Renal MRI: From Nephron to NMR Signal

Abstract

Renal diseases pose a significant socio-economic burden on healthcare systems. The development of better diagnostics and prognostics is well-recognized as a key strategy to resolve these challenges. Central to these developments are MRI biomarkers, due to their potential for monitoring of early pathophysiological changes, renal disease progression or treatment effects. The surge in renal MRI involves major cross-domain initiatives, large clinical studies, and educational programs. In parallel with these translational efforts, the need for greater (patho)physiological specificity remains, to enable engagement with clinical nephrologists and increase the associated health impact. The ISMRM 2022 Member Initiated Symposium (MIS) on renal MRI spotlighted this issue with the goal of inspiring more solutions from the ISMRM community. This work is a summary of the MIS presentations devoted to: 1) educating imaging scientists and clinicians on renal (patho)physiology and demands from clinical nephrologists, 2) elucidating the connection of MRI parameters with renal physiology, 3) presenting the current state of leading MR surrogates in assessing renal structure and functions as well as their next generation of innovation, and 4) describing the potential of these imaging markers for providing clinically meaningful renal characterization to guide or supplement clinical decision making. We hope to continue momentum of recent years and introduce new entrants to the development process, connecting (patho)physiology with (bio)physics, and conceiving new clinical applications. We envision this process to benefit from cross-disciplinary collaboration and analogous efforts in other body organs, but also to maximally leverage the unique opportunities of renal physiology. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 2.

Keywords: Kidney; MRI; imaging; renal pathophysiology.

Figure 1:

Diagram of renal functional markers from multiple approaches (nephrology, physiology, histopathology, quantitative MRI), with different but related connections to key features of renal health. Markers discussed in this review are shaded in green, and others not covered herein are shaded in blue. Continued efforts to flesh out these relationships, in both health and disease, will inform the development application of MRI as a surrogate or supplemental clinical marker. Abbreviations: ASL=arterial spin labelling; BOLD/T2*=blood oxygen level dependent; DCE=dynamic contrast-enhanced MRI; DWI=diffusion-weighted imaging; DKI=diffusion kurtosis imaging; DTI=diffusion tensor imaging; eGFR=estimated glomerular filtration rate; HEP=high energy phosphates; IVIM=intravoxel-incoherent motion model of diffusion; QSM=quantitative susceptibility mapping; MRE= MR elastography; MTR= magnetization transfer imaging; PC MR=phase-contrast MRI.

Figure 2:

Time courses during kidney vascular occlusions and recovery. Time course of relative changes (mean±SEM) for kidney size (cross sectional area; left panels) and T₂ (blue) and T₂* (red) obtained for the renal cortex (right panels) before the occlusions (baseline), during the intervention (green area), and during recovery. Absolute baseline values (mean±SEM) are denoted; * P < 0.05; # P < 0.01; § P < 0.001. Data from Ref. 26 (Cantow et al., 2022).

Figure 3:

Magnitude images overlaid with QSM maps of the right kidney for a healthy volunteer (left image) and a patient with renal fibrosis (CKD V, eGFR < 15 ml/min/1.73 m², right image). Compared to the healthy renal tissue the fibrotic kidney shows a strong diamagnetic susceptibility (0.04 ± 0.07 ppm vs. −0.43 ± 0.02 ppm). Data from Ref. 80 (Bechler et al., 2021)

Figure 4:

Phase contrast MRI is used to measure bulk flow within the renal artery. (A) The imaging plane must be perpendicular to the renal artery, planned using (i) orthogonal localisers or (ii) a vascular survey. (B) For each phase of the cardiac cycle, (i) magnitude and phase (proportional to velocity) images are acquired at each phase of the cardiac cycle, from which (ii) the arterial flux can be calculated.

Figure 5:

Schematic to illustrate planning of labeling and imaging planes for (A) pseudo-continuous arterial spin labeling (ASL) and (B) flow sensitive alternating inversion recovery (FAIR) ASL.

Figure 6:

Renal microstructure and microcirculation measured by diffusion weighted imaging (DWI). (A) A schematic of the Stejskal-Tanner pulsed gradient spin echo experiment, which forms the basis of the current DWI pulse sequences; (B) DW images acquired at different b-values (with different levels of diffusion-weighting); (C) An ideal mono-exponential ADC fit to the noiseless DWI data; and (D) the corresponding ADC map. (E) Signal fractions (f_slow and f_fast) and (pseudo-) diffusion coefficient (D_slow and D_fast) parameter maps derived from DWI using intravoxel incoherent motion (IVIM) modelling. (F) Mean diffusivity (MD), fractional anisotropy (FA) and direction-encoded FA maps obtained from diffusion tensor imaging (DTI).

Figure 7.

mpMRI in 55 year-old female patient with stable functional allograft (A-F; eGFR 78.4 ml/min/1.73m²) and a 38 year-old female patient with dysfunctional allograft (G-L; eGFR 19.9 ml/min/1.73m²) and fibrosis. ADC and D are decreased while T₁ and T₁ρ are increased in both cortex and medulla in the fibrotic allograft.