Evidence map›Paper›PMID 39881040›Full record

ArticleInsights into imaging2025

Imaging of elbow entrapment neuropathies.

Domenico Albano, Gabriella Di Rocco, Salvatore Gitto, Francesca Serpi, Stefano Fusco, Paolo Vitali, Massimo Galia, Carmelo Messina, Luca Maria Sconfienza

Abstract read
In one paragraph

Article in Insights into imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Domenico AlbanoIRCCS Istituto Ortopedico Galeazzi, Milan, Italy. albanodomenico.md@gmail.com.ORCID http://orcid.org/0000-0001-7989-9861
Gabriella Di RoccoScuola di Specializzazione in Radiodiagnostica, Università Degli Studi di Milano, Milano, Italy.
Salvatore GittoIRCCS Istituto Ortopedico Galeazzi, Milan, Italy.
Francesca SerpiIRCCS Istituto Ortopedico Galeazzi, Milan, Italy.
Stefano FuscoDepartment of Biomedical Sciences for Health, Università Degli Studi di Milano, Milan, Italy.
Paolo VitaliIRCCS Istituto Ortopedico Galeazzi, Milan, Italy.
Massimo GaliaSection of Radiology, Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University Hospital "Paolo Giaccone", Palermo, Italy.
Carmelo MessinaDepartment of Biomedical Sciences for Health, Università Degli Studi di Milano, Milan, Italy.
Luca Maria SconfienzaIRCCS Istituto Ortopedico Galeazzi, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Entrapment neuropathies at the elbow are common in clinical practice and require an accurate diagnosis for effective management. Understanding the imaging characteristics of these conditions is essential for confirming diagnoses and identifying underlying causes. Ultrasound serves as the primary imaging modality for evaluating nerve structure and movement, while MRI is superior for detecting muscle denervation. Plain radiography and CT play a minor role and can be used for the evaluation of bony structures and calcifications/ossifications. Comprehensive knowledge of anatomical landmarks, nerve pathways, and compression sites is crucial for clinicians to accurately interpret imaging and guide appropriate treatment strategies for entrapments of ulnar, median, and radial nerves, and their branches. CRITICAL RELEVANCE STATEMENT: Accurate imaging and anatomical knowledge are essential for diagnosing elbow entrapment neuropathies. Ultrasound is the preferred modality for assessing nerve structure and motion, while MRI excels in detecting muscle denervation and guiding effective management of ulnar, median, and radial nerve entrapments. KEY POINTS: Ultrasound is the primary modality for assessing nerve structure and stability. Findings include nerve structural loss, isoechogenicity, thickening, and hyper-vascularization. MRI provides a comprehensive evaluation of the elbow and accurate muscle assessment. Imaging allows the identification of compressive causes, including anatomical variants, masses, or osseous anomalies. Awareness of anatomical landmarks, nerve pathways, and compression sites is essential.

Indexed as

ElbowMagnetic resonance imaging.Nerve compression syndromesUltrasonography

Identifiers

PMID39881040
PMCPMC11780019

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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.