Institute of Clinical Medicine, School of Medicine, Clinical Radiology, University of Eastern Finland, Kuopio, Finland.
Department of Clinical Radiology, Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland.
Br J Radiol. 2022 Feb 1;95(1130):20210702. doi: 10.1259/bjr.20210702. Epub 2021 Dec 8.
The aim of this exploratory study was to evaluate whether three-dimensional texture analysis (3D-TA) features of non-contrast-enhanced weighted MRI associate with traditional prognostic factors and disease-free survival (DFS) of breast cancer.
3D- weighted images from 78 patients with 81 malignant histopathologically verified breast lesions were retrospectively analysed using standard-size volumes of interest. Grey-level co-occurrence matrix (GLCM)-based features were selected for statistical analysis. In statistics the Mann-Whitney and the Kruskal-Wallis tests, the Cox proportional hazards model and the Kaplan-Meier method were used.
Tumours with higher histological grade were significantly associated with higher contrast (1 voxel: = 0.033, 2 voxels: = 0.036). All the entropy parameters showed significant correlation with tumour grade ( = 0.015-0.050) but there were no statistically significant associations between other TA parameters and tumour grade. The Nottingham Prognostic Index (NPI) was correlated with contrast and sum entropy parameters. A higher sum variance TA parameter was a significant predictor of shorter DFS.
Texture parameters, assessed by 3D-TA from non-enhanced weighted images, indicate tumour heterogeneity but have limited independent prognostic value. However, they are associated with tumour grade, NPI, and DFS. These parameters could be used as an adjunct to contrast-enhanced TA parameters.
3D-TA of non-contrast enhanced weighted breast MRI associates with tumour grade, NPI, and DFS. The use of non-contrast 3D-TA parameters in adjunct with contrast-enhanced 3D-TA parameters warrants further research.
本探索性研究旨在评估非对比增强加权磁共振成像的三维纹理分析（3D-TA）特征是否与乳腺癌的传统预后因素和无病生存（DFS）相关。
回顾性分析了 78 例 81 例恶性组织学证实的乳腺癌患者的 3D 加权图像，使用标准大小的感兴趣区进行分析。选择灰度共生矩阵（GLCM）的基于特征进行统计分析。在统计学中，使用曼-惠特尼和克鲁斯卡尔-沃利斯检验、Cox 比例风险模型和 Kaplan-Meier 方法。
组织学分级较高的肿瘤与较高的对比度（1 体素：= 0.033，2 体素：= 0.036）显著相关。所有熵参数与肿瘤分级均呈显著相关性（= 0.015-0.050），但其他 TA 参数与肿瘤分级之间无统计学显著相关性。诺丁汉预后指数（NPI）与对比度和总和熵参数相关。较高的总和方差 TA 参数是 DFS 较短的显著预测因子。
非增强加权图像的 3D-TA 评估的纹理参数表明肿瘤异质性，但具有有限的独立预后价值。然而，它们与肿瘤分级、NPI 和 DFS 相关。这些参数可作为对比增强 TA 参数的辅助手段。
非对比增强加权乳腺 MRI 的 3D-TA 与肿瘤分级、NPI 和 DFS 相关。非对比 3D-TA 参数的使用与对比增强 3D-TA 参数联合使用值得进一步研究。
