Current Trends in Artificial Intelligence-Assisted Spine Surgery: A Systematic Review

Liawrungrueang, Wongthawat; Cho, Sung Tan; Sarasombath, Peem; Kim, Inhee; Kim, Jin Hwan

doi:10.31616/asj.2023.0410

Cited by 5 publications

(1 citation statement)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In a recent systematic review, Liawrungrueang et al [ 101 ] observed that AI and its integration with augmented reality (AR) and virtual reality (VR) appears promising for improving overall surgical safety. They also stated that VR surgical simulators create a secure environment for targeted surgical scenarios and foster self-guided learning.…”

Section: Resultsmentioning

confidence: 99%

Artificial intelligence: a new cutting-edge tool in spine surgery

Kalanjiyam,

Chandramohan,

Raman

et al. 2024

Asian Spine J

View full text Add to dashboard Cite

The purpose of this narrative review was to comprehensively elaborate the various components of artificial intelligence (AI), their applications in spine surgery, practical concerns, and future directions. Over the years, spine surgery has been continuously transformed in various aspects, including diagnostic strategies, surgical approaches, procedures, and instrumentation, to provide better-quality patient care. Surgeons have also augmented their surgical expertise with rapidly growing technological advancements. AI is an advancing field that has the potential to revolutionize many aspects of spine surgery. We performed a comprehensive narrative review of the various aspects of AI and machine learning in spine surgery. To elaborate on the current role of AI in spine surgery, a review of the literature was performed using PubMed and Google Scholar databases for articles published in English in the last 20 years. The initial search using the keywords “artificial intelligence” AND “spine,” “machine learning” AND “spine,” and “deep learning” AND “spine” extracted a total of 78, 60, and 37 articles and 11,500, 4,610, and 2,270 articles on PubMed and Google Scholar. After the initial screening and exclusion of unrelated articles, duplicates, and non-English articles, 405 articles were identified. After the second stage of screening, 93 articles were included in the review. Studies have shown that AI can be used to analyze patient data and provide personalized treatment recommendations in spine care. It also provides valuable insights for planning surgeries and assisting with precise surgical maneuvers and decisionmaking during the procedures. As more data become available and with further advancements, AI is likely to improve patient outcomes.

show abstract

Section: Resultsmentioning

confidence: 99%

Artificial intelligence: a new cutting-edge tool in spine surgery

Kalanjiyam,

Chandramohan,

Raman

et al. 2024

Asian Spine J

View full text Add to dashboard Cite

show abstract

Artificial Intelligence-Assisted MRI Diagnosis in Lumbar Degenerative Disc Disease: A Systematic Review

Liawrungrueang,

Park,

Cholamjiak

et al. 2024

Global Spine Journal

View full text Add to dashboard Cite

Study Design Systematic review. Objectives Lumbar degenerative disc disease (DDD) poses a significant global health care challenge, with accurate diagnosis being difficult using conventional methods. Artificial intelligence (AI), particularly machine learning and deep learning, offers promising tools for improving diagnostic accuracy and workflow in lumbar DDD. This study aims to review AI-assisted magnetic resonance imaging (MRI) diagnosis in lumbar DDD and discuss current research for clinical use. Methods A systematic search of electronic databases identified studies on AI applications in MRI-based lumbar DDD diagnosis, following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Search terms included combinations of “Artificial Intelligence,” “Machine Learning,” “Deep Learning,” “Low Back Pain,” “Lumbar,” “Disc,” “Degeneration,” and “MRI,” targeting studies in English from January 1, 2010, to January 1, 2024. Inclusion criteria encompassed experimental and observational studies in peer-reviewed journals. Data extraction focused on study characteristics, AI techniques, performance metrics, and diagnostic outcomes, with quality assessed using predefined criteria. Results Twenty studies met the inclusion criteria, employing various AI methodologies, including machine learning and deep learning, to diagnose lumbar DDD manifestations such as disc degeneration, herniation, and bulging. AI models consistently outperformed conventional methods in accuracy, sensitivity, and specificity, with performance metrics ranging from 71.5% to 99% across different diagnostic objectives. Conclusion The algorithm model provides a structured framework for integrating AI into routine clinical practice, enhancing diagnostic precision and patient outcomes in lumbar DDD management. Further research and validation are needed to refine AI algorithms for real-world application in lumbar DDD diagnosis.

show abstract

Commentary on “The Utility and Feasibility of Smart Glasses in Spine Surgery: Minimizing Radiation Exposure During Percutaneous Pedicle Screw Insertion”

Liawrungrueang

2024

Neurospine

View full text Add to dashboard Cite

Scientific knowledge used to medicine to aid in diagnosis, prevention, treatment, and innovation is referred to as medical technology. It does this by creating tools, machines, and pharmaceuticals using engineering and biotechnology methods. 1,2 The manufacturing of equipment and techniques utilized in the medical field such as augmented reality (AR)-assisted real-time visualization of spine surgery, neuromonitoring systems, robotics-assisted surgery, robotic-assisted pedicle screw placement, and intraoperative navigation systems is specifically referred to when discussing spinal medical technology. 1,[3][4][5] Augmented and mixed-reality technologies are included in smart glasses (SG) for spine surgery, giving surgeons access to real-time imaging, guidance, and patient information. 6,7 With the use of these glasses, the surgeon may plan and navigate surgery more efficiently by the image on the wearable displays are closer than those on a fluoroscopic monitor, allowing for a clearer view and reducing radiation exposure during percutaneous pedicle screw (PPS) insertion. 7,8 This study 9 examines the potential and usefulness of SG in spine surgery. Adoption of SG offers a possible way to reduce related health concerns, since radiation exposure to spine surgeons during fluoroscopy-guided treatments increases. The MOVERIO SG manufactured by Epson Co., Ltd. (Tokyo, Japan) are a series of wearable AR devices designed for various applications. The latest MOVERIO smart glass delivers an engaging AR experience through quality QHD (quad high definition) or 3-dimensional (3D) images. Its binocular and lightweight see-through display also keeps you aware of your surroundings while you are viewing your content. The objective of the research, which employed operators with varying degrees of experience, was to assess how much SG reduced radiation exposure and increased procedural accuracy. Operators alternated between SG and traditional approaches to direct the insertion of PPS into lumbar model bones under fluoroscopic supervision, using the MOVERIO SG model BT-30E and the COREVISION 3D fluoroscopy system. The SG and non-SG groups' insertion times did not differ significantly, according to the data. However, especially for less experienced operators, the use of SG considerably decreased the duration and amount of radiation exposure. Additionally, deviation studies showed that SG did not impair the precision of screw insertion.The introduction of SG addressed critical concerns regarding radiation exposure in spine Neurospine

show abstract

Current Trends in Artificial Intelligence-Assisted Spine Surgery: A Systematic Review

Cited by 5 publications

References 54 publications

Artificial intelligence: a new cutting-edge tool in spine surgery

Artificial intelligence: a new cutting-edge tool in spine surgery

Artificial Intelligence-Assisted MRI Diagnosis in Lumbar Degenerative Disc Disease: A Systematic Review

Commentary on “The Utility and Feasibility of Smart Glasses in Spine Surgery: Minimizing Radiation Exposure During Percutaneous Pedicle Screw Insertion”

Contact Info

Product

Resources

About