Deep-learning Enabled Ultrasound Diagnosis of Anterior Talofibular Ligament Injury

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

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.

Inclusion Criteria:

• age> 18 years old
• patients who underwent an acute ankle sprain
• patients with a surgery results of the sprained ankle

Exclusion Criteria:

• age< 18 years old
• patients with a previous history of ankle surgery
• patients with ankle tumors
• patients with a previous history of rheumatoid arthritis