Hai-Ming Li1,2, Feng Feng2, Jin-Wei Qiang3, Guo-Fu Zhang4, Shu-Hui Zhao5, Feng-Hua Ma6, Yong-Ai Li1, Wei-Yong Gu7. 1. Department of Radiology, Jinshan Hospital, Fudan University, 1508 Longhang Road, Shanghai, 201508, China. 2. Department of Radiology, Nantong Cancer Hospital, Nantong University, Nantong, 226361, Jiangsu, China. 3. Department of Radiology, Jinshan Hospital, Fudan University, 1508 Longhang Road, Shanghai, 201508, China. dr.jinweiqiang@163.com. 4. Department of Radiology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, 200011, China. guofuzh@msn.com. 5. Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University, Shanghai, 200092, China. 6. Department of Radiology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, 200011, China. 7. Department of Pathology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, 200011, China.
Abstract
PURPOSE: This study aimed to investigate the diagnostic performance of quantitative DCE-MRI for characterizing ovarian tumors. METHODS: We prospectively assessed the differences of quantitative DCE-MRI parameters (Ktrans, kep, and ve) among 15 benign, 28 borderline, and 66 malignant ovarian tumors; and between type I (n = 28) and type II (n = 29) of epithelial ovarian carcinomas (EOCs). DCE-MRI data were analyzed using whole solid tumor volume region of interest (ROI) method, and quantitative parameters were calculated based on a modified Tofts model. The non-parametric Kruskal-Wallis test, Mann-Whitney U test, Pearson's chi-square test, intraclass correlation coefficient (ICC), variance test, and receiver operating characteristic curves (ROC) were used for statistical analysis. RESULTS: The largest Ktrans and kep values were observed in ovarian malignant tumors, followed by borderline and benign tumors (all P < 0.001). Kep was the better parameter for differentiating benign tumors from borderline and malignant tumors, with a sensitivity of 89.3% and 95.5%, a specificity of 86.7% and 100%, an accuracy of 88.4% and 96.3%, and an area under the curve (AUC) of 0.94 and 0.992, respectively, whereas Ktrans was better for differentiating borderline from malignant tumors with a sensitivity of 60.7%, a specificity of 78.8%, an accuracy of 73.4%, and an AUC of 0.743. In addition, a combination with kep could further improve the sensitivity to 78.9%. The median Ktrans and kep values were significantly higher in type II than in type I EOCs. CONCLUSION: DCE-MRI with volume quantification is a technically feasible method, and can be used for the differentiation of ovarian tumors and for discriminating between type I and type II EOCs.
PURPOSE: This study aimed to investigate the diagnostic performance of quantitative DCE-MRI for characterizing ovarian tumors. METHODS: We prospectively assessed the differences of quantitative DCE-MRI parameters (Ktrans, kep, and ve) among 15 benign, 28 borderline, and 66 malignant ovarian tumors; and between type I (n = 28) and type II (n = 29) of epithelial ovarian carcinomas (EOCs). DCE-MRI data were analyzed using whole solid tumor volume region of interest (ROI) method, and quantitative parameters were calculated based on a modified Tofts model. The non-parametric Kruskal-Wallis test, Mann-Whitney U test, Pearson's chi-square test, intraclass correlation coefficient (ICC), variance test, and receiver operating characteristic curves (ROC) were used for statistical analysis. RESULTS: The largest Ktrans and kep values were observed in ovarian malignant tumors, followed by borderline and benign tumors (all P < 0.001). Kep was the better parameter for differentiating benign tumors from borderline and malignant tumors, with a sensitivity of 89.3% and 95.5%, a specificity of 86.7% and 100%, an accuracy of 88.4% and 96.3%, and an area under the curve (AUC) of 0.94 and 0.992, respectively, whereas Ktrans was better for differentiating borderline from malignant tumors with a sensitivity of 60.7%, a specificity of 78.8%, an accuracy of 73.4%, and an AUC of 0.743. In addition, a combination with kep could further improve the sensitivity to 78.9%. The median Ktrans and kep values were significantly higher in type II than in type I EOCs. CONCLUSION:DCE-MRI with volume quantification is a technically feasible method, and can be used for the differentiation of ovarian tumors and for discriminating between type I and type II EOCs.
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Authors: Joshua D Kaggie; Surrin Deen; Dimitri A Kessler; Mary A McLean; Guido Buonincontri; Rolf F Schulte; Helen Addley; Evis Sala; James Brenton; Martin J Graves; Ferdia A Gallagher Journal: IEEE Trans Radiat Plasma Med Sci Date: 2019-03-15