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Updated: May 14, 2026

Automated Joint Space Detection Improves Bone Segmentation Accuracy
Published on: November 28, 2025
Asymptomatic Abnormalities in the Knee, Shoulder, and Ankle Joints of Collegiate Athletes: A Cross-Sectional
Na Jiang1, Hanqi Wang1, Xinyu Zhang2
1Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Abstract:
Background: Asymptomatic structural joint abnormalities are prevalent among athletes, yet studies on their multi-joint distribution and comparisons with low-activity controls remain lacking. This article evaluated the prevalence and characteristics of asymptomatic structural abnormalities across joints in collegiate athletes compared with controls using 3.0-T MRI. Methods: The cross-sectional study enrolled 53 asymptomatic elite collegiate athletes (high physical activity, HPA) and 84 healthy volunteers (low physical activity, LPA) aged 18-25 years. All participants were asymptomatic with no history of joint trauma or surgery. Generalized estimating equation (GEE) logistic regression was employed to identify independent risk factors for joint abnormalities after evaluation. Results: A total of 666 joints were analyzed. Participants with at least one joint abnormality were significantly more common in the HPA group than LPA group (49.1% vs. 6.0%, p < 0.001). At the joint level, overall abnormality prevalence was 13.5% versus 2.2%, respectively. In the HPA group, knee joints were the most frequently affected (24.2%), predominantly involving meniscal lesions. Shoulder pathologies consisted exclusively of supraspinatus tendon lesions (6.8%), while ankle abnormalities were primarily bone marrow edema (5.9%). GEE analysis identified high physical activity (adjusted OR = 5.23; 95% CI: 1.55-17.71; p = 0.008) and elevated BMI (adjusted OR = 1.09 per kg/m2; 95% CI: 1.03-1.15; p = 0.001) as independent risk factors. Conclusions: Asymptomatic abnormalities are highly prevalent and demonstrate intra-individual clustering across multiple joints. MRI-based surveillance represents a promising strategy for early risk identification and injury prevention.
