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

Year 2025, Volume: 35 Issue: 2, 255 - 263, 30.04.2025

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

https://doi.org/10.54005/geneltip.1536404

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

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