A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index
| العنوان: | A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index |
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| المؤلفون: | Ryuta Miyake, Shoichiro Yamanaka, Hiroshi Kobayashi, Naoki Kawahara |
| المصدر: | Cancers Volume 13 Issue 15 Cancers, Vol 13, Iss 3829, p 3829 (2021) |
| بيانات النشر: | MDPI, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Laparoscopic surgery, Cancer Research, medicine.medical_specialty, Multivariate analysis, medicine.medical_treatment, Endometriosis, MR relaxometry, Article, 03 medical and health sciences, 0302 clinical medicine, CEA, endometriosis associated ovarian cancer, Laparotomy, medicine, ovarian endometrioma, R2 predictive index, magnetic resonance imaging, RC254-282, 030219 obstetrics & reproductive medicine, medicine.diagnostic_test, business.industry, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Retrospective cohort study, Magnetic resonance imaging, medicine.disease, Oncology, 030220 oncology & carcinogenesis, Cohort, Radiology, business, Ovarian cancer |
| الوصف: | Simple Summary Ovarian Endometrioma (OE) is a precancerous condition for endometriosis-associated ovarian cancer (EAOC). For many clinicians observing OE outpatients, setting the appropriate time for surgery can be a challenge because there is no suggestive milestone. Out of the fear of malignant transformation, many patients have surgery conducted according to respective faculty standards. This study aims to investigate a novel, noninvasive method not requiring an MRI device. This study partly helps to lift the above restrictions, and has the potential to suggest intervention-appropriate timing to the physician. Abstract Background: Magnetic resonance (MR) relaxometry provides a noninvasive tool to discriminate between ovarian endometrioma (OE) and endometriosis-associated ovarian cancer (EAOC), with a sensitivity and specificity of 86% and 94%, respectively. MRI models that can measure R2 values are limited, and the R2 values differ between MRI models. This study aims to extract the factors contributing to the R2 value, and to make a formula for estimating the R2 values, and to assess whether the R2 predictive index calculated by the formula could discriminate EAOC from OE. Methods: This retrospective study was conducted at our institution from November 2012 to February 2019. A total of 247 patients were included in this study. Patients with benign ovarian tumors mainly received laparoscopic surgery, and the patients suspected of having malignant tumors underwent laparotomy. Information from a chart review of the patients’ medical records was collected. Results: In the investigative cohort, among potential factors correlated with the R2 value, multiple regression analyses revealed that tumor diameter and CEA could predict the R2 value. In the validation cohort, multivariate analysis confirmed that age, CRP, and the R2 predictive index were the independent factors. Conclusions: The R2 predictive index is useful and valuable to the detection of the malignant transformation of endometrioma. |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 2072-6694 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5cf52c5f89297fc04aae429a8179b315Test http://europepmc.org/articles/PMC8345171Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....5cf52c5f89297fc04aae429a8179b315 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 20726694 |
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