Muscle Steatosis and Fibrosis in Older Adults, From the


Journal

AJR. American journal of roentgenology
ISSN: 1546-3141
Titre abrégé: AJR Am J Roentgenol
Pays: United States
ID NLM: 7708173

Informations de publication

Date de publication:
23 Aug 2023
Historique:
medline: 23 8 2023
pubmed: 23 8 2023
entrez: 23 8 2023
Statut: aheadofprint

Résumé

The purpose of this article is to review steatosis and fibrosis of skeletal muscle, focusing on older adults. Although CT, MRI, and ultrasound are commonly used to image skeletal muscle and provide diagnoses for a variety of medical conditions, quantitative assessment of muscle steatosis and fibrosis is uncommon. This review provides radiologists with a broad perspective on muscle steatosis and fibrosis in older adults by considering their public health impact, biologic mechanisms, and evaluation using CT, MRI, and ultrasound. Promising directions in clinical research that employ artificial intelligence algorithms and the imaging assessment of biologic age are also reviewed. The presented imaging methods hold promise for improving the evaluation of common conditions affecting older adults including sarcopenia, frailty, and cachexia.

Identifiants

pubmed: 37610777
doi: 10.2214/AJR.23.29742
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Commentaires et corrections

Type : CommentIn

Auteurs

Leon Lenchik (L)

Department of Radiology, Wake Forest University School of Medicine, Medical Center Blvd, Winston-Salem, NC 27157.

Valentina Mazzoli (V)

Department of Radiology, New York University School of Medicine, New York, NY.

Peggy M Cawthon (PM)

Research InsQtute, California Pacific Medical Center, San Francisco, CA.
Department of Epidemiology and BiostaQsQcs, University of California San Francisco, San Francisco, CA.

Russell T Hepple (RT)

Department of Physical Therapy, Department of Physiology and Aging, University of Florida, Gainesville, FL.

Robert D Boutin (RD)

Department of Radiology, Stanford University School of Medicine, Stanford, CA.

Classifications MeSH