Diagnostic utility of a conventional MRI-based analysis and texture analysis for discriminating between ovarian thecoma-fibroma groups and ovarian granulosa cell tumors
Abstract Objective To evaluate the diagnostic utility of conventional magnetic resonance imaging (MRI)-based characteristics and a texture analysis (TA) for discriminating between ovarian thecoma-fibroma groups (OTFGs) and ovarian granulosa cell tumors (OGCTs). Methods This retrospective multicenter...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-05-01
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| Series: | Journal of Ovarian Research |
| Online Access: | https://doi.org/10.1186/s13048-022-00989-z |
| _version_ | 1797969852051226624 |
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| author | Keita Nagawa Tomoki Kishigami Fumitaka Yokoyama Sho Murakami Toshiharu Yasugi Yasunobu Takaki Kaiji Inoue Saki Tsuchihashi Satoshi Seki Yoshitaka Okada Yasutaka Baba Kosei Hasegawa Masanori Yasuda Eito Kozawa |
| author_facet | Keita Nagawa Tomoki Kishigami Fumitaka Yokoyama Sho Murakami Toshiharu Yasugi Yasunobu Takaki Kaiji Inoue Saki Tsuchihashi Satoshi Seki Yoshitaka Okada Yasutaka Baba Kosei Hasegawa Masanori Yasuda Eito Kozawa |
| author_sort | Keita Nagawa |
| collection | DOAJ |
| description | Abstract Objective To evaluate the diagnostic utility of conventional magnetic resonance imaging (MRI)-based characteristics and a texture analysis (TA) for discriminating between ovarian thecoma-fibroma groups (OTFGs) and ovarian granulosa cell tumors (OGCTs). Methods This retrospective multicenter study enrolled 52 patients with 32 OGCTs and 21 OTFGs, which were dissected and pathologically diagnosed between January 2008 and December 2019. MRI-based features (MBFs) and texture features (TFs) were evaluated and compared between OTFGs and OGCTs. A least absolute shrinkage and selection operator (LASSO) regression analysis was performed to select features and construct the discriminating model. ROC analyses were conducted on MBFs, TFs, and their combination to discriminate between the two diseases. Results We selected 3 features with the highest absolute value of the LASSO regression coefficient for each model: the apparent diffusion coefficient (ADC), peripheral cystic area, and contrast enhancement in the venous phase (VCE) for the MRI-based model; the 10th percentile, difference variance, and maximal correlation coefficient for the TA-based model; and ADC, VCE, and the difference variance for the combination model. The areas under the curves of the constructed models were 0.938, 0.817, and 0.941, respectively. The diagnostic performance of the MRI-based and combination models was similar (p = 0.38), but significantly better than that of the TA-based model (p < 0.05). Conclusions The conventional MRI-based analysis has potential as a method to differentiate OTFGs from OGCTs. TA did not appear to be of any additional benefit. Further studies are needed on the use of these methods for a preoperative differential diagnosis of these two diseases. |
| first_indexed | 2024-04-11T03:08:39Z |
| format | Article |
| id | doaj.art-ac2bf473e0b549cb94bdd9b9699cef00 |
| institution | Directory Open Access Journal |
| issn | 1757-2215 |
| language | English |
| last_indexed | 2024-04-11T03:08:39Z |
| publishDate | 2022-05-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Ovarian Research |
| spelling | doaj.art-ac2bf473e0b549cb94bdd9b9699cef002023-01-02T12:30:26ZengBMCJournal of Ovarian Research1757-22152022-05-0115111410.1186/s13048-022-00989-zDiagnostic utility of a conventional MRI-based analysis and texture analysis for discriminating between ovarian thecoma-fibroma groups and ovarian granulosa cell tumorsKeita Nagawa0Tomoki Kishigami1Fumitaka Yokoyama2Sho Murakami3Toshiharu Yasugi4Yasunobu Takaki5Kaiji Inoue6Saki Tsuchihashi7Satoshi Seki8Yoshitaka Okada9Yasutaka Baba10Kosei Hasegawa11Masanori Yasuda12Eito Kozawa13Department of Radiology, Saitama Medical UniversityDepartment of Radiology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome HospitalDepartment of Radiology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome HospitalDepartment of Radiology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome HospitalDepartment of Gynecology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome HospitalDepartment of Radiology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome HospitalDepartment of Radiology, Saitama Medical UniversityDepartment of Radiology, Saitama Medical UniversityDepartment of Radiology, Saitama Medical UniversityDepartment of Diagnostic Imaging, Saitama Medical University International Medical CenterDepartment of Diagnostic Imaging, Saitama Medical University International Medical CenterDepartment of Gynecologic Oncology, Saitama Medical University International Medical CenterDepartment of Diagnostic Pathology, Saitama Medical University International Medical CenterDepartment of Radiology, Saitama Medical UniversityAbstract Objective To evaluate the diagnostic utility of conventional magnetic resonance imaging (MRI)-based characteristics and a texture analysis (TA) for discriminating between ovarian thecoma-fibroma groups (OTFGs) and ovarian granulosa cell tumors (OGCTs). Methods This retrospective multicenter study enrolled 52 patients with 32 OGCTs and 21 OTFGs, which were dissected and pathologically diagnosed between January 2008 and December 2019. MRI-based features (MBFs) and texture features (TFs) were evaluated and compared between OTFGs and OGCTs. A least absolute shrinkage and selection operator (LASSO) regression analysis was performed to select features and construct the discriminating model. ROC analyses were conducted on MBFs, TFs, and their combination to discriminate between the two diseases. Results We selected 3 features with the highest absolute value of the LASSO regression coefficient for each model: the apparent diffusion coefficient (ADC), peripheral cystic area, and contrast enhancement in the venous phase (VCE) for the MRI-based model; the 10th percentile, difference variance, and maximal correlation coefficient for the TA-based model; and ADC, VCE, and the difference variance for the combination model. The areas under the curves of the constructed models were 0.938, 0.817, and 0.941, respectively. The diagnostic performance of the MRI-based and combination models was similar (p = 0.38), but significantly better than that of the TA-based model (p < 0.05). Conclusions The conventional MRI-based analysis has potential as a method to differentiate OTFGs from OGCTs. TA did not appear to be of any additional benefit. Further studies are needed on the use of these methods for a preoperative differential diagnosis of these two diseases.https://doi.org/10.1186/s13048-022-00989-z |
| spellingShingle | Keita Nagawa Tomoki Kishigami Fumitaka Yokoyama Sho Murakami Toshiharu Yasugi Yasunobu Takaki Kaiji Inoue Saki Tsuchihashi Satoshi Seki Yoshitaka Okada Yasutaka Baba Kosei Hasegawa Masanori Yasuda Eito Kozawa Diagnostic utility of a conventional MRI-based analysis and texture analysis for discriminating between ovarian thecoma-fibroma groups and ovarian granulosa cell tumors Journal of Ovarian Research |
| title | Diagnostic utility of a conventional MRI-based analysis and texture analysis for discriminating between ovarian thecoma-fibroma groups and ovarian granulosa cell tumors |
| title_full | Diagnostic utility of a conventional MRI-based analysis and texture analysis for discriminating between ovarian thecoma-fibroma groups and ovarian granulosa cell tumors |
| title_fullStr | Diagnostic utility of a conventional MRI-based analysis and texture analysis for discriminating between ovarian thecoma-fibroma groups and ovarian granulosa cell tumors |
| title_full_unstemmed | Diagnostic utility of a conventional MRI-based analysis and texture analysis for discriminating between ovarian thecoma-fibroma groups and ovarian granulosa cell tumors |
| title_short | Diagnostic utility of a conventional MRI-based analysis and texture analysis for discriminating between ovarian thecoma-fibroma groups and ovarian granulosa cell tumors |
| title_sort | diagnostic utility of a conventional mri based analysis and texture analysis for discriminating between ovarian thecoma fibroma groups and ovarian granulosa cell tumors |
| url | https://doi.org/10.1186/s13048-022-00989-z |
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