Grading of clear cell renal cell carcinoma using diffusion MRI with a multimodal apparent diffusion model
Year: 2025
Type: article
Study design: Observational Study
Abstract: Objective To assess the feasibility of utilizing parameters derived from a multimodal apparent diffusion (MAD) model to distinguish between low- and high-grade clear cell renal cell carcinoma (ccRCC). Method Diffusion-weighted imaging (DWI) scans with 12 b-values (0 - 3000 s/mm²) were conducted on 54 patients diagnosed with ccRCC (30 low-grade and 24 high-grade). The MAD model parameters, including diffusion coefficients (Dr, Dh, Dui, Df) representing restricted diffusion, hindered diffusion, unimpeded diffusion, and flow, respectively, were computed. Proportions corresponding to these diffusion types (fr, fh, fui, ff) and the heterogeneous nature of hindered diffusion (αh) were also obtained. Parameters were compared between low- and high-grade groups. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of these parameters, compared with the apparent diffusion coefficient (ADC) from a mono-exponential model. Result Significant differences between low- and high-grade ccRCC were observed in Dh (low-grade: 1.360 ± 0.11 μm2/ms; high-grade group, 1.254 ± 0.13 μm2/ms; P = 0.0327), fr (low-grade: 0.06 ± 0.005; high-grade: 0.08 ± 0.009; P = 0.0233), and αh (low-grade: 0.872 ± 0.22; high-grade: 0.896 ± 0.39; P = 0.0294). Additionally, the ADC values (low-grade: 0.924 ± 0.08 μm2/ms; high-grade group, 0.854 ± 0.04 μm2/ms; P = 0.0323) showed statistical significance. The combination of Dh, fr, and αh provided the highest diagnostic accuracy of 0.667, with a sensitivity of 0.750, specificity of 0.734, and area under the curve of 0.796, outperforming individual parameters and ADC. Conclusion The MAD diffusion model shows promise as a non-invasive imaging tool for distinguishing between low- and high-grade ccRCC, which may aid in preoperative planning and personalized treatment strategies.
Source: Frontiers in Oncology
Authors: Shuang Wang, Tuo Ji, Dan Yu, Yimeng Dai, Butian Zhang, Lin Liu
Institution: Jilin University
Language: English
Topic: MRI in cancer diagnosis
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W4408678658