Using artificial neural networks to predict impingement and dislocation in total hip arthroplasty

Abstract

Dislocation after total hip arthroplasty (THA) remains a major issue and an important postsurgical complication. Impingement and subsequent dislocation are influenced by the design (head size) and position (anteversion and abduction angles) of the acetabulum and different movements of the patient, with external extension and internal f lexion the most critical movements. The aim of this study is to develop a computational tool based on a three-dimensional (3D) parametric finite element (FE) model and an artificial neural network (ANN) to assist clinicians in identifying the optimal prosthesis design and position of the acetabular cup to reduce the probability of impingement and dislocation. A 3D parametric model of a THA was used. The model parameters were the f emoral head size and the acetabulum abduction and anteversion angles. Simulations run with this parametric model were used to train an ANN, which predicts the range of movement (ROM) before impingement and dislocation. This study recreates different configurations and obtains absolute errors lower than 5.5º between the ROM obtained from the FE simulations and the ANN predictions. The ROM is also predicted for patients who had already suffered dislocation after THA, and the computational predictions confirm the patient's dislocations.Summarizing, the combination of a 3D parametric FE model of a THA and an ANN is a useful computational tool to predict the ROM allowed for different designs of prosthesis heads.

A Machine-Learning-Based Approach for Predicting Mechanical Performance of Semi-Porous Hip Stems

“…Villamor et al [ 28 ] made comparisons between Support Vector Machine (SVM), Logistic Regression, Shallow Neural Networks, and Random Forest ML methods to determine the best-performing model to predict osteoporotic hip fracture in postmenopausal women based on FE analyses. Alastruey-López et al [ 29 ] used Artificial Neural Networks (ANN) and a parametric FE simulation to predict impingement and dislocation in total hip arthroplasty. Their efforts were aimed at identifying the optimal prosthesis design to reduce the probability of dislocation.…”

Moving fluoroscopy-based analysis of THA kinematics during unrestricted activities of daily living

“…Impingement, and a corresponding increased risk of joint subluxation, is a further potential cause of implant failure heavily influenced by joint kinematics. Geometry based models, or 3D parametric finite element models, of the implant and bone have been used to evaluate the impingement-free range of motion (ROM) of THA ( Alastruey-Lopez et al, 2020 ; Pryce et al, 2022 ). Such simulations have provided ROM-to-impingement curves for challenging high flexion and pivot activities ( McCarthy et al, 2021 ).…”

Functional safe zone for THA considering the patient‐specific pelvic tilts: An ultrasound‐based approach

“…In order to personalise the positioning of implants regarding both the patient's anatomy and pelvic kinematics, several authors have proposed biomechanical models or finite element studies, based on Computerised Tomography (CT) and X‐ray images 16–19 . Nonetheless, all these methods require a significant amount of computation and engineering work for modelling and simulations, and are not therefore easy to integrate in the clinical routine.…”

“…15 In order to personalise the positioning of implants regarding both the patient's anatomy and pelvic kinematics, several authors have proposed biomechanical models or finite element studies, based on Computerised Tomography (CT) and X-ray images. [16][17][18][19] Nonetheless,…”