Kawahara Naoki, Kawaguchi Ryuji, Maehana Tomoka, Yamanaka Shoichiro, Yamada Yuki, Kobayashi Hiroshi, Kimura Fuminori
Department of Obstetrics and Gynecology, Nara Medical University, Kashihara 634-8522, Japan.
Biomedicines. 2022 Oct 24;10(11):2683. doi: 10.3390/biomedicines10112683.
Magnetic resonance (MR) relaxometry provides a noninvasive tool to discriminate endometriosis-associated ovarian cancer (EAOC) from ovarian endometrioma (OE) with high accuracy. However, this method has a limitation in discriminating malignancy in clinical use because the R2 value depends on the device manufacturer and repeated imaging is unrealistic. The current study aimed to reassess the diagnostic accuracy of MR relaxometry and investigate a more powerful tool to distinguish EAOC from OE.
This retrospective study was conducted at our institution from December, 2012, to May, 2022. A total of 150 patients were included in this study. Patients with benign ovarian tumors ( = 108) mainly received laparoscopic surgery, and cases with suspected malignancy ( = 42) underwent laparotomy. Information from a chart review of the patients' medical records was collected.
A multiple regression analysis revealed that the age, the tumor diameter, and the R2 value were independent malignant predicting factors. The endometriotic neoplasm algorithm for risk assessment (e-NARA) index provided high accuracy (sensitivity, 85.7%; specificity, 87.0%) to discriminate EAOC from OE.
The e-NARA index is a reliable tool to assess the probability of malignant transformation of endometrioma.
磁共振（MR）弛豫测量法提供了一种非侵入性工具，能够高精度地区分子宫内膜异位症相关卵巢癌（EAOC）与卵巢子宫内膜瘤（OE）。然而，该方法在临床应用中鉴别恶性肿瘤存在局限性，因为R2值取决于设备制造商，且重复成像不切实际。本研究旨在重新评估MR弛豫测量法的诊断准确性，并探寻一种更有效的工具来区分EAOC与OE。
本回顾性研究于2012年12月至2022年5月在我们机构开展。本研究共纳入150例患者。良性卵巢肿瘤患者（n = 108）主要接受腹腔镜手术，疑似恶性肿瘤的病例（n = 42）接受剖腹手术。收集了患者病历图表回顾中的信息。
多元回归分析显示，年龄、肿瘤直径和R2值是独立的恶性预测因素。用于风险评估的子宫内膜异位肿瘤算法（e-NARA）指数在区分EAOC与OE方面具有较高的准确性（敏感性为85.7%；特异性为87.0%）。
e-NARA指数是评估子宫内膜瘤恶变概率的可靠工具。
