A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index
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 th...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Cancers |
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| Online Access: | https://www.mdpi.com/2072-6694/13/15/3829 |
| _version_ | 1797525723003486208 |
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| author | Naoki Kawahara Ryuta Miyake Shoichiro Yamanaka Hiroshi Kobayashi |
| author_facet | Naoki Kawahara Ryuta Miyake Shoichiro Yamanaka Hiroshi Kobayashi |
| author_sort | Naoki Kawahara |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T09:17:54Z |
| format | Article |
| id | doaj.art-74d5899b61cb475390f957b5d7304dd8 |
| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-10T09:17:54Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-74d5899b61cb475390f957b5d7304dd82023-11-22T05:28:30ZengMDPI AGCancers2072-66942021-07-011315382910.3390/cancers13153829A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive IndexNaoki Kawahara0Ryuta Miyake1Shoichiro Yamanaka2Hiroshi Kobayashi3Department of Obstetrics and Gynecology, Nara Medical University, Nara 634-8521, JapanDepartment of Obstetrics and Gynecology, Nara Medical University, Nara 634-8521, JapanDepartment of Obstetrics and Gynecology, Nara Medical University, Nara 634-8521, JapanDepartment of Obstetrics and Gynecology, Nara Medical University, Nara 634-8521, JapanBackground: 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.https://www.mdpi.com/2072-6694/13/15/3829ovarian endometriomaendometriosis associated ovarian cancermagnetic resonance imagingMR relaxometryCEAR2 predictive index |
| spellingShingle | Naoki Kawahara Ryuta Miyake Shoichiro Yamanaka Hiroshi Kobayashi A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index Cancers ovarian endometrioma endometriosis associated ovarian cancer magnetic resonance imaging MR relaxometry CEA R2 predictive index |
| title | A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index |
| title_full | A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index |
| title_fullStr | A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index |
| title_full_unstemmed | A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index |
| title_short | A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index |
| title_sort | novel predictive tool for discriminating endometriosis associated ovarian cancer from ovarian endometrioma the r2 predictive index |
| topic | ovarian endometrioma endometriosis associated ovarian cancer magnetic resonance imaging MR relaxometry CEA R2 predictive index |
| url | https://www.mdpi.com/2072-6694/13/15/3829 |
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