Magnetic resonance imaging of post traumatic knee: injury pattern analysis in sports activities

Amit Choubey, Rahul Dev Chauhan, Sourabh Kumar


Background: Musculoskeletal injuries of knee are commonly encountered in sportsmen during sports activities. Magnetic resonance imaging (MRI) is the modality of choice for evaluation of traumatic knee injuries and arthroscopic interventions. By knowing the pattern and burden of surgically significant injuries in sportsmen, the artificial intelligence (AI) software may be developed accordingly so that surgically significant injuries may be identified by the young radiologists.

Methods: It was a retrospective study on MRI for knee injuries in sportsmen. The digital data from Radiology department at a zonal level hospital was analysed. The MRI findings were correlated with the arthroscopic records available. For surgically insignificant injuries, the literature was referred for the typical MRI findings of the injuries.

Results: Of 272 cases of MRI knee, 74.3% cases were detected to have acute traumatic injuries. Among various types of injuries found in this study, anterior cruciate ligament (ACL) tear (55.9%) was the commonest injury followed by medial meniscal tear (40%). 40 (19.8%) cases were found to have surgically significant MRI findings which were subsequently corroborated with knee arthroscopy.

Conclusions: Since majority of soft tissue injuries of knee constitute ACL and meniscal tears, the industries involved in developing AI software for soft tissue injuries of knee, should primarily focus on identification of ACL and meniscal injuries. The AI software may also be helpful for the young radiologists in early training days in MRI for knee injuries and may also help in big scale research projects of post traumatic MRI knees.


Sportsmen, Knee injuries, MRI, AI

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