Evaluation of renal function in chronic kidney disease using histogram analysis based on multiple diffusion models

Area of Science:

• Medical Imaging
• Radiology
• Nephrology

Background:

• Chronic kidney disease (CKD) poses a significant health burden.
• Early detection of renal impairment is crucial for timely intervention.
• Non-invasive diagnostic methods are needed for assessing early-stage CKD.

Purpose of the Study:

• To evaluate the diagnostic performance of histogram features from multiple diffusion models in predicting early renal impairment in CKD patients.
• To compare the efficacy of different diffusion models (mono-exponential, IVIM, SEM, DKI) and their combined use.

Main Methods:

• Diffusion-weighted imaging (DWI) was performed on 77 CKD patients and 30 healthy controls.
• Multiple diffusion models (mono-exponential, IVIM, SEM, DKI) were applied to DWI data.
• Histogram features of diffusion metrics were analyzed and correlated with renal function (eGFR, serum creatinine).

Main Results:

• All diffusion models demonstrated high diagnostic efficiency in differentiating mild CKD from healthy controls.
• The combined diffusion model achieved the highest AUC (0.861) for predicting early renal impairment.
• Significant correlations were observed between histogram features and clinical markers of renal function.

Conclusions:

• Histogram analysis of multiple diffusion metrics is a feasible approach for non-invasive assessment of early renal impairment in CKD.
• Advanced diffusion models combined with histogram analysis provide accurate, non-invasive evaluation of early renal damage.
• This technique holds promise for improved CKD management and monitoring.