FP494MAGNETIC RESONANCE IMAGING BIOMARKERS CORRELATE TO UACR IN DIABETIC KIDNEY DISEASE

Renal magnetic resonance imaging (MRI) techniques are currently in vogue, as they provide in vivo information on renal volume, function, metabolism, perfusion, oxygenation, and microstructural alterations, without the need for exogenous contrast media. New imaging biomarkers can be identified using these tools, which represent a major advance in the understanding and study of the different pathologies affecting the kidney. Diabetic kidney disease (DKD) is one of the most important diseases worldwide due to its high prevalence and impact on public health. However, its multifactorial etiology poses a challenge for both basic and clinical research. Therefore, the use of novel renal MRI techniques is an attractive step forward in the comprehension of DKD, both in its pathogenesis and in its detection and surveillance in the clinical practice. This review article outlines the most promising MRI techniques in the study of DKD, with the purpose of stimulating their clinical translation as possible tools for the diagnosis, follow-up, and monitoring of the clinical impacts of new DKD treatments.

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FP491MAGNETIC RESONANCE IMAGING ALLOWS A NOVEL NON-INVASIVE FUNCTIONAL AND PATHOPHYSIOLOGIC ASSESSMENT OF DIABETIC KIDNEY DISEASE

Nephrology Dialysis Transplantation ◽

10.1093/ndt/gfz106.fp491 ◽

2019 ◽

Vol 34 (Supplement_1) ◽

Author(s):

Kianoush Makvandi ◽

Gert Jensen ◽

Paul Hockings ◽

Tim Unnerstall ◽

Henrik Leonhardt ◽

...

Keyword(s):

Kidney Disease ◽

Diabetic Kidney Disease ◽

Resonance Imaging ◽

Diabetic Kidney ◽

Non Invasive

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Prognostic Imaging Biomarkers for Diabetic Kidney Disease (iBEAt): Study protocol

10.1101/2020.01.13.20017228 ◽

2020 ◽

Author(s):

Kim M Gooding ◽

Chrysta Lienczewski ◽

Massimo Papale ◽

Niina Koivuviita ◽

Marlena Maziarz ◽

...

Keyword(s):

Type 2 Diabetes ◽

Kidney Disease ◽

Diabetic Kidney Disease ◽

Imaging Study ◽

Prognostic Biomarkers ◽

Imaging Biomarkers ◽

Diabetic Kidney ◽

Central Processing ◽

Renal Mri

ABSTRACTDiabetic kidney disease (DKD) is traditionally classified based on albuminuria and reduced kidney function (estimated glomerular filtration rate (eGFR)), but these have limitations as prognostic biomarkers due to the heterogeneity of DKD. Novel prognostic markers are needed to improve stratification of patients based on risk of disease progression.The iBEAT study, part of the BEAt-DKD consortium, aims to determine whether renal imaging biomarkers (magnetic resonance imaging (MRI) and ultrasound (US)) provide insight into the pathogenesis and heterogeneity of DKD (primary aim), and whether they have potential as prognostic biomarkers in DKD progression (secondary aim).iBEAT is a prospective multi-centre observational cohort study recruiting 500 patients with type 2 diabetes (T2D) and eGFR > 30ml/min/1.73m2. At baseline each participant will undergo quantitative renal MRI and US imaging with central processing for MRI images. Blood sampling, urine collection and clinical examinations will be performed and medical history obtained at baseline, and these assessments will be repeated annually for 3 years. Biological samples will be stored in a central laboratory for later biomarker and validation studies. All data will be stored in a central data depository. Data analysis will explore the potential associations between imaging biomarkers and renal function, and whether the imaging biomarkers may improve the prediction of DKD progression rates.Embedded within iBEAT are ancillary substudies that will (1) validate imaging biomarkers against renal histopathology; (2) validate MRI based renal blood flow against water-labelled positron-emission tomography (PET); (3) develop machine-learning methods for automated processing of renal MRI images; (4) examine longitudinal changes in imaging biomarkers; (5) examine whether the glycocalyx, microvascular function and structure are associated with imaging biomarkers and eGFR decline; (6) a pilot study to examine whether the findings in T2D can be extrapolated to type 1 diabetes.The iBEAT study, the largest DKD imaging study to date, will provide invaluable insights into the progression and heterogeneity of DKD, and aims to contribute to a more personalized approach to the management of DKD in patients with type 2 diabetes.

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