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NCT06373029

Deep-learning Enabled Ultrasound Diagnosis of Anterior Talofibular Ligament Injury

Sponsor: Peking University People's Hospital

View on ClinicalTrials.gov

Summary

Ultrasound (US) is a more cost-effective, accessible, and available imaging technique to assess anterior talofibular ligament (ATFL) injuries compared with magnetic resonance imaging (MRI). However, challenges in using this technique and increasing demand on qualified musculoskeletal (MSK) radiologists delay the diagnosis. The investigators have already developed a deep convolutional network (DCNN) model that automates detailed classification of ATFL injuries. The investigators hope to use the DCNN in real-world clinical setting to test its diagnostic accuracy.

Official title: Deep Learning-enabled Ultrasound Classification of Anterior Talofibular Ligament Injury in China: A Prospective, Multicentre, Diagnostic Study

Key Details

Gender

All

Age Range

18 Years - 80 Years

Study Type

OBSERVATIONAL

Enrollment

400

Start Date

2024-04-20

Completion Date

2025-12-30

Last Updated

2024-04-18

Healthy Volunteers

Not specified

Interventions

OTHER

Ultrasound examination

The investigators made ultrasound examinations to the participants to test whether the model could improve their diagnostic accuracy

Locations (1)

Peking University People's Hospital

Beijing, Beijing Municipality, China