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The Bone & Joint Journal
Vol. 101-B, Issue 12 | Pages 1479 - 1488
1 Dec 2019
Laverdière C Corban J Khoury J Ge SM Schupbach J Harvey EJ Reindl R Martineau PA

Aims. Computer-based applications are increasingly being used by orthopaedic surgeons in their clinical practice. With the integration of technology in surgery, augmented reality (AR) may become an important tool for surgeons in the future. By superimposing a digital image on a user’s view of the physical world, this technology shows great promise in orthopaedics. The aim of this review is to investigate the current and potential uses of AR in orthopaedics. Materials and Methods. A systematic review of the PubMed, MEDLINE, and Embase databases up to January 2019 using the keywords ‘orthopaedic’ OR ‘orthopedic AND augmented reality’ was performed by two independent reviewers. Results. A total of 41 publications were included after screening. Applications were divided by subspecialty: spine (n = 15), trauma (n = 16), arthroplasty (n = 3), oncology (n = 3), and sports (n = 4). Out of these, 12 were clinical in nature. AR-based technologies have a wide variety of applications, including direct visualization of radiological images by overlaying them on the patient and intraoperative guidance using preoperative plans projected onto real anatomy, enabling hands-free real-time access to operating room resources, and promoting telemedicine and education. Conclusion. There is an increasing interest in AR among orthopaedic surgeons. Although studies show similar or better outcomes with AR compared with traditional techniques, many challenges need to be addressed before this technology is ready for widespread use. Cite this article: Bone Joint J 2019;101-B:1479–1488


The Bone & Joint Journal
Vol. 106-B, Issue 11 | Pages 1216 - 1222
1 Nov 2024
Castagno S Gompels B Strangmark E Robertson-Waters E Birch M van der Schaar M McCaskie AW

Aims

Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of OA currently lack effective therapies to halt or reverse progression. Accurate prediction of OA progression is crucial if timely interventions are to be developed, to enhance patient care and optimize the design of clinical trials.

Methods

A systematic review was conducted in accordance with PRISMA guidelines. We searched MEDLINE and Embase on 5 May 2024 for studies utilizing ML to predict OA progression. Titles and abstracts were independently screened, followed by full-text reviews for studies that met the eligibility criteria. Key information was extracted and synthesized for analysis, including types of data (such as clinical, radiological, or biochemical), definitions of OA progression, ML algorithms, validation methods, and outcome measures.