The goal of this observational study is to learn whether an artificial-intelligence software can reliably recognise the anatomical landmarks used to guide femoral bone tunnel placement on the arthroscopic monitor image during anterior cruciate ligament (ACL) reconstruction in adults. The main questions it aims to answer are: Can the software automatically tell when the arthroscopic image is clean enough to allow identification of these landmarks? Can the software accurately outline the key bony and cartilaginous landmarks on the femur that guide correct tunnel positioning? Participants will undergo their clinically indicated ACL reconstruction without modifications: short video sequences of the operative field will be recorded from the arthroscopic camera already used in routine practice, and used to train and validate the algorithms. No additional devices, manoeuvres or operative time are required.
Age range
18 Years
Sex
ALL
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Area Under the Receiver Operating Characteristic Curve (AUC-ROC) of the binary classification of arthroscopic field cleanliness
Timeframe: Through study completion, an average of 12 months