Fatmaelzahraa Abdelfattah Denewar1, Mitsuru Takeuchi2, Misugi Urano3, Yuki Kamishima4, Tatsuya Kawai5, Naoki Takahashi6, Moe Takeuchi7, Susumu Kobayashi8, Junichi Honda9, Yuta Shibamoto10. 1. Department of Radiology, Nagoya City University Graduate School of Medical Sciences and Medical School, 1 Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya City, Aichi 467-8601, Japan. Electronic address: zahra.denewar@gmail.com. 2. Department of Radiology, Nagoya City University Graduate School of Medical Sciences and Medical School, 1 Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya City, Aichi 467-8601, Japan. Electronic address: m2rbimn@gmail.com. 3. Department of Radiology, Nagoya City University Graduate School of Medical Sciences and Medical School, 1 Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya City, Aichi 467-8601, Japan. Electronic address: koremicchannodakara@yahoo.co.jp. 4. Nagoya City West Medical Center, 1-1-1 Hirade-cho, Kita-ku, Nagoya City, Aichi 462-8508, Japan. Electronic address: yuki.kamishima@gmail.com. 5. Department of Radiology, Nagoya City University Graduate School of Medical Sciences and Medical School, 1 Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya City, Aichi 467-8601, Japan. Electronic address: tatsuyakawai@gmail.com. 6. Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, United States. Electronic address: takahashi.naoki@mayo.edu. 7. Nagoya City East Medical Center, 1-2-23 Wakamizu, Chikusa-ku, Nagoya City, Aichi 464-0071, Japan. Electronic address: karanadesiko@yahoo.co.jp. 8. Toyokawa City Hospital, 23 Noji, Yawata-cho, Toyokawa City, Aichi 442-0857, Japan. Electronic address: viva7sk@gmail.com. 9. Kariya Toyota General Hospital, 5-15 Sumiyoshi-cho, Kariya City, Aichi 448-8505, Japan. Electronic address: weaponspring@yahoo.co.jp. 10. Department of Radiology, Nagoya City University Graduate School of Medical Sciences and Medical School, 1 Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya City, Aichi 467-8601, Japan. Electronic address: yshiba@med.nagoya-cu.ac.jp.
Abstract
OBJECTIVE: To assess the value of contrast-enhanced MRI, apparent diffusion coefficient (ADC) measurement, and CA-125 measurement for differentiating borderline ovarian tumors (BOTs) from stage I malignant epithelial ovarian tumors (MEOTs). MATERIAL AND METHODS: This retrospective study included 43 patients with BOTs and 43 patients with stage I MEOTs who underwent contrast-enhanced MRI with DWI and CA-125 analysis. Two radiologists evaluated the MRI findings in consensus. Univariate and multivariate analyses were performed to detect the best predictor variables for MEOTs. RESULTS: Mixed cystic/solid and predominantly solid appearances, as well as thickened irregular septa, were more frequent in MEOTs. A papillary architecture and internal branching (PA&IB) pattern was more frequent in BOTs. MEOTs had thicker walls and septa, larger solid components, and higher CA-125 values. The mean ADC value of solid components (ADCmean) and minimum ADC value of whole lesions (ADCmin) were lower in MEOTs. Multivariate analysis revealed that ADCmin and maximum diameter of the solid components were independent indicators of MEOTs with an AUC, sensitivity, and specificity of 0.86, 81%, and 84%, respectively. CONCLUSION: ADCmin and maximum diameter of solid components were useful for differentiating BOTs from MEOTs.
OBJECTIVE: To assess the value of contrast-enhanced MRI, apparent diffusion coefficient (ADC) measurement, and CA-125 measurement for differentiating borderline ovarian tumors (BOTs) from stage I malignant epithelial ovarian tumors (MEOTs). MATERIAL AND METHODS: This retrospective study included 43 patients with BOTs and 43 patients with stage I MEOTs who underwent contrast-enhanced MRI with DWI and CA-125 analysis. Two radiologists evaluated the MRI findings in consensus. Univariate and multivariate analyses were performed to detect the best predictor variables for MEOTs. RESULTS: Mixed cystic/solid and predominantly solid appearances, as well as thickened irregular septa, were more frequent in MEOTs. A papillary architecture and internal branching (PA&IB) pattern was more frequent in BOTs. MEOTs had thicker walls and septa, larger solid components, and higher CA-125 values. The mean ADC value of solid components (ADCmean) and minimum ADC value of whole lesions (ADCmin) were lower in MEOTs. Multivariate analysis revealed that ADCmin and maximum diameter of the solid components were independent indicators of MEOTs with an AUC, sensitivity, and specificity of 0.86, 81%, and 84%, respectively. CONCLUSION: ADCmin and maximum diameter of solid components were useful for differentiating BOTs from MEOTs.