Novel non-invasive and quantitative assessment of the renal function of transplanted kidneys using Doppler ultrasonography with the vascular index of superb microvascular imaging

利用多普勒超声和超微血管成像血管指数,对移植肾的肾功能进行新型无创定量评估

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Abstract

PURPOSE: This study assessed the reproducibility and clinical value of the vascular index (VI), derived from superb microvascular imaging (SMI) using Doppler ultrasonography, for evaluating renal function in transplanted kidneys. METHODS: This retrospective study included 63 renal transplant patients who underwent grayscale and Doppler ultrasonography with SMI from January 2022 to February 2023. The VI of the transplanted kidneys was measured using three methods (VIbox, VIF1, VIF2). The VI was compared across chronic kidney disease (CKD) groups categorized by estimated glomerular filtration rate (eGFR) and Kidney Disease: Improving Global Outcomes (KDIGO) CKD risk groups based on eGFR and albuminuria. The correlation between VI and renal function was evaluated. Univariate and multivariate linear regression analyses were used to identify predictors of eGFR. RESULTS: Significant differences in VI were observed among CKD groups based on eGFR (VIbox, P=0.001; VIF1, P<0.001; VIF2, P<0.001) and KDIGO CKD groups based on eGFR and albuminuria (VIbox, P=0.039; VIF1, P=0.001; VIF2, P<0.001). VIF1 and VIF2 demonstrated moderate/high correlations with eGFR (r=0.627, P<0.001 and r=0.657, P<0.001, respectively) and serum creatinine (r=-0.626, P<0.001 and r=-0.649, P<0.001, respectively). VIbox moderately correlated with eGFR (r=0.445, P<0.001). Multivariate regression identified the urine albumincreatinine ratio (ACR) (adjusted odds ratio [aOR], 1.122; 95% confidence interval [CI], -0.007 to, 0.000; P=0.030) and VIF2 (aOR, 1.114; 95% CI, 0.466 to 1.235; P<0.001) were independently associated with eGFR. CONCLUSION: The VI measured by drawing a region of interest along the border of the transplanted kidney in SMI (VIF2) is highly reproducible and correlates well with eGFR. Both VIF2 and ACR independently predict eGFR.

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