AUTHOR=Li Nai-yu , Shi Bin , Chen Yu-lan , Wang Pei-pei , Wang Chuan-bin , Chen Yao , Ge Ya-qiong , Dong Jiang-ning , Wei Chao 

TITLE=The Value of MRI Findings Combined With Texture Analysis in the Differential Diagnosis of Primary Ovarian Granulosa Cell Tumors and Ovarian Thecoma–Fibrothecoma

JOURNAL=Frontiers in Oncology

VOLUME=Volume 11 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2021.758036

DOI=10.3389/fonc.2021.758036

ISSN=2234-943X

ABSTRACT=Abstract
Objective: To explore the value of magnetic resonance imaging (MRI) and texture analysis (TA) in the differential diagnosis between ovarian granulosa cell tumours (OGCTs) and thecoma-fibrothecoma (OTCA-FTCA). Methods: The preoperative MRI data of 32 patients with OTCA-FTCA and 14 patients with OGCTs confirmed by pathological examination from June 2013 to August 2020 were retrospectively analysed. The texture data of three-dimensional MRI scans based on T2-weighted imaging and clinical and conventional MRI features were analysed and compared between tumour types. The Mann-Whitney U test, χ2 test/Fisher exact test and multivariate logistic regression analysis were adopted to identify differences between the OTCA-FTCA and OGCT groups. A regression model was established by using binary logistic regression analysis, and receiver operating characteristic (ROC) curve analysis was carried out to evaluate diagnostic efficiency. Results: The texture parameters based on T2WI (log-sigma-2-0-mm-3D_glszm_SmallAreaEmphasis, log-sigma-2-0-mm-3D_glszm_SmallAreaHighGrayLevelEmphasis, log-sigma-3-0-mm-3D_glcm_InverseVariance, wavelet-LLH_glcm_MCC,wavelet-HLH_glszm_SmallAreaHighGrayLevelEmphasis and wavelet-HLL_glszm_LowGrayLevelZoneEmphasis) as well as imaging-based features (mean apparent diffusion coefficient (ADC) (103 s/mm2), enhancement degree (solid), cystic form and intratumoral haemorrhage) showed significant differences between the OTCA-FTCA and OGCT groups (all P<0.05). Multivariate analysis of the imaging-based features combined with TA revealed that intratumoral haemorrhage (OR = 0.037), log-sigma-20mm-3D_glszm_SmallAreaEmphasis (OR = 4.40) and log-sigma-2-0mm-3D_glszm_SmallAreaHighGrayLevelEmphasis (OR = 1.034) were independent features for discriminating between OGCTs and OTCA-FTCA (P< 0.05). An imaging-based diagnosis model, TA-based model and combination model were established. The areas under the curves (AUCs) of the three models in predicting OGCTs and OTCA-FTCA were 0.935, 0.944 and 0.969, respectively, the sensitivities were 93.75%, 93.75% and 96.87%, respectively, and the specificities were 85.71%, 92.86% and 92.86%, respectively. The DeLong test indicated that the combination model had the highest predictive efficiency (P<0.05), with no significant difference among the three models in differentiating between OGCTs and OTCA-FTCA (P>0.05). Conclusions: MRI is the preferred imaging examination method for OGCTs and OTCA-FTCA. Texture features can reflect the microheterogeneity of OGCTs and OTCA-FTCA. MRI signs and texture features can help differentiate between OGCTs and OTCA-FTCA and provide a more comprehensive and accurate basis for clinical treatment.