Evidence map›Paper›PMID 39544479›Full record

ReviewQuantitative imaging in medicine and surgery2024

Myosteatosis: diagnostic significance and assessment by imaging approaches.

Ana Isabel Garcia-Diez, Marta Porta-Vilaro, Jaime Isern-Kebschull, Natali Naude, Roman Guggenberger, Laura Brugnara, Ana Milinkovic, Alvaro Bartolome-Solanas, Juan Carlos Soler-Perromat, Montserrat Del Amo and 2 more

Abstract readReview
In one paragraph

Review in Quantitative imaging in medicine and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

51 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Intramuscular Fat Infiltration and Knee Osteoarthritis: A Systematic Review and Meta-Analysis.Physiotherapy research international : the journal for researchers and clinicians in physical therapy · 2026
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  8. Baseline body composition and early PRRT outcome in GEP-NETs: an exploratory analysis.European journal of nuclear medicine and molecular imaging · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Ana Isabel Garcia-DiezDepartment of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain.ORCID https://orcid.org/0000-0002-8573-6628
Marta Porta-VilaroDepartment of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain.ORCID https://orcid.org/0000-0002-7462-5586
Jaime Isern-KebschullDepartment of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain.ORCID https://orcid.org/0000-0001-6789-000X
Natali NaudeInstitute of Glycomics, Griffith University, Gold Coast, Queensland, Australia.ORCID https://orcid.org/0000-0002-4941-4285
Roman GuggenbergerInstitute of Diagnostic and Interventional Radiology, University Hospital Zurich, Switzerland.ORCID https://orcid.org/0000-0002-5903-2248
Laura BrugnaraAugust Pi i Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clínic de Barcelona, Barcelona, Spain.ORCID https://orcid.org/0000-0002-9896-5024
Ana MilinkovicChelsea and Westminster Foundation NHS Hospital Trust, Imperial College London, London, UK.ORCID https://orcid.org/0000-0002-7732-9168
Alvaro Bartolome-SolanasDepartment of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain.ORCID https://orcid.org/0000-0002-2307-0007
Juan Carlos Soler-PerromatDepartment of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain.ORCID https://orcid.org/0000-0002-2552-3903
Montserrat Del AmoDepartment of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain.
Anna NovialsAugust Pi i Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clínic de Barcelona, Barcelona, Spain.ORCID https://orcid.org/0000-0003-0465-2949
Xavier TomasDepartment of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain.ORCID https://orcid.org/0000-0003-2189-8721

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Myosteatosis has emerged as an important concept in muscle health as it is associated with an increased risk of adverse health outcomes, a higher rate of complications, and increased mortality associated with ageing, chronic systemic and neuromuscular diseases, cancer, metabolic syndromes, degenerative events, and trauma. Myosteatosis involves ectopic infiltration of fat into skeletal muscle, and it exhibits a negative correlation with muscle mass, strength, and mobility representing a contributing factor to decreased muscle quality. While myosteatosis serves as an additional biomarker for sarcopenia, cachexia, and metabolic syndromes, it is not synonymous with sarcopenia. Myosteatosis induces proinflammatory changes that contribute to decreased muscle function, compromise mitochondrial function, and increase inflammatory response in muscles. Imaging techniques such as computed tomography (CT), particularly opportunistic abdominal CT scans, and magnetic resonance imaging (MRI) or magnetic resonance spectroscopy (MRS), have been used in both clinical practice and research. And in recent years, ultrasound has emerged as a promising bedside tool for measuring changes in muscle tissue. Various techniques, including CT-based muscle attenuation (MA) and intermuscular adipose tissue (IMAT) quantification, MRI-based proton density fat fraction (PDFF) and T1-T2 mapping, and musculoskeletal ultrasound (MSUS)-based echo intensity (EI) and shear wave elastography (SWE), are accessible in clinical practice and can be used as adjunct biomarkers of myosteatosis to assess various debilitating muscle health conditions. However, a stan¬dard definition of myosteatosis with a thorough understanding of the pathophysiological mechanisms, and a consensus in assessment methods and clinical outcomes has not yet been established. Recent developments in image acquisition and quantification have attempted to develop an appropriate muscle quality index for the assessment of myosteatosis. Additionally, emerging studies on artificial intelligence (AI) may provide further insights into quantification and automated assessment, including MRS analysis. In this review, we discuss the pathophysiological aspects of myosteatosis, all the current imaging techniques and recent advances in imaging assessment as potential biomarkers of myosteatosis, and the most common clinical conditions involved.

Indexed as

computed tomography (CT)imaging biomarkersmagnetic resonance (MR)Myosteatosisultrasound (US)

Identifiers

PMID39544479
PMCPMC11558492

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.