Abstract
There are two surgical approaches to performing total hip arthroplasty (THA): a cemented or uncemented type of prosthesis. The choice is usually based on the experience of the orthopaedic surgeon and on parameters such as the age and gender of the patient. Using machine learning (ML) techniques on quantitative biomechanical and bone quality data extracted from computed tomography, electromyography and gait analysis, the aim of this paper was, firstly, to help clinicians use patient-specific biomarkers from diagnostic exams in the prosthetic decision-making process. The second aim was to evaluate patient long-term outcomes by predicting the bone mineral density (BMD) of the proximal and distal parts of the femur using advanced image processing analysis techniques and ML. The ML analyses were performed on diagnostic patient data extracted from a national database of 51 THA patients using the Knime analytics platform. The classification analysis achieved 93% accuracy in choosing the type of prosthesis; the regression analysis on the BMD data showed a coefficient of determination of about 0.6. The start and stop of the electromyographic signals were identified as the best predictors. This study shows a patient-specific approach could be helpful in the decision-making process and provide clinicians with information regarding the follow up of patients.
Highlights
Advanced arthroplasty and pain in hip joints have been extensively treated with total hip arthroplasty (THA)
THA surgical revision rates are increasing [53] and the effects of non-optimal prosthesis selections and fixation methods may dramatically affect patient mobility. These results demonstrate that patient-specific information such as gait parameters, bone mineral density (BMD), and fracture risk calculation during press fitting are important in assessing patient conditions pre-THA and determining an optimal surgical strategy
The question would be understandable, but this study aimed to investigate the feasibility of creating a new approach in this context: deciding the prosthesis of patients undergoing THA based on their quantitative data, following a patient-specific approach
Summary
Advanced arthroplasty and pain in hip joints have been extensively treated with total hip arthroplasty (THA). Hip replacement with a prosthesis has been among the most effective orthopedic surgeries for re-establishing function and lowering the pain of patients affected by various pathologies, osteoarthritis and osteonecrosis of the femoral head and neck fractures. In the case of an uncemented prosthesis, surgery is performed using a press fit, and the stratum of the bone directly neighboring the implant stem is preloaded and stimulated to grow [2]. Because the probability of the need for revision surgery increases with age, patients receiving an implant early in life have a higher probability of needing revision surgery, and the risk of intra-operative fracture under press fitting due to poor bone quality is lower in the population [10,11]
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