Comparative Study of Microvascular Flow and Viscoelasticity Imaging in Monitoring Renal Allograft Function

This study aimed to compare the efficacy of microvascular flow imaging (MVFI) and ultrasound viscoelasticity imaging (UVI) in assessing renal allograft stability, and to evaluate their potential as noninvasive diagnostic tools for early dysfunction detection and biopsy guidance.

A total of 61 renal transplant recipients (37 stable, 24 unstable) were ultimately included. All participants underwent conventional ultrasonography, MVFI, and UVI. Quantitative parameters included entire color pixel percentage (eCPP), cortical color pixel percentage (cCPP), and viscoelastic metrics (elasticity, viscosity, and dispersion). Group differences were assessed using appropriate statistical tests; correlations with estimated glomerular filtration rate (eGFR) and serum creatinine were evaluated; and receiver operating characteristic (ROC) curves were generated to assess diagnostic performance. Intra- and inter-observer consistency was calculated to ensure measurement reliability.

Significant differences in color pixel percentage and multiple cortical viscoelastic parameters (eg, mean elasticity and viscosity) were observed between stable and unstable groups (p < .05). cCPP correlated strongly with eGFR (r = 0.715, p < .001) and serum creatinine (r = -0.731, p < .001), whereas other viscoelastic metrics showed weaker correlations. ROC analysis revealed that cCPP had superior diagnostic accuracy compared to the combined viscoelastic model. Both modalities exhibited excellent reproducibility (ICC >0.87 for all parameters).

MVFI provides high diagnostic accuracy for distinguishing stable and unstable renal allografts (cCPP AUC = 0.95), outperforming UVI parameters. UVI provides complementary microstructural information, and combining MVFI and UVI may enhance noninvasive monitoring and optimize biopsy decision-making in renal transplant recipients.