Li Nai-Yu, Shi Bin, Chen Yu-Lan, Wang Pei-Pei, Wang Chuan-Bin, Chen Yao, Ge Ya-Qiong, Dong Jiang-Ning, Wei Chao
The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
Department of the Healthcare, GE of China, Shanghai, China.
Front Oncol. 2021 Oct 27;11:758036. doi: 10.3389/fonc.2021.758036. eCollection 2021.
This study aims to explore the value of magnetic resonance imaging (MRI) and texture analysis (TA) in the differential diagnosis of ovarian granulosa cell tumors (OGCTs) and thecoma-fibrothecoma (OTCA-FTCA).
The preoperative MRI data of 32 patients with OTCA-FTCA and 14 patients with OGCTs, confirmed by pathological examination between June 2013 and August 2020, were retrospectively analyzed. The texture data of three-dimensional MRI scans based on T2-weighted imaging and clinical and conventional MRI features were analyzed and compared between tumor types. The Mann-Whitney -test, test/Fisher exact test, and multivariate logistic regression analysis were used to identify differences between the OTCA-FTCA and OGCTs groups. A regression model was established by using binary logistic regression analysis, and receiver operating characteristic curve analysis was carried out to evaluate diagnostic efficiency.
A multivariate analysis of the imaging-based features combined with TA revealed that intratumoral hemorrhage (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 ( < 0.05). An imaging-based diagnosis model, TA-based model, and combination model were established. The areas under the curve 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 ( < 0.05), with no significant difference among the three models in differentiating between OGCTs and OTCA-FTCA ( > 0.05).
Compared with OTCA-FTCA, intratumoral hemorrhage may be characteristic MR imaging features with OGCTs. 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.
本研究旨在探讨磁共振成像(MRI)及纹理分析(TA)在卵巢颗粒细胞瘤(OGCT)与纤维卵泡膜细胞瘤(OTCA-FTCA)鉴别诊断中的价值。
回顾性分析2013年6月至2020年8月间经病理检查确诊的32例OTCA-FTCA患者及14例OGCT患者的术前MRI数据。分析并比较基于T2加权成像的三维MRI扫描纹理数据以及不同肿瘤类型的临床和传统MRI特征。采用Mann-Whitney检验、检验/Fisher精确检验及多因素逻辑回归分析来确定OTCA-FTCA组与OGCT组之间的差异。通过二元逻辑回归分析建立回归模型,并进行受试者工作特征曲线分析以评估诊断效能。
基于成像特征联合TA的多因素分析显示,瘤内出血(OR = 0.037)、log-sigma-20mm-3D_glszm_SmallAreaEmphasis(OR = 4.40)及log-sigma-2-0mm-3D_glszm_SmallAreaHighGrayLevelEmphasis(OR = 1.034)是鉴别OGCT与OTCA-FTCA的独立特征(<0.05)。建立了基于成像的诊断模型、基于TA的模型及联合模型。三种模型预测OGCT与OTCA-FTCA的曲线下面积分别为0.935、0.944及0.969;敏感度分别为93.75%、93.75%及96.87%;特异度分别为85.71%、92.86%及92.86%。DeLong检验表明联合模型具有最高的预测效能(<0.05),三种模型在鉴别OGCT与OTCA-FTCA方面无显著差异(>0.05)。
与OTCA-FTCA相比,瘤内出血可能是OGCT的特征性MRI表现。纹理特征可反映OGCT与OTCA-FTCA的微观异质性。MRI征象及纹理特征有助于OGCT与OTCA-FTCA的鉴别诊断,并为临床治疗提供更全面准确的依据。