Posters
Presenting Author Academic/Professional Position
Medical Student
Academic Level (Author 1)
Medical Student
Academic Level (Author 2)
Medical Student
Academic Level (Author 3)
Medical Student
Academic Level (Author 4)
Medical Student
Academic Level (Author 5)
Medical Student
Presentation Type
Poster
Discipline Track
Clinical Science
Abstract Type
Research/Clinical
Abstract
Background: High tibial osteotomy (HTO) is a surgical procedure which helps in managing lower limb deformities, provides pain relief, and arrests the progression of osteoarthritis of the knee joint. This surgical method involves cutting and realignment of the tibia and this is only as effective as the accuracy with which the tibia is cut and realigned and this success is based on the understanding of the biomechanics and the anatomical characteristics of the patient. Artificial Intelligence (AI) is becoming more widespread in the field of orthopaedic surgery, with applications in diagnostics, pre-operative planning, and predictive models of outcomes following procedures. Despite the advances of AI in the field, studies have been controversial in demonstrating improved outcomes associated with the incorporation of AI in the clinical field. A recent review concluded that AI-based tools improved the surgical aspects of total knee arthroplasty. The current study seeks to investigate the impact and effect of AI on tibial osteotomies with a systematic review of the existing literature.
Methods: This systematic review was conducted in accordance with the preferred reporting items for systematic reviews and meta-analyses (PRISMA). The initial search was conducted in September 2024. Three databases were utilized: PubMed and Web of Science using the Boolean operators - (tibial osteotomy) AND (AI OR machine learning OR artificial intelligence OR deep learning). Eligibility criteria focused on the relevance of AI in use with tibial osteotomy procedures.
Results: The initial search identified 94 articles, of which 15 met eligibility criteria for the study. Primary outcomes were sorted into three groups depending on the timeline in the surgical process in which AI was utilized: pre-procedural, peri-procedural, and post-procedural. AI demonstrated helpful usages across all stages of high tibial osteotomy (HTO) procedures. Preoperative applications included machine learning models that achieved AUCs as high as 0.992 for predicting complications like lateral hinge fractures. Tools like OsteoAid offered simultaneous calculation of correction angles, which decreased calculation time pre-procedurally. Postoperatively, AI-based analyses showed no significant differences from manual measurements, with reliability exceeding 95%; however, AI had significantly faster processing times.
Conclusion: AI potentially offers significant improvements in the precision, efficiency, and outcomes of tibial osteotomy procedures in different timelines of the procedure. These improvements could have further impacts on preoperative planning, surgical decisions optimization, and postoperative complication reduction, all factors that can transform clinical practice and improve patient outcomes.
Recommended Citation
Khalil, Mohammad; Rakay, David; Karkoutly, Mohammad Y.; Ayas, Zayd; and Karkoutly, Omar, "The Effect of Artificial Intelligence on High Tibial Osteotomies" (2025). Research Symposium. 114.
https://scholarworks.utrgv.edu/somrs/2025/posters/114
Included in
The Effect of Artificial Intelligence on High Tibial Osteotomies
Background: High tibial osteotomy (HTO) is a surgical procedure which helps in managing lower limb deformities, provides pain relief, and arrests the progression of osteoarthritis of the knee joint. This surgical method involves cutting and realignment of the tibia and this is only as effective as the accuracy with which the tibia is cut and realigned and this success is based on the understanding of the biomechanics and the anatomical characteristics of the patient. Artificial Intelligence (AI) is becoming more widespread in the field of orthopaedic surgery, with applications in diagnostics, pre-operative planning, and predictive models of outcomes following procedures. Despite the advances of AI in the field, studies have been controversial in demonstrating improved outcomes associated with the incorporation of AI in the clinical field. A recent review concluded that AI-based tools improved the surgical aspects of total knee arthroplasty. The current study seeks to investigate the impact and effect of AI on tibial osteotomies with a systematic review of the existing literature.
Methods: This systematic review was conducted in accordance with the preferred reporting items for systematic reviews and meta-analyses (PRISMA). The initial search was conducted in September 2024. Three databases were utilized: PubMed and Web of Science using the Boolean operators - (tibial osteotomy) AND (AI OR machine learning OR artificial intelligence OR deep learning). Eligibility criteria focused on the relevance of AI in use with tibial osteotomy procedures.
Results: The initial search identified 94 articles, of which 15 met eligibility criteria for the study. Primary outcomes were sorted into three groups depending on the timeline in the surgical process in which AI was utilized: pre-procedural, peri-procedural, and post-procedural. AI demonstrated helpful usages across all stages of high tibial osteotomy (HTO) procedures. Preoperative applications included machine learning models that achieved AUCs as high as 0.992 for predicting complications like lateral hinge fractures. Tools like OsteoAid offered simultaneous calculation of correction angles, which decreased calculation time pre-procedurally. Postoperatively, AI-based analyses showed no significant differences from manual measurements, with reliability exceeding 95%; however, AI had significantly faster processing times.
Conclusion: AI potentially offers significant improvements in the precision, efficiency, and outcomes of tibial osteotomy procedures in different timelines of the procedure. These improvements could have further impacts on preoperative planning, surgical decisions optimization, and postoperative complication reduction, all factors that can transform clinical practice and improve patient outcomes.
