CC BY 4.0 · J Brachial Plex Peripher Nerve Inj 2021; 16(01): e17-e23
DOI: 10.1055/s-0041-1729176
Review Article

Magnetic Resonance Neurography for Evaluation of Peripheral Nerves

Vanessa Ku
1   Department of Orthopaedic Surgery, Texas Tech University Health Sciences Center, Lubbock, Texas, United States
,
Cameron Cox
1   Department of Orthopaedic Surgery, Texas Tech University Health Sciences Center, Lubbock, Texas, United States
,
Andrew Mikeska
1   Department of Orthopaedic Surgery, Texas Tech University Health Sciences Center, Lubbock, Texas, United States
,
1   Department of Orthopaedic Surgery, Texas Tech University Health Sciences Center, Lubbock, Texas, United States
2   Department of Orthopaedic Surgery, University Medical Center, Lubbock, Texas, United States
› Author Affiliations

Abstract

Peripheral nerve injuries (PNIs) continue to present both diagnostic and treatment challenges. While nerve transections are typically a straightforward diagnosis, other types of PNIs, such as chronic or traumatic nerve compression, may be more difficult to evaluate due to their varied presentation and limitations of current diagnostic tools. As a result, diagnosis may be delayed, and these patients may go on to develop progressive symptoms, impeding normal activity. In the past, PNIs were diagnosed by history and clinical examination alone or techniques that raised concerns regarding accuracy, invasiveness, or operator dependency. Magnetic resonance neurography (MRN) has been increasingly utilized in clinical settings due to its ability to visualize complex nerve structures along their entire pathway and distinguish nerves from surrounding vasculature and tissue in a noninvasive manner. In this review, we discuss the clinical applications of MRN in the diagnosis, as well as pre- and postsurgical assessments of patients with peripheral neuropathies.



Publication History

Received: 01 December 2020

Accepted: 29 January 2021

Article published online:
14 May 2021

© 2021. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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