NCT06883669

Brief Summary

  1. 1.To develop an AI system that can automatically identify standard sections and save images during wrist and hand joint ultrasound scans, while labeling key anatomical structures.
  2. 2.To recruit sonographers untrained in musculoskeletal ultrasound, train them in wrist and hand joint scans, and compare their scanning speed and image quality when using and not using the AI system.

Trial Health

57
Monitor

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
500

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Jan 2021

Longer than P75 for all trials

Geographic Reach
1 country

1 active site

Status
recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

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Study Timeline

Key milestones and dates

Study Start

First participant enrolled

January 1, 2021

Completed
4.2 years until next milestone

First Submitted

Initial submission to the registry

March 11, 2025

Completed
8 days until next milestone

First Posted

Study publicly available on registry

March 19, 2025

Completed
1 month until next milestone

Primary Completion

Last participant's last visit for primary outcome

May 1, 2025

Completed
1 month until next milestone

Study Completion

Last participant's last visit for all outcomes

June 1, 2025

Completed
Last Updated

April 4, 2025

Status Verified

March 1, 2025

Enrollment Period

4.3 years

First QC Date

March 11, 2025

Last Update Submit

March 31, 2025

Conditions

EducationJoint Diseases

Keywords

ultrasoundhandmedical educationartificial intelligencedeep learningwrist

Outcome Measures

Primary Outcomes (1)

  • Image acquisition is complete

    Day 1

Study Arms (2)

Research Subjects-for AI system establishment

Collect ultrasound images of wrist and hand joints, annotate and segment them frame - by - frame for model training.

Research Subjects-for AI system validation

Recruit sonographers untrained in musculoskeletal ultrasound, train them in wrist and hand joint scans, and compare their scanning speed and image quality when using and not using the AI system.

Eligibility Criteria

Age18 Years - 100 Years
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodProbability Sample
Study Population

healthy individuals and rheumatoid arthritis (RA) patients，sonographers untrained for MSK ultrasound

You may qualify if:

  • Healthy volunteers with good compliance
  • No history of disease on peripheral nerve, muscle, or tendons;
  • No early - stage RA or history of RA.

You may not qualify if:

  • \. Amputees or those with limb disabilities.
  • Individuals with poor compliance.
  • (2) Research Subjects-for AI system validation
  • \. Sonographers with at least 2 years of ultrasound scanning experience
  • \. Those who have performed musculoskeletal ultrasound scanning or received related training

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Xinyi Tang

Chengdu, Sichuan, China

RECRUITING

MeSH Terms

Conditions

Joint Diseases

Condition Hierarchy (Ancestors)

Musculoskeletal Diseases

Study Officials

  • Xinyi Tang

    Department of Medical Ultrasound, West China Hospital, Sichuan University

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Xinyi Tang

CONTACT

+8615680819215tangxinyi1996@outlook.com

Study Design

Study Type
observational
Observational Model
CASE ONLY
Time Perspective
PROSPECTIVE
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Principal Investigator

Study Record Dates

First Submitted

March 11, 2025

First Posted

March 19, 2025

Study Start

January 1, 2021

Primary Completion

May 1, 2025

Study Completion

June 1, 2025

Last Updated

April 4, 2025

Record last verified: 2025-03

Locations

CN(1)