MUSCLE-ML: Multimodal Integration of Muscle Strength, Structure by Machine Learning for Precision Rehabilitation After ACL Injury

December 3, 2025 updated by: Patrick Shu-Hang YUNG, Chinese University of Hong Kong

The goal of this clinical trial is to use machine learning (ML) to predict functional recovery by integrating muscle-related factors and other relevant parameters for identification of non-responders to conventional rehabilitation. The main questions it aims to answer are:

Do deficit clusters lead to poorer functional recovery compared to non-deficit clusters? Does an ML-derived composite score that integrates quadriceps/hamstring strength and size outperform isolated metrics in predicting RTP success?

Researchers will compare deficit clusters against non-deficit clusters to determine if deficit clusters lead to poorer functional recovery.

Participants will:

Return for 5 follow-up timepoints in total for PRO and functional assessments including pre-operation, 1-, 3-, 6- and 12-months post-operation.

Study Overview

Status

Not yet recruiting

Conditions

Study Type

Observational

Enrollment (Estimated)

182

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Sampling Method

Probability Sample

Study Population

All the ACLR patients will be recruited at the Orthopaedics Outpatient Clinic at Prince of Wales Hospital.

Description

Inclusion Criteria:

  • Unilateral ACL injury and plan for ACLR
  • Commit the post-operation physiotherapy in Prince of Wales Hospital

Exclusion Criteria:

  • Preoperative radiographic signs of arthritis
  • Patient non-compliance to the rehabilitation program

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Deficit group
no intervention

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Time Frame
International Knee Documentation Committee score
Time Frame: 6- and 12-months post-operation
6- and 12-months post-operation

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Shu Hang YUNG, Chinese University of Hong Kong

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

April 1, 2026

Primary Completion (Estimated)

March 31, 2028

Study Completion (Estimated)

August 31, 2028

Study Registration Dates

First Submitted

December 3, 2025

First Submitted That Met QC Criteria

December 3, 2025

First Posted (Actual)

December 16, 2025

Study Record Updates

Last Update Posted (Actual)

December 16, 2025

Last Update Submitted That Met QC Criteria

December 3, 2025

Last Verified

December 1, 2025

More Information

Terms related to this study

Other Study ID Numbers

  • 2025.374
  • 23241901 (Other Grant/Funding Number: Health and Medical Research Fund)

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on Machine Learning

Clinical Trials on No Intervention: Observational Cohort

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