MODELING OF PATELLA HEIGHT WITH DISTAL FEMUR AND PROXIMAL TIBIA REFERENCE POINTS WITH ARTIFICIAL NEURAL NETWORK

Abstract

The patellofemoral joint is one of the parts of the knee extension mechanism that plays a role in the stability of the knee by enlarging the force arm of the quadriceps muscle and changing the direction of the muscle strength. For the entire knee joint to perform its task painlessly and functionally, the positions and strength of the muscles, the strength of the ligaments, and their reaction to movement must be compatible. The Insall–Salvati (Ins-Sal) index is useful for showing changes in patellar height produced by repositioning the tibial plateau, in other words, showing changes in patellar tendon length. Patella height is an important value to be taken into account in knee prosthesis surgery, tibial osteotomy, and anterior cruciate ligament reconstruction. The morphometric relationship between the reference measurements of the distal femur and proximal tibia and the position of the patella will be useful in determining the natural anatomy. In this study, we aimed to determine the relationship between patella height and distal femur and proximal tibia reference areas by using the arti¯cial neural network method as an alternative approach method. In order to assess the performance of the estimation of the InsSal index, the four ANN model with six input combinations which included age, gender and the reference measurements for the right and left sides have been constructed and tested. The MSE and r values are calculated for every four models for the training and test phase. The results show that the proposed approach for modeling of relation between reference measurements and the Ins-Sal index is a powerful approach.