ArticleBiomedicines2022
The Endometriotic Neoplasm Algorithm for Risk Assessment (e-NARA) Index Sheds Light on the Discrimination of Endometriosis-Associated Ovarian Cancer from Ovarian Endometrioma.
Article in Biomedicines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Prediction models for endometriosis-associated ovarian malignancy: A systematic review and meta-analysis.European journal of obstetrics & gynecology and reproductive biology: X · 2026Review
- Comprehensive serum glycopeptide spectra analysis to identify early-stage epithelial ovarian cancer.Scientific reports · 2024Article
- Investigating the efficacy of tissue factor pathway inhibitor‑2 as a promising prognostic marker for ovarian cancer.Oncology letters · 2024Article
- MR Relaxometry for Discriminating Malignant Ovarian Cystic Tumors: A Prospective Multicenter Cohort Study.Diagnostics (Basel, Switzerland) · 2024Article
- Derivation and validation of a nomogram based on clinical characteristics to diagnose endometriosis associated ovarian cancer preoperatively.Journal of cancer research and clinical oncology · 2024Article
- New insights about endometriosis-associated ovarian cancer: pathogenesis, risk factors, prediction and diagnosis and treatment.Frontiers in oncology · 2024Review
- State-of-the-Art Cancer Biology, Biodiagnostics and Therapeutics in Japan.Biomedicines · 2023Article
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Abstract
backgroundMagnetic 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.
methodsThis 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 (
resultsA 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.
conclusionsThe e-NARA index is a reliable tool to assess the probability of malignant transformation of endometrioma.
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