Machine vision augmented reality for pedicle screw insertion during spine surgery

Nguyen, Nhu; Priola, Stefano Maria; Ramjist, Joel; Guha, Daipayan; Dobashi, Yuta; Lee, Kenneth; Lu, Michael T.; Androutsos, Dimitrios; Yang, Victor X. D.

doi:10.1016/j.jocn.2019.12.067

Cited by 19 publications

(16 citation statements)

References 13 publications

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“…An additional unique feature of the 7D Surgical System is the option of using augmented reality (AR) to facilitate accuracy and safety. Nguyen et al demonstrated that AR software can be added to machine vision navigation to superimpose "safe" zones and trajectories through selected pedicles (25). When a navigated trajectory has been selected, a virtual line along that trajectory can be projected onto the system's video monitor and preserved during screw insertion (Figure 2).…”

Section: Machine Vision Navigation Technologymentioning

confidence: 99%

Machine Vision Navigation in Spine Surgery

Kalfas

2021

Front. Surg.

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The advancements in computing and digital localizer technologies has led to the evolving clinical application of image-guided technology for the surgical management of spinal disorders. Image-guided spinal navigation addresses the limitations of fluoroscopy and improves the accurate placement of fixation screws. Several navigation platforms are currently available, each having its own unique advantages and disadvantages. The most recent spinal navigation system developed utilizes machine vision structured light imaging which creates a precise and detailed three-dimensional image of the exposed surface anatomy and co-registers it to a pre-operatively or intra-operatively acquired image. This system improves upon the intraoperative workflow and efficiency of the navigation process. With the continued advancements in machine vision, there is a potential for clinical applications that extend beyond surgical navigation. These applications include reducing the potential for wrong level spine surgery and providing for real-time tracking of spinal deformity correction. As the adoption and clinical experience with navigation continues to expand and evolve, the technology that enables navigation also continues to evolve.

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Section: Machine Vision Navigation Technologymentioning

confidence: 99%

Machine Vision Navigation in Spine Surgery

Kalfas

2021

Front. Surg.

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“…The blue, red, pink, yellow, and green lines represent correct, medial, lateral, superior and inferior breaches, respectively. Reproduced with permission by Nguyen et al (69). mixed reality (69)(70)(71)(72).…”

Section: Future Perspectives On Machine Learning and Spine Surgerymentioning

confidence: 99%

“…Reproduced with permission by Nguyen et al (69). mixed reality (69)(70)(71)(72). Nguyen et al in a trial of augmented reality for pedicle screw insertion with navigation, designed a virtual road map that was superimposed on the surgical site of patients undergoing spinal fusion (69).…”

Section: Future Perspectives On Machine Learning and Spine Surgerymentioning

confidence: 99%

“…mixed reality (69)(70)(71)(72). Nguyen et al in a trial of augmented reality for pedicle screw insertion with navigation, designed a virtual road map that was superimposed on the surgical site of patients undergoing spinal fusion (69). Their intention was to address the underlying obstacle of surgeons memorizing optimal screw trajectory provided by navigation, which is typically displayed away from the surgical site.…”

Section: Future Perspectives On Machine Learning and Spine Surgerymentioning

confidence: 99%

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The Role of Machine Learning in Spine Surgery: The Future Is Now

et al. 2020

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The recent influx of machine learning centered investigations in the spine surgery literature has led to increased enthusiasm as to the prospect of using artificial intelligence to create clinical decision support tools, optimize postoperative outcomes, and improve technologies used in the operating room. However, the methodology underlying machine learning in spine research is often overlooked as the subject matter is quite novel and may be foreign to practicing spine surgeons. Improper application of machine learning is a significant bioethics challenge, given the potential consequences of over-or underestimating the results of such studies for clinical decision-making processes. Proper peer review of these publications requires a baseline familiarity of the language associated with machine learning, and how it differs from classical statistical analyses. This narrative review first introduces the overall field of machine learning and its role in artificial intelligence, and defines basic terminology. In addition, common modalities for applying machine learning, including classification and regression decision trees, support vector machines, and artificial neural networks are examined in the context of examples gathered from the spine literature. Lastly, the ethical challenges associated with adapting machine learning for research related to patient care, as well as future perspectives on the potential use of machine learning in spine surgery, are discussed specifically.

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“…The development of spinal surgery AR techniques has recently introduced new questions and new potential avenues for research on whether this could be combined with other novel techniques, such as navigational or robotic systems, and whether these innovations could bring spinal surgery to the next generation. 20 21 22 23 24 25 Although the clinical application of AR guidance in spinal surgery is still in its infancy, some pioneers have already made tremendous inroads with impressive research findings. 26 27 Here, our team describes the currently available AR-assisted spinal surgery techniques and summarizes the workflows and outcomes.…”

Section: Introductionmentioning

confidence: 99%

Spine Surgery Assisted by Augmented Reality: Where Have We Been?

2022

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This present systematic review examines spine surgery literature supporting augmented reality (AR) technology and summarizes its current status in spinal surgery technology. Database search strategies were retrieved from PubMed, Web of Science, Cochrane Library, Embase, from the earliest records to April 1, 2021. Our review briefly examines the history of AR, and enumerates different device application workflows in a variety of spinal surgeries. We also sort out the pros and cons of current mainstream AR devices and the latest updates. A total of 45 articles are included in our review. The most prevalent surgical applications included are the augmented reality surgical navigation system and head-mounted display. The most popular application of AR is pedicle screw instrumentation in spine surgery, and the primary responsible surgical levels are thoracic and lumbar. AR guidance systems show high potential value in practical clinical applications for the spine. The overall number of cases in AR-related studies is still rare compared to traditional surgical-assisted techniques. These lack long-term clinical efficacy and robust surgical-related statistical data. Changing healthcare laws as well as the increasing prevalence of spinal surgery are generating critical data that determines the value of AR technology.

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Machine vision augmented reality for pedicle screw insertion during spine surgery

Cited by 19 publications

References 13 publications

Machine Vision Navigation in Spine Surgery

Machine Vision Navigation in Spine Surgery

The Role of Machine Learning in Spine Surgery: The Future Is Now

Spine Surgery Assisted by Augmented Reality: Where Have We Been?

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