Evidence map›Paper›PMID 39335687›Full record

ReviewDiagnostics (Basel, Switzerland)2024

Advances in Ultrasound-Guided Surgery and Artificial Intelligence Applications in Musculoskeletal Diseases.

Soichi Hattori, Rachit Saggar, Eva Heidinger, Andrew Qi, Joseph Mullen, Brianna Fee, Cortez L Brown, Stephen P Canton, Devon Scott, MaCalus V Hogan

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–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

10 citing papers in PubMed.

  1. Review
  2. Review
  3. Carpal Tunnel Syndrome Diagnosis: A Narrative Review of Complementary Roles of Neuromuscular Ultrasound and Electrodiagnostic Studies.Medical science monitor : international medical journal of experimental and clinical research · 2026
    Review
  4. Article
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  9. Article
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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

10 authors.

Soichi HattoriFoot and Ankle Injury Research (FAIR), Division of Foot and Ankle, Department of Orthopaedic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15219, USA.ORCID 0000-0003-3818-8988
Rachit SaggarFoot and Ankle Injury Research (FAIR), Division of Foot and Ankle, Department of Orthopaedic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15219, USA.ORCID 0000-0002-9123-7999
Eva HeidingerFoot and Ankle Injury Research (FAIR), Division of Foot and Ankle, Department of Orthopaedic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15219, USA.ORCID 0009-0003-9463-8899
Andrew QiFoot and Ankle Injury Research (FAIR), Division of Foot and Ankle, Department of Orthopaedic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15219, USA.
Joseph MullenFoot and Ankle Injury Research (FAIR), Division of Foot and Ankle, Department of Orthopaedic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15219, USA.
Brianna FeeFoot and Ankle Injury Research (FAIR), Division of Foot and Ankle, Department of Orthopaedic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15219, USA.
Cortez L BrownFoot and Ankle Injury Research (FAIR), Division of Foot and Ankle, Department of Orthopaedic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15219, USA.
Stephen P CantonFoot and Ankle Injury Research (FAIR), Division of Foot and Ankle, Department of Orthopaedic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15219, USA.
Devon ScottFoot and Ankle Injury Research (FAIR), Division of Foot and Ankle, Department of Orthopaedic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15219, USA.
MaCalus V HoganFoot and Ankle Injury Research (FAIR), Division of Foot and Ankle, Department of Orthopaedic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15219, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ultrasound imaging is a vital imaging tool in musculoskeletal medicine, with the number of publications on ultrasound-guided surgery increasing in recent years, especially in minimally invasive procedures of sports, foot and ankle, and hand surgery. However, ultrasound imaging has drawbacks, such as operator dependency and image obscurity. Artificial intelligence (AI) and deep learning (DL), a subset of AI, can address these issues. AI/DL can enhance screening practices for hip dysplasia and osteochondritis dissecans (OCD) of the humeral capitellum, improve diagnostic accuracy for carpal tunnel syndrome (CTS), and provide physicians with better prognostic prediction tools for patients with knee osteoarthritis. Building on these advancements, DL methods, including segmentation, detection, and localization of target tissues and medical instruments, also have the potential to allow physicians and surgeons to perform ultrasound-guided procedures more accurately and efficiently. This review summarizes recent advances in ultrasound-guided procedures for musculoskeletal diseases and provides a comprehensive overview of the utilization of AI/DL in ultrasound for musculoskeletal medicine, particularly focusing on ultrasound-guided surgery.

Indexed as

artificial intelligencedeep learningmusculoskeletal ultrasoundradiomicsultrasound-guided surgery

Identifiers

PMID39335687
PMCPMC11431371

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.