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• Clinical Article •
Application of texture analysis in dynamic contrast-enhanced MRI for differentiation of renal cell carcinoma subtypes
ZHOU Zhi  CHEN Jie  PAN Liang  ZHOU Feifei  XING Wei 

Cite this article as: Zhou Z, Chen J, Pan L, et al. Application of texture analysis in dynamic contrast-enhanced MRI for differentiation of renal cell carcinoma subtypes. Chin J Magn Reson Imaging, 2019, 10(7): 525-529. DOI:10.12015/issn.1674-8034.2019.07.009.


[Abstract] Objective: To evaluate the diagnostic performance of three-dimensional (3D) texture analysis (TA) in dynamic contrast-enhanced (DCE) MRI for the classification of clear cell (ccRCC), papillary (pRCC) and chromophobe renal cell carcinoma (ChRCC).Materials and Methods: A retrospective review was performed on patients with ccRCCs (n=74 ), pRCCs (n=22) or ChRCCs (n=17) confirmed by pathology. Corticomedullary phase, nephrographic phase and delayed phase CE-MR images obtained from all the patients were used for texture analysis. 314 3D texture features were extracted from each of the three image series, and 30 important features were selected separately for each pair of ccRCCs, pRCCs and ChRCCs. Texture analysis was performed using raw data analysis, principle component analysis and linear discriminant analysis, and nonlinear discriminant analysis. Classification accuracy, sensitivity, specificity and area under the receiver operator characteristics curve (AUC) were calculated.Results: For ccRCC vs pRCC, the classification accuracy, sensitivity and specificity of 3D TA in DCE-MRI were up to 88.54%, 91.89% and 77.27% (AUC=0.846), for ccRCC vs ChRCC, the classification accuracy, sensitivity and specificity were up to 95.60%, 97.30% and 88.24% (AUC=0.928), for pRCC vs ChRCC, the classification accuracy, sensitivity and specificity were up to 79.49%, 72.73% and 88.24% (AUC=0.805). For all the pairs of ccRCCs, pRCCs and ChRCCs, classification performed the best in nonlinear discriminant analysis (AUC 0.707—0.928) within each of the three image series.Conclusions: The three-dimensional texture analysis in DCE-MRI can be a reliable quantitative approach for differentiating ccRCC from pRCC or ChRCC and pRCC from ChRCC.
[Keywords] kidney neoplasms；magnetic resonance imaging；texture analysis

ZHOU Zhi Department of Radiology, No.904 Hospital of Joint Logistics Unit, Changzhou 213001, China

CHEN Jie Department of Radiology, the Third Affiliated Hospital of Soochow University, Changzhou 213001, China

PAN Liang Department of Radiology, the Third Affiliated Hospital of Soochow University, Changzhou 213001, China

ZHOU Feifei Department of Radiology, the Third Affiliated Hospital of Soochow University, Changzhou 213001, China

XING Wei* Department of Radiology, the Third Affiliated Hospital of Soochow University, Changzhou 213001, China

*Correspondence to: Xing W, Email: suzhxingwei@126.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  This article is supported by the National Natural Science Found No. 81771798 and Changzhou Sci & Tech Program No. CJ20179021
Received  2019-03-21
Accepted  2019-05-23
DOI: 10.12015/issn.1674-8034.2019.07.009
Cite this article as: Zhou Z, Chen J, Pan L, et al. Application of texture analysis in dynamic contrast-enhanced MRI for differentiation of renal cell carcinoma subtypes. Chin J Magn Reson Imaging, 2019, 10(7): 525-529. DOI:10.12015/issn.1674-8034.2019.07.009.

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