Related Experiment Video
Updated: Jun 23, 2025
Unilateral Ureteral Obstruction Model for Investigating Kidney Interstitial Fibrosis
Published on: April 25, 2025
Assessing renal interstitial fibrosis using compartmental, non-compartmental, and model-free diffusion MRI approaches
Wentao Hu1, Yongming Dai2, Fang Liu1
1Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Objective:
To assess renal interstitial fibrosis (IF) using diffusion MRI approaches, and explore whether corticomedullary difference (CMD) of diffusion parameters, combination among MRI parameters, or combination with estimated glomerular filtration rate (eGFR) benefit IF evaluation.
Methods:
Forty-two patients with chronic kidney disease were included, undergoing MRI examinations. MRI parameters from apparent diffusion coefficient (ADC), intra-voxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), and diffusion-relaxation correlated spectrum imaging (DR-CSI) were obtained both for renal cortex and medulla. CMD of these parameters was calculated. Pathological IF scores (1-3) were obtained by biopsy. Patients were divided into mild (IF = 1, n = 23) and moderate-severe fibrosis (IF = 2-3, n = 19) groups. Group comparisons for MRI parameters were performed. Diagnostic performances were assessed by the receiver operator's curve analysis for discriminating mild from moderate-severe IF patients.
Results:
Significant inter-group differences existed for cortical ADC, IVIM-D, IVIM-f, DKI-MD, DR-CSI VB, and DR-CSI VC. Significant inter-group differences existed in ΔADC, ΔMD, ΔVB, ΔVC, ΔQB, and ΔQC. Among the cortical MRI parameters, VB displayed the highest AUC = 0.849, while ADC, f, and MD also showed AUC > 0.8. After combining cortical value and CMD, the diagnostic performances of the MRI parameters were slightly improved except for IVIM-D. Combining VB with f brings the best performance (AUC = 0.903) among MRI bi-variant models. A combination of cortical VB, ΔADC, and eGFR brought obvious improvement in diagnostic performance (AUC 0.963 vs 0.879, specificity 0.826 vs 0.896, and sensitivity 1.000 vs 0.842) than eGFR alone.
Conclusion:
Our study shows promising results for the assessment of renal IF using diffusion MRI approaches.
Critical Relevance Statement:
Our study explores the non-invasive assessment of renal IF, an independent and effective predictor of renal outcomes, by comparing and combining diffusion MRI approaches including compartmental, non-compartmental, and model-free approaches.
Key Points:
Significant difference exists for diffusion parameters between mild and moderate-severe IF. Generally, cortical parameters show better performance than corresponding CMD. Bi-variant model lifts the diagnostic performance for assessing IF.
