To evaluate renal allografts function early after transplantation using intravoxel incoherent motion (IVIM) and arterial spin labeling (ASL) MRI. This prospective study was approved by the local ethics committee, and written informed consent was obtained from all participants. A total of 82 participants with 62 renal allograft recipients (2-4weeks after kidney transplantation) and 20 volunteers were enrolled to be scanned using IVIM and ASL MRI on a 3.0T MR scanner. Recipients were divided into two groups with either normal or impaired function according to the estimated glomerular filtration rate (eGFR) with a threshold of 60ml/min/1.73m(2). The apparent diffusion coefficient (ADC) of pure diffusion (ADCslow), the ADC of pseudodiffusion (ADCfast), perfusion fraction (PF), and renal blood flow (RBF) of cortex were compared among three groups. The correlation of ADCslow, ADCfast, PF and RBF with eGFR was evaluated. The receiver operating characteristic (ROC) curve and binary logistic regression analyses were performed to assess the diagnostic efficiency of using IVIM and ASL parameters to discriminate allografts with impaired function from normal function. P0.05). Cortical RBF in allografts with normal function was statistically lower than that of healthy controls (P<0.001). Mean cortical ADCslow, ADCfast, PF and RBF were lower for allografts with impaired function than that with normal function (P<0.05). Mean cortical ADCslow, ADCfast, PF and RBF showed a positive correlation with eGFR (all P<0.01) for recipients. The combination of IVIM and ASL MRI showed a higher area under the ROC curve (AUC) (0.865) than that of ASL MRI alone (P=0.02). Combined IVIM and ASL MRI can better evaluate the diffusion and perfusion properties for allografts early after kidney transplantation.

Xie S, et al. Korean J Radiol. 2017 Nov-Dec;18(6):898-905. https://doi.org/10.3348/kjr.2017.18.6.898

A scoring model based on gadoxetic acid–enhanced MRI enabled noninvasive preoperative prediction of high-risk pathologic features in patients with hepatocellular carcinoma and could be used to predict early recurrence.