Multiparametric magnetic resonance imaging allows non-invasive functional and structural evaluation of diabetic kidney disease
Journal article, 2022

Background We sought to develop a novel non-contrast multiparametric MRI (mpMRI) protocol employing several complementary techniques in a single scan session for a comprehensive functional and structural evaluation of diabetic kidney disease (DKD). Methods In the cross-sectional part of this prospective observational study, 38 subjects ages 18-79 years with type 2 diabetes and DKD [estimated glomerular filtration rate (eGFR) 15-60 mL/min/1.73 m(2)] and 20 age- and gender-matched healthy volunteers (HVs) underwent mpMRI. Repeat mpMRI was performed on 23 DKD subjects and 10 HVs. By measured GFR (mGFR), 2 DKD subjects had GFR stage G2, 16 stage G3 and 20 stage G4/G5. A wide range of MRI biomarkers associated with kidney haemodynamics, oxygenation and macro/microstructure were evaluated. Their optimal sensitivity, specificity and repeatability to differentiate diabetic versus healthy kidneys and categorize various stages of disease as well as their correlation with mGFR/albuminuria was assessed. Results Several MRI biomarkers differentiated diabetic from healthy kidneys and distinct GFR stages (G3 versus G4/G5); mean arterial flow (MAF) was the strongest predictor (sensitivity 0.94 and 1.0, specificity 1.00 and 0.69; P = .04 and .004, respectively). Parameters significantly correlating with mGFR were specific measures of kidney haemodynamics, oxygenation, microstructure and macrostructure, with MAF being the strongest univariate predictor (r = 0.92; P < .0001). Conclusions A comprehensive and repeatable non-contrast mpMRI protocol was developed that, as a single, non-invasive tool, allows functional and structural assessment of DKD, which has the potential to provide valuable insights into underlying pathophysiology, disease progression and analysis of efficacy/mode of action of therapeutic interventions in DKD.

magnetic resonance imaging (MRI)

multiparametric

diabetic kidney disease

chronic kidney disease

biomarkers

Author

Kianoush Makvandi

University of Gothenburg

Paul Hockings

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

Gert Jensen

University of Gothenburg

Tim Unnerstall

Sahlgrenska University Hospital

Henrik Leonhardt

Sahlgrenska University Hospital

Lisa V. Jarl

Antaros Medical AB

Camilla Englund

Antaros Medical AB

Susan Francis

University of Nottingham

Anna K. Sundgren

AstraZeneca AB

Johannes Hulthe

Antaros Medical AB

Seema Baid-Agrawal

University of Gothenburg

CKJ: Clinical Kidney Journal

2048-8505 (ISSN) 2048-8513 (eISSN)

Vol. 15 7 1387-1402

Subject Categories

Other Clinical Medicine

Clinical Laboratory Medicine

Radiology, Nuclear Medicine and Medical Imaging

DOI

10.1093/ckj/sfac054

More information

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3/7/2024 9