The human kidneys play a pivotal role in regulating blood pressure, water, and salt homeostasis, but assessment of renal function typically requires invasive methods. Deuterium metabolic imaging (DMI) is a novel, noninvasive technique for mapping tissue-specific uptake and metabolism of deuterium-labeled tracers. This study evaluates the feasibility of renal DMI at 7-Tesla (7T) to track deuterium-labeled tracers with high spatial and temporal resolution, aiming to establish a foundation for potential clinical applications in the noninvasive investigation of renal physiology and pathophysiology. Five healthy participants (3 m/2f) underwent renal DMI at 7T using MR spectroscopic imaging with concentric ring trajectory sampling. Two subjects participated in dynamic DMI experiments after oral administration of deuterium-labeled water (D2O, 0.25, and 0.5 mL/kg) or glucose (6,6'-2H-Glc, 0.5 g/kg) following 12 h overnight fasting. Continuous glucose monitoring (CGM) was performed using FreeStyle Libre 3 and compared to renal 2H-glucose levels. Three-dimensional maps of 2H-water and 2H-glucose were acquired every ∼8.5 min at isotropic resolutions of ∼1.8 and ∼0.9 mL, respectively. Tensor Marchenko-Pastur Principal Component Analysis (tMPPCA) was used for spectral denoising. Renal DMI successfully generated dynamic 3D maps of 2H-water and 2H-glucose with improved spatial resolution compared to previous studies. Following D2O ingestion, 2H-water dynamics (0-60 min) and steady-state levels (> 90 min) were assessed. Following 2H-glucose ingestion, renal 2H-Glc concentrations peaked at 1.8 ± 1.0 mM on average over both kidneys, and overall dynamics aligned with interstitial glucose levels simultaneously assessed using CGM sensor. This study demonstrates the feasibility of dynamic renal DMI with improved spatial resolution to noninvasively map multiple 2H-labeled tracers in the human kidney at 7T. Future improvements in signal mitigation and intravenous tracer administration could enhance its clinical utility, potentially aiding in the evaluation of metabolic effects of novel therapies like SGLT-2 inhibitors for personalized treatment strategies.
Niess et al. (Wed,) studied this question.
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