American journal of translational research · 2026
Diagnostic performance of multimodal imaging integrating X-ray, CT, and MRI in femoroacetabular impingement syndrome.
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Liu Qitong, Zhang Weiguo, Mu Yu
Аннотация
OBJECTIVE: To evaluate the diagnostic performance of combined X-ray, computed tomography (CT), and magnetic resonance imaging (MRI) for femoroacetabular impingement (FAI) syndrome and its subtypes, and to explore potential factors associated with FAI.
METHODS: A total of 86 patients with FAI syndrome (FAI group) and 70 individuals without hip joint abnormalities (control group) were retrospectively enrolled. All participants underwent X-ray, CT, and MRI examinations. The imaging findings were collected and analyzed. The diagnostic performance of each modality and their combination for FAI syndrome was analyzed using the receiver operating characteristic (ROC) curve analysis. Subsequently, independent risk factors were identified, and a nomogram prediction model was built and validated.
RESULTS: The area under the ROC curve (AUC) for diagnosing FAI syndrome using X-ray, CT, and MRI was 0.792, 0.845, and 0.889, respectively, whereas the combined diagnostic model achieved an AUC of 0.932 (specificity: 90.70%, sensitivity: 95.71%, accuracy: 92.95%). Multivariate analysis further identified age, high-intensity exercise history (Hx_HIE), α angle, and center-edge (CE) angle as independent risk factors for FAI syndrome, while femoral offset played a protective role. The constructed nomogram demonstrated excellent predictive performance, with a C-index of 0.966 and high calibration accuracy, particularly in the high-risk range.
CONCLUSION: The joint screening using X-ray, CT, and MRI can significantly improve the diagnostic accuracy for FAI syndrome. Age ≥32 years, a history of high-intensity exercise, increased α/CE angles, and decreased femoral offset are associated with a higher risk of developing FAI syndrome.
METHODS: A total of 86 patients with FAI syndrome (FAI group) and 70 individuals without hip joint abnormalities (control group) were retrospectively enrolled. All participants underwent X-ray, CT, and MRI examinations. The imaging findings were collected and analyzed. The diagnostic performance of each modality and their combination for FAI syndrome was analyzed using the receiver operating characteristic (ROC) curve analysis. Subsequently, independent risk factors were identified, and a nomogram prediction model was built and validated.
RESULTS: The area under the ROC curve (AUC) for diagnosing FAI syndrome using X-ray, CT, and MRI was 0.792, 0.845, and 0.889, respectively, whereas the combined diagnostic model achieved an AUC of 0.932 (specificity: 90.70%, sensitivity: 95.71%, accuracy: 92.95%). Multivariate analysis further identified age, high-intensity exercise history (Hx_HIE), α angle, and center-edge (CE) angle as independent risk factors for FAI syndrome, while femoral offset played a protective role. The constructed nomogram demonstrated excellent predictive performance, with a C-index of 0.966 and high calibration accuracy, particularly in the high-risk range.
CONCLUSION: The joint screening using X-ray, CT, and MRI can significantly improve the diagnostic accuracy for FAI syndrome. Age ≥32 years, a history of high-intensity exercise, increased α/CE angles, and decreased femoral offset are associated with a higher risk of developing FAI syndrome.