Intravoxel incoherent motion diffusion-weighted imaging for predicting kidney allograft function decline: comparison...

Area of Science:

• Nephrology
• Radiology
• Transplant Medicine

Background:

• Kidney allograft function decline is a significant concern in transplant recipients.
• Predicting long-term allograft function is crucial for patient management.
• Diffusion-weighted imaging (DWI) shows potential for non-invasive assessment of kidney allografts.

Purpose of the Study:

• To evaluate the added benefit of diffusion-weighted imaging (DWI) over clinical parameters in predicting kidney allograft function decline.
• To assess the predictive capability of different models incorporating clinical and DWI parameters.
• To determine the prognostic value of specific DWI-derived parameters for long-term allograft outcomes.

Main Methods:

• Retrospective analysis of data from 97 kidney allograft recipients undergoing DWI.
• Analysis of DWI signals using mono-exponential and bi-exponential models to derive parameters like apparent diffusion coefficient (ADC_T), true diffusion (D), pseudo-diffusion (D*), and perfusion fraction (fp).
• Construction and comparison of three predictive models: clinical parameters only, DWI parameters only, and a combined model, using Area Under the Receiver Operating Characteristic Curve (AUROC).

Main Results:

• Forty-five patients experienced kidney allograft function decline over a median follow-up of 98 months.
• The combined model (Model 3) incorporating clinical and DWI parameters demonstrated significantly higher AUROCs than the clinical model (Model 1) at 60 and 84 months.
• Multivariable analysis identified baseline eGFR, proteinuria, cortical D, and cortical fp as significant predictors of long-term allograft function decline.

Conclusions:

• Diffusion-weighted imaging (DWI) parameters, particularly cortical D and fp, offer added prognostic value for predicting long-term kidney allograft function decline.
• Integrating DWI-derived parameters (cortical D and fp) with baseline clinical factors (eGFR and proteinuria) improves the prediction accuracy compared to clinical parameters alone.
• Multi-b DWI shows promise for managing kidney transplant recipients and monitoring allograft health.