Use of Artificial Intelligence on Imaging and Preoperatory Planning of the Knee Joint: A Scoping Review.

Abstract

Background and Objectives: This scoping review explores the current state of the art of AI-based applications in the field of orthopedics, focusing on its implementation in diagnostic imaging and preoperative planning of knee joint procedures. Materials and Methods: The search was carried out using the recognized scholarly databases PubMed, Medline and Embase and was set to identify original research addressing AI applied to imaging in knee diagnosis and surgical planning, written in English and published up to January 2025. Results: The search produced 1612 papers, of which 36 were included in our review. All papers addressed AI applied to common imaging methods in clinical practice. Of these, thirty integrated AI-based tools with X-rays, one applied AI to X-rays to produce CT-like 3D reproductions, and two studies applied AI to MRI. Conclusions: Several AI tools have already been validated for enhancing the accuracy of measurements and detecting additional parameters in a shorter time compared to standard assessments. We expect these may soon be introduced into routine clinical practice to streamline a number of technical tasks and in some cases to replace the need for human intervention.