Augmented reality and artificial intelligence-assisted surgical navigation: Technique and cadaveric feasibility study

Accuracy of augmented reality-assisted pedicle screw placement: a systematic review

OBJECTIVE

Conventional freehand methods of pedicle screw placement are associated with significant complications due to close proximity to neural and vascular structures. Recent advances in augmented reality surgical navigation (ARSN) have led to its adoption into spine surgery. However, little is known regarding its overall accuracy. The purpose of this study is to delineate the overall accuracy of ARSN pedicle screw placement across various models.

METHODS

A systematic review was conducted of Medline/PubMed, Cochrane and Embase Library databases according to the PRISMA guidelines. Relevant data extracted included reports of pedicle screw placement accuracy and breaches, as defined by the Gertzbein-Robbins classification, in addition to deviation from pre-planned trajectory and entry point. Accuracy was defined as the summation of grade 0 and grade 1 events per the Gertzbein-Robbins classification.

RESULTS

Twenty studies reported clinically accurate placed screws. The range of clinically accurate placed screws was 26.3-100%, with 2095 screws (93.1%) being deemed clinically accurate. Furthermore, 5.4% (112/2088) of screws were reported as grade two breaches, 1.6% (33/2088) grade 3 breaches, 3.1% (29/926) medial breaches and 2.3% (21/926) lateral breaches. Mean linear deviation ranged from 1.3 to 5.99 mm, while mean angular/trajectory deviation ranged 1.6°-5.88°.

CONCLUSION

The results of this study highlight the overall accuracy of ARSN pedicle screw placement. However, further robust prospective studies are needed to accurately compare to conventional methods of pedicle screw placement.

Virtual, Augmented, and Mixed Reality Applications for Surgical Rehearsal, Operative Execution, and Patient Education in Spine Surgery: A Scoping Review

Background and Objectives: Advances in virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies have resulted in their increased application across many medical specialties. VR's main application has been for teaching and preparatory roles, while AR has been mostly used as a surgical adjunct. The objective of this study is to discuss the various applications and prospects for VR, AR, and MR specifically as they relate to spine surgery. Materials and Methods: A systematic review was conducted to examine the current applications of VR, AR, and MR with a focus on spine surgery. A literature search of two electronic databases (PubMed and Scopus) was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The study quality was assessed using the MERSQI score for educational research studies, QUACS for cadaveric studies, and the JBI critical appraisal tools for clinical studies. Results: A total of 228 articles were identified in the primary literature review. Following title/abstract screening and full-text review, 46 articles were included in the review. These articles comprised nine studies performed in artificial models, nine cadaveric studies, four clinical case studies, nineteen clinical case series, one clinical case-control study, and four clinical parallel control studies. Teaching applications utilizing holographic overlays are the most intensively studied aspect of AR/VR; the most simulated surgical procedure is pedicle screw placement. Conclusions: VR provides a reproducible and robust medium for surgical training through surgical simulations and for patient education through various platforms. Existing AR/MR platforms enhance the accuracy and precision of spine surgeries and show promise as a surgical adjunct.

The Rise of Artificial Intelligence: Implications in Orthopedic Surgery

Artificial intelligence (AI) is slowly making its way into all domains and medicine is no exception. AI is already proving to be a promising tool in the health-care field. With respect to orthopedics, AI is already under use in diagnostics as in fracture and tumor detection, predictive algorithms to predict the mortality risk and duration of hospital stay or complications such as implant loosening and in real-time assessment of post-operative rehabilitation. AI could also be of use in surgical training, utilizing technologies such as virtual reality and augmented reality. However, clinicians should also be aware of the limitations of AI as validation is necessary to avoid errors. This article aims to provide a description of AI and its subfields, its current applications in orthopedics, the limitations, and its future prospects.

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

This systematic review summarizes existing evidence and outlines the benefits of artificial intelligence-assisted spine surgery. The popularity of artificial intelligence has grown significantly, demonstrating its benefits in computer-assisted surgery and advancements in spinal treatment. This study adhered to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), a set of reporting guidelines specifically designed for systematic reviews and meta-analyses. The search strategy used Medical Subject Headings (MeSH) terms, including "MeSH (Artificial intelligence)," "Spine" AND "Spinal" filters, in the last 10 years, and English- from January 1, 2013, to October 31, 2023. In total, 442 articles fulfilled the first screening criteria. A detailed analysis of those articles identified 220 that matched the criteria, of which 11 were considered appropriate for this analysis after applying the complete inclusion and exclusion criteria. In total, 11 studies met the eligibility criteria. Analysis of these studies revealed the types of artificial intelligence-assisted spine surgery. No evidence suggests the superiority of assisted spine surgery with or without artificial intelligence in terms of outcomes. In terms of feasibility, accuracy, safety, and facilitating lower patient radiation exposure compared with standard fluoroscopic guidance, artificial intelligence-assisted spine surgery produced satisfactory and superior outcomes. The incorporation of artificial intelligence with augmented and virtual reality appears promising, with the potential to enhance surgeon proficiency and overall surgical safety.

Current clinical applications of artificial intelligence in shoulder surgery: what the busy shoulder surgeon needs to know and what's coming next

Background

Artificial intelligence (AI) is a continuously expanding field with the potential to transform a variety of industries-including health care-by providing automation, efficiency, precision, accuracy, and decision-making support for simple and complex tasks. Basic knowledge of the key features as well as limitations of AI is paramount to understand current developments in this field and to successfully apply them to shoulder surgery. The purpose of the present review is to provide an overview of AI within orthopedics and shoulder surgery exploring current and forthcoming AI applications.

Methods

PubMed and Scopus databases were searched to provide a narrative review of the most relevant literature on AI applications in shoulder surgery.

Results

Despite the enormous clinical and research potential of AI, orthopedic surgery has been a relatively late adopter of AI technologies. Image evaluation, surgical planning, aiding decision-making, and facilitating patient evaluations over time are some of the current areas of development with enormous opportunities to improve surgical practice, research, and education. Furthermore, the advancement of AI-driven strategies has the potential to create a more efficient medical system that may reduce the overall cost of delivering and implementing quality health care for patients with shoulder pathology.

Conclusion

AI is an expanding field with the potential for broad clinical and research applications in orthopedic surgery. Many challenges still need to be addressed to fully leverage the potential of AI to clinical practice and research such as privacy issues, data ownership, and external validation of the proposed models.

Technological advancements in surgical laparoscopy considering artificial intelligence: a survey among surgeons in Germany

PURPOSE

The integration of artificial intelligence (AI) into surgical laparoscopy has shown promising results in recent years. This survey aims to investigate the inconveniences of current conventional laparoscopy and to evaluate the attitudes and desires of surgeons in Germany towards new AI-based laparoscopic systems.

METHODS

A 12-item web-based questionnaire was distributed to 38 German university hospitals as well as to a Germany-wide voluntary hospital association (CLINOTEL) consisting of 66 hospitals between July and November 2022.

RESULTS

A total of 202 questionnaires were completed. The majority of respondents (88.1%) stated that they needed one assistant during laparoscopy and rated the assistants' skillfulness as "very important" (39.6%) or "important" (49.5%). The most uncomfortable aspects of conventional laparoscopy were inappropriate camera movement (73.8%) and lens condensation (73.3%). Selected features that should be included in a new laparoscopic system were simple and intuitive maneuverability (81.2%), automatic de-fogging (80.7%), and self-cleaning of camera (77.2%). Furthermore, AI-based features were improvement of camera positioning (71.3%), visualization of anatomical landmarks (67.3%), image stabilization (66.8%), and tissue damage protection (59.4%). The reason for purchasing an AI-based system was to improve patient safety (86.1%); the reasonable price was €50.000-100.000 (34.2%), and it was expected to replace the existing assistants' workflow up to 25% (41.6%).

CONCLUSION

Simple and intuitive maneuverability with improved and image-stabilized camera guidance in combination with a lens cleaning system as well as AI-based augmentation of anatomical landmarks and tissue damage protection seem to be significant requirements for the further development of laparoscopic systems.

Application progress of artificial intelligence and augmented reality in orthopaedic arthroscopy surgery

In today's rapidly developing technological era, the technological revolution triggered by the rapid iteration of artificial intelligence and augmented reality has provided brand-new digital intelligent empowerment for orthopaedic clinical operation. Although traditional arthroscopy has been widely promoted globally due to its advantages such as minimally invasive, safety and early functional exercise, it still has deficiencies in precision and personalization. The assistance of artificial intelligence and augmented reality enables precise positioning and navigation in arthroscopic surgery, as well as personalized operations based on patient conditions, which lifts the objective limitations of traditional sports medicine surgery. The integration of artificial intelligence and augmented reality with orthopaedic arthroscopy surgery is still in infancy, even though there are still some insufficient to be solved, but its prospect is bright.

The Accuracy and Absolute Reliability of a Knee Surgery Assistance System Based on ArUco-Type Sensors

Recent advances allow the use of Augmented Reality (AR) for many medical procedures. AR via optical navigators to aid various knee surgery techniques (e.g., femoral and tibial osteotomies, ligament reconstructions or menisci transplants) is becoming increasingly frequent. Accuracy in these procedures is essential, but evaluations of this technology still need to be made. Our study aimed to evaluate the system's accuracy using an in vitro protocol. We hypothesised that the system's accuracy was equal to or less than 1 mm and 1° for distance and angular measurements, respectively. Our research was an in vitro laboratory with a 316 L steel model. Absolute reliability was assessed according to the Hopkins criteria by seven independent evaluators. Each observer measured the thirty palpation points and the trademarks to acquire direct angular measurements on three occasions separated by at least two weeks. The system's accuracy in assessing distances had a mean error of 1.203 mm and an uncertainty of 2.062, and for the angular values, a mean error of 0.778° and an uncertainty of 1.438. The intraclass correlation coefficient was for all intra-observer and inter-observers, almost perfect or perfect. The mean error for the distance's determination was statistically larger than 1 mm (1.203 mm) but with a trivial effect size. The mean error assessing angular values was statistically less than 1°. Our results are similar to those published by other authors in accuracy analyses of AR systems.

Artificial intelligence in orthopaedic surgery

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as 'big data', AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI's limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction.

Virtual and Augmented Reality in Spine Surgery: A Systematic Review

BACKGROUND

Augmented reality (AR) and virtual reality (VR) implementation in spinal surgery has expanded rapidly over the past decade. This systematic review summarizes the use of AR/VR technology in surgical education, preoperative planning, and intraoperative guidance.

METHODS

A search query for AR/VR technology in spine surgery was conducted through PubMed, Embase, and Scopus. After exclusions, 48 studies were included. Included studies were then grouped into relevant subsections. Categorization into subsections yielded 12 surgical training studies, 5 preoperative planning, 24 intraoperative usage, and 10 radiation exposure.

RESULTS

VR-assisted training significantly reduced penetration rates or increased accuracy rates compared to lecture-based groups in 5 studies. Preoperative VR planning significantly influenced surgical recommendations and reduced radiation exposure, operating time, and estimated blood loss. For 3 patient studies, AR-assisted pedicle screw placement accuracy ranged from 95.77% to 100% using the Gertzbein grading scale. Head-mounted display was the most common interface used intraoperatively followed by AR microscope and projector. AR/VR also had applications in tumor resection, vertebroplasty, bone biopsy, and rod bending. Four studies reported significantly reduced radiation exposure in AR group compared to fluoroscopy group.

CONCLUSIONS

AR/VR technologies have the potential to usher in a paradigm shift in spine surgery. However, the current evidence indicates there is still a need for 1) defined quality and technical requirements for AR/VR devices, 2) more intraoperative studies that explore usage outside of pedicle screw placement, and 3) technological advancements to overcome registration errors via the development of an automatic registration method.

Clinical applications of augmented reality in orthopaedic surgery: a comprehensive narrative review

PURPOSE

The development of augmented reality (AR) technology allows orthopaedic surgeons to incorporate and visualize surgical data, assisting the execution of both routine and complex surgical operations. Uniquely, AR technology allows a surgeon to view the surgical field and superimpose peri-operative imaging, anatomical landmarks, navigation guidance, and more, all in one view without the need for conjugate gaze between multiple screens. The aim of this literature review was to introduce the fundamental requirements for an augmented reality system and to assess the current applications, outcomes, and potential limitations to this technology.

METHODS

A literature search was performed using MEDLINE and Embase databases, by two independent reviewers, who then collaboratively synthesized and collated the results of the literature search into a narrative review focused on the applications of augmented reality in major orthopaedic sub-specialties.

RESULTS

Current technology requires that pre-operative patient data be acquired, and AR-compatible models constructed. Intra-operatively, to produce manipulatable virtual images into the user's view in real time, four major components are required including a camera, computer image processing technology, tracking tools, and an output screen. The user is provided with a heads-up display, which is a transparent display, enabling the user to look at both their natural view and the computer-generated images. Currently, high-quality evidence for clinical implementation of AR technology in the orthopaedic surgery operating room is lacking; however, growing in vitro literature highlights a multitude of potential applications, including increasing operative accuracy, improved biomechanical angular and alignment parameters, and potentially reduced operative time.

CONCLUSION

While the application of AR systems in surgery is currently in its infancy, we anticipate rapid and widespread implementation of this technology in various orthopaedic sub-specialties.

Advancing Surgical Education: The Use of Artificial Intelligence in Surgical Training

The technology of artificial intelligence (AI) has made significant in-roads into the field of medicine over the last decade. With surgery being a discipline where repetition is the key to mastery, the scope of AI presents enormous potential for resident education through the analysis of technique and delivery of structured feedback for performance improvement. In an era marred by a raging pandemic that has decreased exposure and opportunity, AI offers an attractive solution towards improving operating room efficiency, safe patient care in the hands of supervised residents and can ultimately culminate in reduced health care costs. Through this article, we elucidate the current adoption of the artificial intelligence technology and its prospects for advancing surgical education.

Augmented Reality in Spine Surgery: Current State of the Art

Augmented reality (AR) is the superimposition of a virtual environment on the real world. The use of AR in spine surgery continues to grow, with multiple companies and products becoming available. The proposed benefits of AR include decreased attention shift, decreased line-of-site interruption, opportunity for more minimally invasive approaches, decreased radiation exposure to the operative team, and improved pedicle screw accuracy. In this review, we examine our institutional experiences with utilization and implementation of some of the current AR products.

Navigation Techniques in Endoscopic Spine Surgery

Endoscopic spine surgery (ESS) advances the principles of minimally invasive surgery, including minor collateral tissue damage, reduced blood loss, and faster recovery times. ESS allows for direct access to the spine through small incisions and direct visualization of spinal pathology via an endoscope. While this technique has many applications, there is a steep learning curve when adopting ESS into a surgeon's practice. Two types of navigation, optical and electromagnetic, may allow for widespread utilization of ESS by engendering improved orientation to surgical anatomy and reduced complication rates. The present review discusses these two available navigation technologies and their application in endoscopic procedures by providing case examples. Furthermore, we report on the future directions of navigation within the discipline of ESS.

Machine Learning Applications of Surgical Imaging for the Diagnosis and Treatment of Spine Disorders: Current State of the Art

Recent developments in machine learning (ML) methods demonstrate unparalleled potential for application in the spine. The ability for ML to provide diagnostic faculty, produce novel insights from existing capabilities, and augment or accelerate elements of surgical planning and decision making at levels equivalent or superior to humans will tremendously benefit spine surgeons and patients alike. In this review, we aim to provide a clinically relevant outline of ML-based technology in the contexts of spinal deformity, degeneration, and trauma, as well as an overview of commercial-level and precommercial-level surgical assist systems and decisional support tools. Furthermore, we briefly discuss potential applications of generative networks before highlighting some of the limitations of ML applications. We conclude that ML in spine imaging represents a significant addition to the neurosurgeon's armamentarium-it has the capacity to directly address and manifest clinical needs and improve diagnostic and procedural quality and safety-but is yet subject to challenges that must be addressed before widespread implementation.

Feasibility and Accuracy of Thoracolumbar Pedicle Screw Placement Using an Augmented Reality Head Mounted Device

Background: To investigate the accuracy of augmented reality (AR) navigation using the Magic Leap head mounted device (HMD), pedicle screws were minimally invasively placed in four spine phantoms. Methods: AR navigation provided by a combination of a conventional navigation system integrated with the Magic Leap head mounted device (AR-HMD) was used. Forty-eight screws were planned and inserted into Th11-L4 of the phantoms using the AR-HMD and navigated instruments. Postprocedural CT scans were used to grade the technical (deviation from the plan) and clinical (Gertzbein grade) accuracy of the screws. The time for each screw placement was recorded. Results: The mean deviation between navigation plan and screw position was 1.9 ± 0.7 mm (1.9 [0.3–4.1] mm) at the entry point and 1.4 ± 0.8 mm (1.2 [0.1–3.9] mm) at the screw tip. The angular deviation was 3.0 ± 1.4° (2.7 [0.4–6.2]°) and the mean time for screw placement was 130 ± 55 s (108 [58–437] s). The clinical accuracy was 94% according to the Gertzbein grading scale. Conclusion: The combination of an AR-HMD with a conventional navigation system for accurate minimally invasive screw placement is feasible and can exploit the benefits of AR in the perspective of the surgeon with the reliability of a conventional navigation system.

Augmented Reality (AR) in Orthopedics: Current Applications and Future Directions

PURPOSE OF REVIEW

Imaging technologies (X-ray, CT, MRI, and ultrasound) have revolutionized orthopedic surgery, allowing for the more efficient diagnosis, monitoring, and treatment of musculoskeletal aliments. The current review investigates recent literature surrounding the impact of augmented reality (AR) imaging technologies on orthopedic surgery. In particular, it investigates the impact that AR technologies may have on provider cognitive burden, operative times, occupational radiation exposure, and surgical precision and outcomes.

RECENT FINDINGS

Many AR technologies have been shown to lower provider cognitive burden and reduce operative time and radiation exposure while improving surgical precision in pre-clinical cadaveric and sawbones models. So far, only a few platforms focusing on pedicle screw placement have been approved by the FDA. These technologies have been implemented clinically with mixed results when compared to traditional free-hand approaches. It remains to be seen if current AR technologies can deliver upon their multitude of promises, and the ability to do so seems contingent upon continued technological progress. Additionally, the impact of these platforms will likely be highly conditional on clinical indication and provider type. It remains unclear if AR will be broadly accepted and utilized or if it will be reserved for niche indications where it adds significant value. One thing is clear, orthopedics' high utilization of pre- and intra-operative imaging, combined with the relative ease of tracking rigid structures like bone as compared to soft tissues, has made it the clear beachhead market for AR technologies in medicine.

Autonomous lumbar spine pedicle screw planning using machine learning: A validation study

Introduction:

Several techniques for pedicle screw placement have been described including freehand techniques, fluoroscopy assisted, computed tomography (CT) guidance, and robotics. Image-guided surgery offers the potential to combine the benefits of CT guidance without the added radiation. This study investigated the ability of a neural network to place lumbar pedicle screws with the correct length, diameter, and angulation autonomously within radiographs without the need for human involvement.

Materials and Methods:

The neural network was trained using a machine learning process. The method combines the previously reported autonomous spine segmentation solution with a landmark localization solution. The pedicle screw placement was evaluated using the Zdichavsky, Ravi, and Gertzbein grading systems.

Results:

In total, the program placed 208 pedicle screws between the L1 and S1 spinal levels. Of the 208 placed pedicle screws, 208 (100%) had a Zdichavsky Score 1A, 206 (99.0%) of all screws were Ravi Grade 1, and Gertzbein Grade A indicating no breech. The final two screws (1.0%) had a Ravi score of 2 (<2 mm breech) and a Gertzbein grade of B (<2 mm breech).

Conclusion:

The results of this experiment can be combined with an image-guided platform to provide an efficient and highly effective method of placing pedicle screws during spinal stabilization surgery.

The Clinical Application of Augmented Reality in Orthopaedics: Where Do We Stand?

PURPOSE OF REVIEW

The surgical community is constantly working to improve accuracy and reproducibility in patient care, with the goal to improve patient outcomes and efficiency. One area of growing interest with potential to meet these goals is in the use of augmented reality (AR) in surgery. There is still a paucity of published research on the clinical benefits of AR over traditional techniques, but this article aims to present an update on the current state of AR within orthopaedics over the past 5 years.

RECENT FINDINGS

AR systems are being developed and studied for use in all areas of orthopaedics. Most recently published research has focused on the areas of fracture care, adult reconstruction, orthopaedic oncology, spine, and resident education. These studies have shown some promising results, particularly in surgical accuracy, decreased surgical time, and less radiation exposure. However, the majority of recently published research is still in the pre-clinical setting, with very few studies using living patients. AR supplementation in orthopaedic surgery has shown promising results in pre-clinical settings, with improvements in surgical accuracy and reproducibility, decreased operating times, and less radiation exposure. Most AR systems, however, are still not approved for clinical use. Further research is needed to validate the benefits of AR use in orthopaedic surgery before it is widely adopted into practice.

How precise are oral splints for frameless stereotaxy in guided ear, nose, throat, and maxillofacial surgery: a cadaver study

Background

Computer-assisted surgery optimises accuracy and serves to improve precise surgical procedures. We validated oral splints with fiducial markers by testing them against rigid bone markers.

Methods

We screwed twenty bone anchors as fiducial markers into different regions of a dried skull and measured the distances. After computed tomography (CT) scanning, the accuracy was evaluated by determining the markers’ position using frameless stereotaxy on a dry cadaver and indicated on the CT scan. We compared the accuracy of chairside fabricated oral splints to standard registration with bone markers immediately after fabrication and after a ten-time use. Accuracy was calculated as deviation (mean ± standard deviation). For statistical analysis, t test, Kruskal-Wallis, Tukey's, and various linear regression models, such as the Pearson's product–moment correlation coefficient, were used.

Results

Oral splints showed an accuracy of 0.90 mm ± 0.27 for viscerocranium, 1.10 mm ± 0.39 for skull base, and 1.45 mm ± 0.59 for neurocranium. We found an accuracy of less than 2 mm for both splints for a distance of up to 152 mm. The accuracy persisted even after ten times removing and reattaching the splints.

Conclusions

Oral splints offer a non-invasive indicator to improve the accuracy of image-guided surgery. The precision is dependent on the distance to the target. Up to 150-mm distance, a precision of fewer than 2 mm is possible. Dental splints provide sufficient accuracy than bone markers and may opt for higher precision combined with other non-invasive registration methods.

Augmented reality navigation in spine surgery: a systematic review

BACKGROUND

Conventional spinal navigation solutions have been criticized for having a negative impact on time in the operating room and workflow. AR navigation could potentially alleviate some of these concerns while retaining the benefits of navigated spine surgery. The objective of this study is to summarize the current evidence for using augmented reality (AR) navigation in spine surgery.

METHODS

We performed a systematic review to explore the current evidence for using AR navigation in spine surgery. PubMed and Web of Science were searched from database inception to November 27, 2020, for data on the AR navigation solutions; the reported efficacy of the systems; and their impact on workflow, radiation, and cost-benefit relationships.

RESULTS

In this systematic review, 28 studies were included in the final analysis. The main findings were superior workflow and non-inferior accuracy when comparing AR to free-hand (FH) or conventional surgical navigation techniques. A limited number of studies indicated decreased use of radiation. There were no studies reporting mortality, morbidity, or cost-benefit relationships.

CONCLUSIONS

AR provides a meaningful addition to FH surgery and traditional navigation methods for spine surgery. However, the current evidence base is limited and prospective studies on clinical outcomes and cost-benefit relationships are needed.