Rie Mimura1, Fumi Kato2, Khin Khin Tha1, Kohsuke Kudo3, Yosuke Konno4, Noriko Oyama-Manabe3, Tatsuya Kato4, Hidemichi Watari4, Noriaki Sakuragi4, Hiroki Shirato1. 1. Department of Radiation Medicine, Hokkaido University Graduate School of Medicine, N15, W7, Kita-ku, Sapporo, 060-8638, Japan. 2. Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, N14, W5, Kita-ku, Sapporo, 060-8648, Japan. fumikato@med.hokudai.ac.jp. 3. Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, N14, W5, Kita-ku, Sapporo, 060-8648, Japan. 4. Department of Obstetrics and Gynecology, Hokkaido University Graduate School of Medicine, N14, W5, Sapporo, 060-8648, Japan.
Abstract
PURPOSE: This study aimed to evaluate whether histogram analysis of the apparent diffusion coefficient (ADC) of a solid tumor component could distinguish borderline ovarian tumors from ovarian carcinoma. MATERIALS AND METHODS: Sixteen pathologically proven borderline tumors and 21 carcinomas were retrospectively examined. Magnetic resonance (1.5-T) image data sets were coregistered, and the solid components of each tumor were semiautomatically segmented. ADC histograms of the solid components were extracted; modes, minimums, means, and 10th, 25th, 50th, 75th, and 90th percentiles of the histograms were compared between the two tumor types, and receiver-operating characteristic (ROC) analysis was performed. RESULTS: The mode, minimum, mean, 10th, 25th, 50th, and 75th percentile ADC values of solid components of borderline tumors were significantly larger than those of carcinomas. Among these, the 10th percentile values had the lowest p value (p = 0.0003). At ROC analysis, the area under the curve (AUC) in the 10th percentile was the greatest (0.854), and the best cutoff value in the 10th percentile provided the highest specificity (93.8 %). CONCLUSIONS: ADC histograms of solid tumor components facilitated the distinction between borderline ovarian tumors and carcinoma. The 10th percentile ADC values had the best diagnostic performance.
PURPOSE: This study aimed to evaluate whether histogram analysis of the apparent diffusion coefficient (ADC) of a solid tumor component could distinguish borderline ovarian tumors from ovarian carcinoma. MATERIALS AND METHODS: Sixteen pathologically proven borderline tumors and 21 carcinomas were retrospectively examined. Magnetic resonance (1.5-T) image data sets were coregistered, and the solid components of each tumor were semiautomatically segmented. ADC histograms of the solid components were extracted; modes, minimums, means, and 10th, 25th, 50th, 75th, and 90th percentiles of the histograms were compared between the two tumor types, and receiver-operating characteristic (ROC) analysis was performed. RESULTS: The mode, minimum, mean, 10th, 25th, 50th, and 75th percentile ADC values of solid components of borderline tumors were significantly larger than those of carcinomas. Among these, the 10th percentile values had the lowest p value (p = 0.0003). At ROC analysis, the area under the curve (AUC) in the 10th percentile was the greatest (0.854), and the best cutoff value in the 10th percentile provided the highest specificity (93.8 %). CONCLUSIONS: ADC histograms of solid tumor components facilitated the distinction between borderline ovarian tumors and carcinoma. The 10th percentile ADC values had the best diagnostic performance.
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