ALGORITHM FOR INFRARED-BASED IMAGELESS NAVIGATION IN UNICONDYLAR KNEE ARTHROPLASTY: A CADAVERIC STUDY

Abstract

Unicondylar knee arthroplasty (UKA) is a minimally invasive surgical procedure designed to treat osteoarthritis affecting a single condyle of the knee. Unlike total knee arthroplasty (TKA), which replaces all knee joint components, UKA preserves healthy structures, leading to faster recovery, reduced blood loss, and lower surgical morbidity. Imageless navigation systems have been introduced to enhance precision while minimizing invasiveness. These systems typically utilize infrared cameras and tracking software to determine the three-dimensional (3D) positions of anatomical landmarks required for surgical planning. This study presents an advanced algorithm for imageless UKA navigation that calculates varus angle and optimal bone resection depths for both the distal femur and proximal tibia. Additionally, it determines the hip-knee-ankle (HKA) and flexion angles for improved surgical accuracy. Initial validation was performed in a virtual simulation using a CT-based bone model in SolidWorks. Further validation involved experimental trials on SoftBone models, comparing conventional alignment techniques with the proposed algorithm. Finally, a cadaveric study was conducted under the supervision of an orthopaedic surgeon. The results demonstrated a resection error margin of approximately 1 mm for both femur and tibia, using an infrared camera with +/- 0.5 mm accuracy. Future improvements in camera resolution may further enhance the system's precision.