Usefulness of Multiparametric Ultrasound for Evaluating Structural Abnormality of Transplanted Kidney: Can We Predict Histologic Abnormality on Renal Biopsy in Advance?

Abstract

OBJECTIVE: The purpose of this study was to investigate the associations between microscopic abnormalities of transplanted kidneys and sonography-based imaging biomarkers, including elasticity, venous impedance index, arterial resistive index, and size.

MATERIALS AND METHODS: Between 2011 and 2015, 159 recipients underwent sonography and biopsy of a transplanted kidney at our institution; 104 adult patients were included in this study. The maximal longitudinal length on gray-scale images, arterial resistive index, and venous impedance index on Doppler images and shear wave velocity on acoustic radiation force impulse imaging or Young modulus on supersonic shear imaging were measured before biopsy. The Banff criteria (2009 update), an international standardized classification and scoring system for renal allograft pathology, were used to evaluate the biopsy samples. Sonography parameters and clinical variables were analyzed with individual and summed Banff scores.

RESULTS: Spearman rank correlation coefficients and ordinal logistic regression showed no association between sonography parameters and summed Banff scores. Only the interval between transplant and biopsy was significantly associated with summed Banff scores (p < 0.05). Univariate logistic regression analysis with individual Banff scores showed associations of one Banff feature with arterial resistive index, three with venous impedance index, and six with interval between transplant and biopsy (p < 0.05). Sonoelastography parameters were not associated with any individual Banff score.

CONCLUSION: Neither sonoelastography parameter was associated with any histopathologic change of renal allografts. Although arterial resistive index and venous impedance index were related to a few individual Banff scores, length of time between transplant and biopsy showed stronger correlation than any imaging biomarkers with renal allograft deterioration.