Does AI input improve efficiency of 3D planning of knee replacement

  • Research type

    Research Study

  • Full title

    Does AI input improve efficiency of 3 D planning during knee replacement

  • IRAS ID

    278260

  • Contact name

    Muthu Ganapathi

  • Contact email

    muthu.ganapathi@wales.nhs.uk

  • Sponsor organisation

    Betsi Cadwaladr University Health Board

  • Duration of Study in the UK

    0 years, 0 months, 16 days

  • Research summary

    Patient Specific Instrumentation (PSI) is a technique used to perform knee replacements. MRI scan of the patient's knee is used to create 3 D model of the patients knee which is used to pre-plan the bone cuts, sizing and placement of the implants. The surgeon is provided a default plan initially (default plan) which the surgeon can modify before final approval. This approval process takes time if a number of changes are needed. We are analysing whether artificial intelligence (AI) could replicate the surgeon's preference at the default planning stage so that the surgeon will need to make lesser number of changes and thus decreasing the time taken to approve the plan. The anonymised 3 D images of previous patient's images with the surgeon's approved final plan will be used to educate AI. Subsequently, AI input will be used at the stage of default plan to see if the surgeon needs to make lesser number of changes and thus making the approval process more efficient. The surgeon will also be provided randomly different plans to rank them on the acceptability of the plan.

  • REC name

    N/A

  • REC reference

    N/A