How AI Will Change the Way We Do Pre-Surgical Planning: A Study of Total Knee Arthroplasty

About this webinar

Recently, we have begun to see the first successful applications of AI in healthcare that aid physicians with their daily tasks. Currently, AI has surpassed expert radiologists in detecting breast tumors in mammography scans and eye diseases from optical topography scans (Fauw et al., 2018; McKinney et al., 2020). However, the field of orthopaedics has been lagging in AI adoption.

In this context, we started research to learn how AI can help orthopaedic surgeons in their daily practice, starting with the most commonly performed procedure: total knee arthroplasty (TKA). Consequently, we created an algorithm that learns from the surgeon’s previously planned cases. Our goal with this study was to evaluate if the AI model is indeed capable of proposing improved preoperative plans compared to the current defaults.

What you will learn

  • The basics of preoperative planning for total knee arthroplasty (TKA)
  • Variations and challenges in preoperative planning
  • Major clinical takeaways from the study
  • How AI can help to improve preoperative planning
  • Other areas of exploration that this study will include as it evolves


Adriaan Lambrechts

Research Engineer, Materialise

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Close-up view of an organic, porous structure

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