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Deep-learning Enabled Ultrasound Diagnosis of Anterior Talofibular Ligament Injury
Sponsor: Peking University People's Hospital
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
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