Role of Magnetic Resonance Imaging in Obesity and Diabetes: 2nd Edition

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: 31 August 2026 | Viewed by 604

Special Issue Editor


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Guest Editor
1. Department of Cardiology, Herlev-Gentofte Hospital, Copenhagen, Denmark
2. Department of Clinical Medicine and The August Krogh Institute, NEXS, Copenhagen University, Copenhagen, Denmark
Interests: magnetic resonance imaging; heart failure; diabetes; physiology; diastolic dysfunction
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Dear Colleagues,

Magnetic Resonance Imaging (MRI) has emerged as a crucial diagnostic and monitoring tool in the management of obesity and diabetes and their associated complications. Its non-invasive nature and ability to provide detailed anatomical and functional information make it invaluable for assessing the progression and severity of diabetic complications.

In diabetic foot complications, MRI effectively differentiates osteomyelitis and Charcot neuro-osteoarthropathy, enabling targeted treatment plans. For brain imaging, MRI can detect the early signs of atrophy in patients with diabetes, potentially indicating neurovascular complications. Additionally, MRI techniques such as arterial spin labeling (ASL), blood oxygenation level-dependent (BOLD), and diffusion-weighted imaging (DWI) show promise in the early diagnosis and monitoring of diabetic kidney disease (DKD), providing insights into renal perfusion, oxygenation, and structural changes.

Overall, MRI’s comprehensive capabilities and non-invasive approach make it an essential tool in the clinical management of diabetes, facilitating early intervention and improved patient outcomes.

Dr. Per Lav Madsen
Guest Editor

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Keywords

  • magnetic resonance imaging (MRI)
  • obesity and diabetes
  • diabetic foot complications
  • brain atrophy
  • diabetic kidney disease (DKD)
  • functional MRI
  • non-invasive imaging
  • early diagnosis

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Published Papers (1 paper)

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Review

27 pages, 3589 KB  
Review
Multimodal Magnetic Resonance Imaging in Diabetic Kidney Disease: From Pathophysiological Insights to Clinical Applications
by Mengdan Ni and Bingcang Huang
Diagnostics 2026, 16(11), 1676; https://doi.org/10.3390/diagnostics16111676 - 29 May 2026
Viewed by 271
Abstract
Background: Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease. Conventional clinical markers of renal function lack sufficient sensitivity for early diagnosis, whereas renal biopsy is unsuitable for routine monitoring because of its invasiveness. Objective: This narrative review aimed to [...] Read more.
Background: Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease. Conventional clinical markers of renal function lack sufficient sensitivity for early diagnosis, whereas renal biopsy is unsuitable for routine monitoring because of its invasiveness. Objective: This narrative review aimed to evaluate recent advances in novel, non-invasive multimodal magnetic resonance imaging (MRI) biomarkers for the assessment of renal pathological alterations in DKD. Recent findings: Recent studies have demonstrated that multimodal MRI can non-invasively characterize several key pathological features of DKD, including renal hypoxia, microvascular dysfunction, ectopic fat deposition, and interstitial fibrosis. Furthermore, emerging evidence suggests that these imaging biomarkers may enhance risk stratification, monitor disease progression, and assess treatment efficacy, particularly in the presence of comorbidities and the advent of emerging therapies. Conclusions: Multimodal MRI shows considerable promise in translating advanced imaging biomarkers into clinical practice, facilitating the personalized management of DKD. However, future research must focus on establishing standardized imaging acquisition and analytical protocols, conducting prospective cohort studies to validate the association between imaging biomarkers and hard clinical endpoints, integrating artificial intelligence for automated analysis, and developing molecular imaging probes targeted at early disease pathways. Full article
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