Acute Kidney Injury (AKI) is a sudden reduction in kidney function, with causes and degree of renal recovery varying widely between individuals. MRI provides a method to assess changes associated with AKI. Here, we use multi-parametric MRI to monitor renal changes in AKI at time of injury and recovery. At peak AKI an increase was seen in renal volumes and T2* values while cortical ADC and perfusion was lower during the AKI phase. T1 maps showed an increase at time of AKI with a reduction in corticomedullary differentiation. At 3 months post AKI, T1 remained higher than HVs.
Data Acquisition: Three patients with AKI Stage 3 (1M; 29-51yrs, no pre-existing kidney disease) were scanned 2–5 days and 3 months following peak AKI, and will be assessed again at 1 year. 7 healthy volunteers (HV) were scanned as a reference. Serum creatinine and eGFR measures were acquired at each visit. Scanning was performed on a 3T Philips Ingenia scanner (Multi-Transmit, dStream). Localiser bTFE scans were acquired in three orthogonal planes for planning and organ volume measures. ASL, T1, and DWI data were acquired in matched space (FOV 288x288mm, resolution 3x3x5mm, SENSE 2) using respiratory-triggered schemes with 5 coronal-oblique slices collected using a spin-echo EPI readout. ASL was collected using a flow alternating inversion recovery (FAIR) scheme (in-plane pre- and post-saturation, post-label delay 1800ms, selective(S)/non-selective(NS) thickness 45/400mm, 25 pairs). Inversion recovery T1 data was acquired at 13 inversion times with a SE-EPI readout. DWI data was acquired with 8 b-values. T2* data was acquired with an mFFE scheme with 16 echo times (TE 1.4ms, echo spacing 1.4ms, voxel resolution1x1x5mm and FOV 350x350mm). T1 measures were also obtained using a bFFE readout at higher resolution (1.5x1.5mm). PC-MRI was used to assess renal artery blood flow with bTRANCE angiography to ensure measurements were taken prior to any bifurcations.
Data Analysis: Kidney volumes were calculated from bTFE scans (Analyze9). All multiparametric maps were generated using Matlab. Inversion recovery data was fit to form T1 maps. Perfusion maps were formed from the average perfusion weighted images (S-NS) normalised to a base magnetisation image which were fit to a kinetic model to calculate perfusion maps. mFFE data was fit to compute T2* maps. DWI data was fit to both an ADC and an IVIM model to calculate D, D* and perfusion fraction. Cortex and medulla masks were created from the T1 maps. All measures are the mode of histogram analysis. Vessel flow was analysed using Philips ViewForum Qflow software, and used to compute global kidney perfusion by combining with kidney volume.
1. Hueper K, Peperhove M, Rong S, et al. T1-mapping for assessment of ischemia-induced acute kidney injury and prediction of chronic kidney disease in mice. Eur. Radiol. 2014;24:2252–60.
2. Hueper K, Gutberlet M, Rong S, et al. Acute Kidney Injury: Arterial Spin Labeling to Monitor Renal Perfusion Impairment in Mice—Comparison with Histopathologic Results and Renal Function. Radiology, 2013;270:117-124
3. Heuper K, Rong S, Gutberlet M, et al, T2 Relaxation Time and Apparent Diffusion Coefficient for Noninvasive Assessment of Renal Pathology After Acute Kidney Injury in Mice: Comparison With Histopathology. Invest. Radiol 2013;48: 834-82
4. Rabb H, Griffin MD, McKay DB, et al. Inflammation in AKI: Current Understanding, Key Questions, and Knowledge Gaps. J Am Soc Nephrol. 2016;27(2):371-9.