The Diagnostic Performance of Magnetic Resonance Texture Analysis in Histological Subtyping and Grading of the Renal Cell Carcinoma

Authors : Nusret Seher, Mustafa Koplay, Abidin Kılınçer, Lütfi Saltuk Demir, Mehmet Kaynar, Kadir Böcü, Serdar Göktaş

Pages : 255-263

Doi:10.54005/geneltip.1536404

View : 25 | Download : 32

Publication Date : 2025-04-30

Article Type : Research Paper

Abstract :Backgrounds-Aims: To evaluate the efficiency of MRTA in distinguishing RCC types and in the distinction of tumor grade. Methods: 62 patients were analyzed retrospectively and grouped as 40 clear cell-RCC, 11 papillary-RCC and 11 chromophobe-RCC. In the MRI (1.5-T) protocol, the axial T2 weighted (W), axial T1W in-phase (IP) and apparent diffusion coefficient (ADC) images were used. Additionally, postcontrast images obtained in the corticomedullary (CM) phase and nephrogram (NG) phase of the axial fat-suppressed T1W (VIBE) sequence were used. In MRTA were used parameters as mean, median, entropy, skewness, kurtosis, variance, uniformity. Statistical analysis was performed to compare CC-RCC &NC-RCC, and high-grade& low-grade tumors and between the subtypes. Results: Tissue parameters that perform best in separating CC-RCC from NC-RCC (AUC in brackets): Values obtained included entropy (0.67) in CM phase, mean (0.75) and median (0.76) in ADC, entropy (0,66) and variance (0.66) in NG phase were obtained. The p values in IP and T2W images in the distinction between the high and low degrees were significant. Conclusion: Several MR texture parameters performed well (AUC> 0.75) in separating CC-RCC from NC-RCC. MRTA can be a useful noninvasive tool for this purpose. The first order parameters that we used in TA can be used to evaluate the prognosis in RCC patients.
Keywords : Renal cell carcinoma, texture analysis, Fuhrman, grade, MRI