Assessment of transplanted kidney function based on apparent diffusion coefficient histogram

Objectives This study evaluated the effectiveness of whole-volume apparent diffusion coefficient (ADC) histogram analysis for stratifying renal allograft function. Methods A retrospective analysis included 85 renal transplant recipients with ADC measurements from May 2019 to February 2024. They were divided into three groups based on estimated glomerular filtration rate (eGFR): normal graft function (nRAF, eGFR > 60 mL/min/1.73 m2), mild to moderate graft injury (mRAI, 30 mL/min/1.73 m2≤eGFR ≤ 60 mL/min/1.73 m2), and severe allograft injury (sRAI, eGFR < 30 mL/min/1.73 m2). Receiver operating characteristic (ROC) analysis compared the ability of histogram features to differentiate these groups. Correlations between time since transplantation and histogram features were also evaluated. Results Sixteen ADC-based histogram features were extracted. Eight parameters were valuable for assessing renal dysfunction (|r|≥0.3, P < 0.05). Seven parameters—ADCmean and Percentiles (10th, 25th, 50th, 75th, 90th, and 95th)—differed significantly between nRAF and sRAI (P < 0.05), with the 50th percentile yielding the largest area under the curve (AUC = 0.785; 95% CI: 0.624-0.928). Two parameters (10th and 25th percentiles) differed significantly between nRAF and mRAI (P < 0.05), with the 10th percentile achieving the largest AUC (0.684; 95% CI: 0.560-0.808). The 10th percentile was negatively correlated with time since transplantation. Conclusions ADC-based histogram analysis effectively stratifies renal allograft function and can be used for long-term monitoring of kidney transplant patients in clinical practice. Advances in knowledge This study shows that ADC-based histogram analysis can distinguish different degrees of renal allograft dysfunction and is sensitive to early and chronic renal function changes. It offers a non-invasive method for long-term monitoring of kidney transplant patients.