scholarly journals Contrast-Enhanced CT Texture Analysis for Distinguishing Fat-Poor Renal Angiomyolipoma From Chromophobe Renal Cell Carcinoma

2019 ◽  
Vol 18 ◽  
pp. 153601211988316 ◽  
Author(s):  
Guangjie Yang ◽  
Aidi Gong ◽  
Pei Nie ◽  
Lei Yan ◽  
Wenjie Miao ◽  
...  

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.

2017 ◽  
Vol 10 (4) ◽  
pp. 679-685 ◽  
Author(s):  
Simon Matoori ◽  
Yeeliang Thian ◽  
Dow-Mu Koh ◽  
Aslam Sohaib ◽  
James Larkin ◽  
...  

2015 ◽  
Vol 205 (6) ◽  
pp. 1194-1202 ◽  
Author(s):  
Naoki Takahashi ◽  
Shuai Leng ◽  
Kazuhiro Kitajima ◽  
Daniel Gomez-Cardona ◽  
Prabin Thapa ◽  
...  

2010 ◽  
Vol 35 (12) ◽  
pp. 918-923 ◽  
Author(s):  
Ryogo Minamimoto ◽  
Noboru Nakaigawa ◽  
Ukihide Tateishi ◽  
Akiko Suzuki ◽  
Kazuya Shizukuishi ◽  
...  

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