FindTrial
Sign In

Clinical Study of Deep Learning-Based MR DIT Technique in Predicting Return-to-Sport Outcomes in Patients with Anterior Talofibular Ligament Injury

Clinical Study of Deep Learning-Based MR DIT Technique in Predicting Return-to-Sport Outcomes in Patients with Anterior Talofibular Ligament Injury

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600123292
Enrollment
Unknown
Registered
2026-04-23
Start date
2026-05-01
Completion date
Unknown
Last updated
2026-04-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Anterior Talofibular Ligament Injury

Interventions

ATFL Injury Cohort:No

Sponsors

The First People's Hospital of Shaoguan
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 50 Years

Inclusion criteria

Inclusion criteria: 1. Clinically and via routine MRI confirmed ATFL injury; 2. Age 18-50 years; 3. Signed informed consent.

Exclusion criteria

Exclusion criteria: Excluding those with combined ankle fractures, nerve injuries, or severe underlying diseases.

Design outcomes

Primary

MeasureTime frame
Return-to-sport success rate in patients with ATFL injury;Accuracy;Sensitivity;Specificity;—

Countries

China

Contacts

Public ContactPenghuan Wu

The First People's Hospital of Shaoguan

wupenghuan888@126.com+86 751 887 1280

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: May 1, 2026