Background
Identifying and reducing the risk of chronic ankle instability (CAI) is crucial for patients selecting appropriate treatment modalities. However, there is limited research on the factors contributing to CAI. This study aims to provide a comprehensive assessment of CAI risk factors, including demographics, bone structure, and ligament characteristics, to identify those most closely associated with the condition.
Methods
This retrospective study included patients with CAI who underwent MRI following acute ankle sprains between January 2018 and June 2023. Demographic and clinical data were collected through the 24-month follow-up or electronic medical records. The imaging parameters were measured using the DICOM/PACS system and included the Axial Malleolar Index (AMI), Intermalleolar Index (IMI), Malleolar Talus Index (MTI), external rotation angle of the fibula, retromalleolar groove, signal to noise ratio (SNR), length, cross-sectional area (CSA), width of the anterior talofibular ligament (ATFL), and ATFL-posterior talofibular ligament (PTFL) angle. Logistic regression analysis and Receiver Operating Characteristic (ROC) curve analysis were performed to identify CAI risk factors and assess diagnostic accuracy.
Results
A total of 131 patients with CAI were evaluated, including 78 women and 33 men. Univariate logistic regression analysis revealed that the 6 risk factors associated with CAI included height (odds ratio (OR) 1.09, 95% CI 0.56–6.26, P < 0.05), ATFL-PTFL angle (OR, 1.12, 95%CI, 1.07–1.17, P < 0.001), IMI (OR, 1.15, 95%CI, 1.04–1.27, P < 0.05), the external rotation angle of the fibula (OR, 0.81, 95%CI, 0.72–0.90, P < 0.001), the SNR of ATFL(OR, 1.10, 95%CI, 1.00-1.21, P < 0.05), the retromalleolar groove (OR, 3.59, 95%CI, 1.49–8.63, P < 0.05). The ATFL-PTFL angle had the highest diagnostic performance for CAI, with an area under the ROC curve (AUC) of 0.77, a positive likelihood ratio of 5.84 (P < 0.001).
Conclusion
MRI can be a valuable tool for the detection of risk factors associated with CAI. Our findings will offer valuable insights for the diagnosis and treatment of CAI in clinical settings.