The prognostic and predictive value of vascular response parameters measured by dynamic contrast-enhanced-CT, -MRI and -US in patients with metastatic renal cell carcinoma receiving sunitinib

2018 ◽  
Vol 28 (6) ◽  
pp. 2281-2290 ◽  
Author(s):  
John M. Hudson ◽  
Colleen Bailey ◽  
Mostafa Atri ◽  
Greg Stanisz ◽  
Laurent Milot ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Predictive Value ◽  
Renal Cell ◽  
Vascular Response ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Dynamic Contrast Enhanced Ct

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 ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Texture Analysis ◽  
Renal Cell ◽  
Texture Features ◽  
Regions Of Interest ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
2D And 3D

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.

scholarly journals Contrast-Enhanced CT Density Predicts Response to Sunitinib Therapy in Metastatic Renal Cell Carcinoma Patients

2017 ◽  
Vol 10 (4) ◽  
pp. 679-685 ◽  
Author(s):  
Simon Matoori ◽  
Yeeliang Thian ◽  
Dow-Mu Koh ◽  
Aslam Sohaib ◽  
James Larkin ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Ct Density

Small (< 4 cm) Renal Masses: Differentiation of Angiomyolipoma Without Visible Fat From Renal Cell Carcinoma Using Unenhanced and Contrast-Enhanced CT

2015 ◽  
Vol 205 (6) ◽  
pp. 1194-1202 ◽  
Author(s):  
Naoki Takahashi ◽  
Shuai Leng ◽  
Kazuhiro Kitajima ◽  
Daniel Gomez-Cardona ◽  
Prabin Thapa ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Renal Masses ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct

Evaluation of Response to Multikinase Inhibitor in Metastatic Renal Cell Carcinoma by FDG PET/Contrast-Enhanced CT

2010 ◽  
Vol 35 (12) ◽  
pp. 918-923 ◽  
Author(s):  
Ryogo Minamimoto ◽  
Noboru Nakaigawa ◽  
Ukihide Tateishi ◽  
Akiko Suzuki ◽  
Kazuya Shizukuishi ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Fdg Pet ◽  
Renal Cell ◽  
Multikinase Inhibitor ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct
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