Abstract

Abstract Background and Aims Cardiovascular health and kidney transplant health are inter-connected [1]. Phase-contrast magnetic resonance imaging (PC-MRI) is a non-invasive means of quantifying blood flow volume within vasculature. Its utility for the assessment of blood flow volumes within the transplant renal artery has not been explored. The aims of this study were to determine if: (A) flow in the transplant artery is influenced by donor and recipients factors, (B) flow in the transplant artery is related to or influences clinical outcomes for transplant recipients. Method Analysis of PC-MRI sequences obtained during 218 kidney transplant magnetic resonance angiograms (MRA) performed at a single centre between 2019 and 2021 was undertaken. All scans were clinically indicated and requested by clinicians to investigate for transplant renal artery stenosis (TRAS). Baseline clinical and demographic data and subsequent clinical outcome data were collected for all study participants. Median follow up was 49 (IQR 40–54) months. For Kaplan-Meier survival analyses, comparison of clinical outcomes by interquartile range of flow volumes was performed, whereby quartile one comprised subjects with the lowest transplant artery blood flow volumes. Statistical analysis was performed using MedCalc Statistical Software version 22.013. Results In this study of 218 subjects, 49 (22.4%) had features of possible TRAS identified on initial MRA. TRAS was subsequently confirmed via intra-arterial digital subtraction angiography in 19 (8.7%) cases. The majority of participants were male 150/218 (68.8%). The commonest cause of ESKD was diabetic kidney disease at 71/218 (32.6%). Living donor transplant recipients were 35/218 (11.5%) of the study population. The median donor age was 55 (IQR 44–65) years. The median time from ESKD to transplantation was 25 (IQR 9–53) months. The median time from transplantation to PC-MRI for all participants was 322 (IQR 81–1744) days; for participants who were ultimately diagnosed with TRAS it was 169 (IQR 76–262) days. The median age of recipients at time of PC-MRI was 56 (IQR 45–64) years. Overall, the mean transplant artery flow volume was 0.41 L/min (95% CI 0.39–0.45 L/min). Rank correlation between age of donor and flow in the transplant artery (L/min) showed r = −0.25 (95% CI −0.37 - −0.12) P = 0.0002. Rank correlation between age of recipient at time of PC-MRI and flow in the transplant artery (L/min) showed r = −0.37 (95% CI −0.48 to −0.25) P ≤ 0.0001. Rank correlation between flow in the transplant artery (L/min) and estimated glomerular filtration rate (mL/min/1.73 m2) showed r = 0.43 (95% CI 0.31–0.53) P < 0.0001. Univariable linear regression analysis of flow in the transplant artery (L/min) and estimated glomerular filtration rate (mL/min/1.73 m2) was R2 0.14, DF regression = 1 DF residual = 214, F = 34.7, P < 0.0001 (Fig. 1). Overall, 35 (16.1%) participants experienced kidney transplant failure and 42 (19.3%) participants died within the study follow up period. Kaplan-Meier analysis showed no significant difference in kidney transplant survival between four groups categorized according to transplant artery flow volumes, logrank test P = 0.93 (Fig. 2A). Subjects in the first quartile were at greater risk of death, logrank test P = 0.01, HR 4.36 (95% CI 1.77–10.74) compared with fourth quartile (Fig. 2B) Conclusion This study has demonstrated that both older donor age and older recipient age negatively correlate with transplant artery flow, and that transplant artery flow is positively correlated and predicts estimated glomerular filtration rate. Finally, recipients with low transplant artery flow volume are at greater risk of death. Neither cause nor effect of low blood flow volume have been elucidated in this study. However, improving transplant blood flow by optimising cardiovascular health may have a positive impact on outcomes for people with kidney transplants and warrants further study.

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