Systematic review of artificial intelligence tack in preventive orthopaedics: is the land coming soon?

PURPOSE: This study aims to describe and assess the current stage of the artificial intelligence (AI) technology integration in preventive orthopaedics of the knee and hip joints. MATERIALS AND METHODS: The study was conducted in strict compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. Literature databases were searched for articles describing the development and validation of AI models aimed at diagnosing knee or hip joint pathologies or predicting their development or course in patients. The quality of the included articles was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and QUADAS-AI tools. RESULTS: 56 articles were found that meet all the inclusion criteria. We identified two problems that block the full integration of AI into the routine of an orthopaedic physician. The first of them is related to the insufficient amount, variety and quality of data for training, and validation and testing of AI models. The second problem is the rarity of rational evaluation of models, which is why their real quality cannot always be evaluated. CONCLUSION: The vastness and relevance of the studied topic are beyond doubt. Qualitative and optimally validated models exist in all four scopes considered. Additional optimization and confirmation of the models' quality on various datasets are the last technical stumbling blocks for creating usable software and integrating them into the routine of an orthopaedic physician.

Automated personalization of biomechanical knee model.

PURPOSE: Patient-specific biomechanical models of the knee joint can effectively aid in understanding the reasons for pathologies and improve diagnostic methods and treatment procedures. For deeper research of knee diseases, the development of biomechanical models with appropriate configurations is essential. In this study, we mainly focus on the development of a personalized biomechanical model for the investigation of knee joint pathologies related to patellar motion using automated methods. METHODS: This study presents a biomechanical model created for patellar motion pathologies research and some techniques for automating the generation of the biomechanical model. To generate geometric models of bones, the U-Net neural network was adapted for 3D input datasets. The method uses the same neural network for segmentation of femur, tibia, patella and fibula. The total size of the train/validation (75/25%) dataset is 18,183 3D volumes of size 512 × 512 × 4 voxels. The configuration of the biomechanical knee model proposed in the paper includes six degrees of freedom for the tibiofemoral and patellofemoral joints, lateral and medial contact surfaces for femur and tibia, and ligaments, representing, among other things, the medial and lateral stabilizers of the knee cap. The development of the personalized biomechanical model was carried out using the OpenSim software system. The automated model generation was implemented using OpenSim Python scripting commands. RESULTS: The neural network for bones segmentation achieves mean DICE 0.9838. A biomechanical model for realistic simulation of patellar movement within the trochlear groove was proposed. Generation of personalized biomechanical models was automated. CONCLUSIONS: In this paper, we have implemented a neural network for the segmentation of 3D CT scans of the knee joint to produce a biomechanical model for the study of knee cap motion pathologies. Most stages of the generation process have been automated and can be used to generate patient-specific models.

Short-Term Outcomes of Total Knee Arthroplasty Using a Conventional, Computer-Assisted, and Robotic Technique: A Pilot Clinical Trial.

Background: Total Knee Arthroplasty (TKA) is a prevalent surgical procedure for treating severe knee arthritis, aiming to alleviate pain and restore function. Recent advancements have introduced computer-assisted (CAS) and robot-assisted (RA-TKA) surgical techniques as alternatives to conventional methods, promising improved accuracy and patient outcomes. However, comprehensive comparative studies evaluating the short-term outcomes and prostheses survivorship among these techniques are limited. We hypothesized that the outcome of RA-TKA and/or CAS- TKA is advantageous in function and prosthesis survivorship compared to manually implanted prostheses. Methods: This prospective controlled study compared the short-term outcomes and prostheses survivorship following TKA using conventional, CAS, and RA-TKA techniques. One hundred seventy-eight patients requiring TKA were randomly assigned to one of the three surgical groups. The primary outcomes were knee function (KSS knee score) and functional recovery (KSS function score), which were assessed before surgery three years postoperatively. Secondary outcomes included prosthesis alignment, knee range of movements, and complication rates. Survivorship analysis was conducted using Kaplan-Meier curves, with revision surgery as the endpoint. Results: While all three groups showed significant improvements in knee function postoperatively (p < 0.001), the CAS and RA-TKA groups demonstrated superior prosthetic alignment and higher survivorship rates than the conventional group (100%, 97%, and 96%, respectively). However, although the RA-TKA group had a maximal 100% survivorship rate, its knee score was significantly lower than following CAS and conventional techniques (mean 91 ± 3SD vs. mean 93 ± 3SD, p = 0.011). Conclusion: The RA-TKA technique offers advantages over conventional and CAS methods regarding alignment accuracy and short-term survivorship of TKA prostheses. Since short-term prosthesis survivorship indicates the foreseen rates of mid- and long-term survivorship, the current data have a promising indication of the improved TKA prosthesis's long-term survivorship by implementing RA-TKA. According to the presented data, although the survival rates were 100%, 97%, and 96% in the three study groups, no clinical difference in the functional outcome was found despite the better mechanical alignment and higher survivorship in the group of patients treated by the RA-TKA.