Contrast-Enhanced CT Texture Analysis for Distinguishing Fat-Poor Renal Angiomyolipoma From Chromophobe Renal Cell Carcinoma
Contrast-Enhanced CT Texture Analysis for Distinguishing Fat-Poor Renal Angiomyolipoma From Chromophobe Renal Cell Carcinoma
复制标题
对比增强 CT 纹理分析用于区分贫脂肾血管平滑肌脂肪瘤和嫌色肾细胞癌
DOI：
10.1177/1536012119883161
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发表时间：
2019-10-17
影响因子：
2.8
通讯作者：
Wang, Zhenguang
中科院分区：
文献类型：
--
作者：
Yang, Guangjie;Gong, Aidi;Wang, Zhenguang
Objective: To evaluate the value of 2-dimensional (2D) and 3-dimensional (3D) computed tomography texture analysis (CTTA) models in distinguishing fat-poor angiomyolipoma (fpAML) from chromophobe renal cell carcinoma (chRCC). Methods: We retrospectively enrolled 32 fpAMLs and 24 chRCCs. Texture features were extracted from 2D and 3D regions of interest in triphasic CT images. The 2D and 3D CTTA models were constructed with the least absolute shrinkage and selection operator algorithm and texture scores were calculated. The diagnostic performance of the 2D and 3D CTTA models was evaluated with respect to calibration, discrimination, and clinical usefulness. Results: Of the 177 and 183 texture features extracted from 2D and 3D regions of interest, respectively, 5 2D features and 8 3D features were selected to build 2D and 3D CTTA models. The 2D CTTA model (area under the curve [AUC], 0.811; 95% confidence interval [CI], 0.695-0.927) and the 3D CTTA model (AUC, 0.915; 95% CI, 0.838-0.993) showed good discrimination and calibration (P > .05). There was no significant difference in AUC between the 2 models (P = .093). Decision curve analysis showed the 3D model outperformed the 2D model in terms of clinical usefulness. Conclusions: The CTTA models based on contrast-enhanced CT images had a high value in differentiating fpAML from chRCC.
