Augmented Reality in Surgery
Recruiting now
Conditions studied: Anterior Cruciate Ligament (ACL) Tear
In brief
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.
Key facts
- Study ID
- NCT07636278
- Run by
- I.R.C.C.S Ospedale Galeazzi-Sant'Ambrogio
- People needed
- 100
- Starts
- 2026-05-26
- Expected to finish
- 2027-05-31
- Last updated by the study team
- 2026-06-09
Who can join
Age: 18 and older. Sex: any. Healthy volunteers: not accepted.
You may qualify if…
- Age 18 years or older
- Scheduled for primary arthroscopic anterior cruciate ligament reconstruction at IRCCS Galeazzi-Sant'Ambrogio
- Signed written informed consent
You may not qualify if…
- Revision anterior cruciate ligament reconstruction
- Arthroscopic video quality judged inadequate by the investigator (artefacts, insufficient illumination, uninterpretable images)
- Failure to sign informed consent, or withdrawal of consent
Where it is running
- IRCCS Ospedale Galeazzi-Sant'Ambrogio — Milan, Michigan, Italy (enrolling)
Full record on ClinicalTrials.gov
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