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Quantitative Analysis With Time-Dependent Diffusion MRI for Assessing WHO/ISUP Tumor Grade in Clear Cell Renal Cell
Chunlei He1,2, Enyu Yuan1, Lei Ye1
1Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
Korean Journal of Radiology
|June 17, 2025
Summary
Time-dependent diffusion-weighted imaging (td-dMRI) can assess clear cell renal cell carcinoma (ccRCC) grades. TD-dMRI parameters, particularly intracellular volume fraction, show promise as noninvasive biomarkers for characterizing ccRCC.
Area of Science:
- Radiology
- Oncology
- Medical Imaging
Background:
- Clear cell renal cell carcinoma (ccRCC) grading is crucial for treatment decisions.
- Accurate noninvasive grading of ccRCC remains a clinical challenge.
Purpose of the Study:
- To evaluate the feasibility of time-dependent diffusion-weighted imaging (td-dMRI) for assessing the pathological World Health Organization/International Society of Urological Pathology (WHO/ISUP) grade of ccRCC.
- To identify td-dMRI parameters that can differentiate between low- and high-grade ccRCC.
Main Methods:
- 138 patients with surgically confirmed ccRCC underwent preoperative td-dMRI.
- Microstructural parameters (cell diameter, intracellular volume fraction, cellularity, extracellular diffusivities) were quantified using a two-compartment model.
- Correlation between td-dMRI parameters and pathological nuclear fraction was assessed.
Main Results:
- Low-grade ccRCC showed lower cellularity and intracellular volume fraction, and higher diameter and extracellular diffusivities compared to high-grade tumors.
- Intracellular volume fraction demonstrated the highest diagnostic performance (AUC=0.943) for differentiating tumor grades, followed by cellularity (AUC=0.931).
- Pathological nuclear fraction moderately correlated with intracellular volume fraction (r=0.65).
Conclusions:
- TD-dMRI parameters show potential for noninvasively assessing WHO/ISUP grades in ccRCC.
- TD-dMRI may serve as a promising biomarker for characterizing ccRCC, aiding in clinical decision-making.

