coefficient (ADC) values of hepatocellular carcinoma (HCC) and pathological grade. MATERIALS AND METHODS: Preoperative magnetic resonance imaging (MRI) images of 241 patients with HCC confirmed by pathology were retrospectively analyzed. All patients underwent preoperative diffusion-weighted imaging (DWI) on a 1.5T MRI scanner. The mean and minimum ADC values of the tumors were measured. The ADC values were compared in tumors with different grades and the correlations between ADC values and pathological grade were analyzed. Receiver operating characteristic (ROC) curves of ADC values were obtained and compared to distinguish poorly and nonpoorly differentiated HCCs. Interobserver agreements were assessed by intraclass correlation coefficient (ICC). RESULTS: The mean and minimum ADC values of poorly differentiated HCCs were lower than those of nonpoorly differentiated HCCs (P = 0.000, 0.000, respectively). The mean and minimum ADC values were negatively correlated with pathological grade (rs = -0.180 and -0.202, respectively) (P = 0.005, 0.002, respectively). For the differentiation between poorly and nonpoorly differentiated HCCs, the mean ADC value provided a sensitivity of 69.57% and a specificity of 73.39% with a cutoff value of 0.96 × 10-3 mm2 /s while the minimum ADC value showed a sensitivity of 78.26% and a specificity of 61.47% with a cutoff value of 0.90 × 10-3 mm2 /s. No significant difference existed between both ROC curves (P = 0.64). The ICC for the measurements of the mean and minimum ADC values was 0.92 (95% confidence interval [CI] 0.90-0.93) and 0.91 (95% CI 0.89-0.93), respectively. CONCLUSION: DWI of HCC could preoperatively provide quantitative parameters for predicting tumor histological grade. J. Magn. Reson. Imaging 2016;44:1442-1447.
PURPOSE: To investigate the correlations between the minimum and mean apparent diffusion coefficient (ADC) values of hepatocellular carcinoma (HCC) and pathological grade. MATERIALS AND METHODS: Preoperative magnetic resonance imaging (MRI) images of 241 patients with HCC confirmed by pathology were retrospectively analyzed. All patients underwent preoperative diffusion-weighted imaging (DWI) on a 1.5T MRI scanner. The mean and minimum ADC values of the tumors were measured. The ADC values were compared in tumors with different grades and the correlations between ADC values and pathological grade were analyzed. Receiver operating characteristic (ROC) curves of ADC values were obtained and compared to distinguish poorly and nonpoorly differentiated HCCs. Interobserver agreements were assessed by intraclass correlation coefficient (ICC). RESULTS: The mean and minimum ADC values of poorly differentiated HCCs were lower than those of nonpoorly differentiated HCCs (P = 0.000, 0.000, respectively). The mean and minimum ADC values were negatively correlated with pathological grade (rs = -0.180 and -0.202, respectively) (P = 0.005, 0.002, respectively). For the differentiation between poorly and nonpoorly differentiated HCCs, the mean ADC value provided a sensitivity of 69.57% and a specificity of 73.39% with a cutoff value of 0.96 × 10-3 mm2 /s while the minimum ADC value showed a sensitivity of 78.26% and a specificity of 61.47% with a cutoff value of 0.90 × 10-3 mm2 /s. No significant difference existed between both ROC curves (P = 0.64). The ICC for the measurements of the mean and minimum ADC values was 0.92 (95% confidence interval [CI] 0.90-0.93) and 0.91 (95% CI 0.89-0.93), respectively. CONCLUSION: DWI of HCC could preoperatively provide quantitative parameters for predicting tumor histological grade. J. Magn. Reson. Imaging 2016;44:1442-1447.
Authors: Yeo Eun Han; Yongwon Cho; Min Ju Kim; Beom Jin Park; Deuk Jae Sung; Na Yeon Han; Ki Choon Sim; Yang Shin Park; Bit Na Park Journal: Abdom Radiol (NY) Date: 2022-09-21
Authors: Alexey Surov; Maciej Pech; Jazan Omari; Frank Fischbach; Robert Damm; Katharina Fischbach; Maciej Powerski; Borna Relja; Andreas Wienke Journal: Liver Cancer Date: 2021-01-27 Impact factor: 11.740