Cargando…

Diagnostic utility of a conventional MRI-based analysis and texture analysis for discriminating between ovarian thecoma-fibroma groups and ovarian granulosa cell tumors

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Nagawa, Keita, Kishigami, Tomoki, Yokoyama, Fumitaka, Murakami, Sho, Yasugi, Toshiharu, Takaki, Yasunobu, Inoue, Kaiji, Tsuchihashi, Saki, Seki, Satoshi, Okada, Yoshitaka, Baba, Yasutaka, Hasegawa, Kosei, Yasuda, Masanori, Kozawa, Eito
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9131674/
https://www.ncbi.nlm.nih.gov/pubmed/35610706
http://dx.doi.org/10.1186/s13048-022-00989-z
_version_ 1784713223423918080
author Nagawa, Keita
Kishigami, Tomoki
Yokoyama, Fumitaka
Murakami, Sho
Yasugi, Toshiharu
Takaki, Yasunobu
Inoue, Kaiji
Tsuchihashi, Saki
Seki, Satoshi
Okada, Yoshitaka
Baba, Yasutaka
Hasegawa, Kosei
Yasuda, Masanori
Kozawa, Eito
author_facet Nagawa, Keita
Kishigami, Tomoki
Yokoyama, Fumitaka
Murakami, Sho
Yasugi, Toshiharu
Takaki, Yasunobu
Inoue, Kaiji
Tsuchihashi, Saki
Seki, Satoshi
Okada, Yoshitaka
Baba, Yasutaka
Hasegawa, Kosei
Yasuda, Masanori
Kozawa, Eito
author_sort Nagawa, Keita
collection PubMed
description 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13048-022-00989-z.
format Online
Article
Text
id pubmed-9131674
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-91316742022-05-26 Diagnostic utility of a conventional MRI-based analysis and texture analysis for discriminating between ovarian thecoma-fibroma groups and ovarian granulosa cell tumors Nagawa, Keita Kishigami, Tomoki Yokoyama, Fumitaka Murakami, Sho Yasugi, Toshiharu Takaki, Yasunobu Inoue, Kaiji Tsuchihashi, Saki Seki, Satoshi Okada, Yoshitaka Baba, Yasutaka Hasegawa, Kosei Yasuda, Masanori Kozawa, Eito J Ovarian Res Research 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13048-022-00989-z. BioMed Central 2022-05-25 /pmc/articles/PMC9131674/ /pubmed/35610706 http://dx.doi.org/10.1186/s13048-022-00989-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Nagawa, Keita
Kishigami, Tomoki
Yokoyama, Fumitaka
Murakami, Sho
Yasugi, Toshiharu
Takaki, Yasunobu
Inoue, Kaiji
Tsuchihashi, Saki
Seki, Satoshi
Okada, Yoshitaka
Baba, Yasutaka
Hasegawa, Kosei
Yasuda, Masanori
Kozawa, Eito
Diagnostic utility of a conventional MRI-based analysis and texture analysis for discriminating between ovarian thecoma-fibroma groups and ovarian granulosa cell tumors
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
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9131674/
https://www.ncbi.nlm.nih.gov/pubmed/35610706
http://dx.doi.org/10.1186/s13048-022-00989-z
work_keys_str_mv AT nagawakeita diagnosticutilityofaconventionalmribasedanalysisandtextureanalysisfordiscriminatingbetweenovarianthecomafibromagroupsandovariangranulosacelltumors
AT kishigamitomoki diagnosticutilityofaconventionalmribasedanalysisandtextureanalysisfordiscriminatingbetweenovarianthecomafibromagroupsandovariangranulosacelltumors
AT yokoyamafumitaka diagnosticutilityofaconventionalmribasedanalysisandtextureanalysisfordiscriminatingbetweenovarianthecomafibromagroupsandovariangranulosacelltumors
AT murakamisho diagnosticutilityofaconventionalmribasedanalysisandtextureanalysisfordiscriminatingbetweenovarianthecomafibromagroupsandovariangranulosacelltumors
AT yasugitoshiharu diagnosticutilityofaconventionalmribasedanalysisandtextureanalysisfordiscriminatingbetweenovarianthecomafibromagroupsandovariangranulosacelltumors
AT takakiyasunobu diagnosticutilityofaconventionalmribasedanalysisandtextureanalysisfordiscriminatingbetweenovarianthecomafibromagroupsandovariangranulosacelltumors
AT inouekaiji diagnosticutilityofaconventionalmribasedanalysisandtextureanalysisfordiscriminatingbetweenovarianthecomafibromagroupsandovariangranulosacelltumors
AT tsuchihashisaki diagnosticutilityofaconventionalmribasedanalysisandtextureanalysisfordiscriminatingbetweenovarianthecomafibromagroupsandovariangranulosacelltumors
AT sekisatoshi diagnosticutilityofaconventionalmribasedanalysisandtextureanalysisfordiscriminatingbetweenovarianthecomafibromagroupsandovariangranulosacelltumors
AT okadayoshitaka diagnosticutilityofaconventionalmribasedanalysisandtextureanalysisfordiscriminatingbetweenovarianthecomafibromagroupsandovariangranulosacelltumors
AT babayasutaka diagnosticutilityofaconventionalmribasedanalysisandtextureanalysisfordiscriminatingbetweenovarianthecomafibromagroupsandovariangranulosacelltumors
AT hasegawakosei diagnosticutilityofaconventionalmribasedanalysisandtextureanalysisfordiscriminatingbetweenovarianthecomafibromagroupsandovariangranulosacelltumors
AT yasudamasanori diagnosticutilityofaconventionalmribasedanalysisandtextureanalysisfordiscriminatingbetweenovarianthecomafibromagroupsandovariangranulosacelltumors
AT kozawaeito diagnosticutilityofaconventionalmribasedanalysisandtextureanalysisfordiscriminatingbetweenovarianthecomafibromagroupsandovariangranulosacelltumors