Commentary: Augmented reality in neurosurgery, state of art and future projections. A systematic review
Andrew Willett, Mohammad Haq, Joseph Holland, Elizabeth Bridwell
- 发表年份
- 2023
- 引用次数
- 2
- 访问权限
- 开放获取
摘要
Innovation and medicine are inseparable, and technologies such as augmented reality (AR) may transform the modern neurosurgical armamentarium. Per insights shared by Cannizzaro and colleagues in their review article “Augmented Reality in Neurosurgery, State of Art and Future Projections. A Systematic Review” [1], AR-assisted neurosurgery is a promising, albeit complex and challenging advancement. Over the past year our team of medical students has engaged in a biomedical innovation curriculum offered by a select cohort of accredited medical schools throughout the United States. We were tasked with evaluating the future of AR in neurosurgery. Thanks to our immersive experience with this unique technology, we felt inclined to comment on this article and share our perspectives in hopes that others will engage in these conversations and further promote AR in medicine, specifically within the field of neurosurgery. We found the review article to be robust and believe that it warrants a significant amount of consideration.The authors highlight how AR has been largely investigated in spine surgeries, composing 18.2% of their literature review [1]. This neurosurgical subspeciality has grown in minimally invasive techniques, a process that has been amplified with the utilization of neuronavigation systems. Studies suggest that AR-assisted pedicle screw placement is legitimate, with some reports sharing 100% accuracy [2] while others share 97.8-98.5% accuracy [3]. Although these numbers are encouraging, we must thoroughly question how this technology challenges more traditional surgical techniques. Why invest in AR if it offers no significant benefit? Dennler et al. [4] show that supplemental anatomical information provided via AR may help novice surgeons match the efficacy of expert surgeons with pedicle screw placement. However, to our knowledge, no large-scale randomized control trials to date have compared AR assisted pedicle screw placement versus traditional pedicle screw placement. Moreover, we do not thoroughly understand if AR-assisted surgeries are cost-effective. We can glean insights from literature that compares the use of free hand techniques with robotic devices; although robotics may have more accuracy in placing pedicle screws and can help decrease postoperative complications, the initial costs (which can approach upwards of $850,000) and increased OR time are thought to drastically outweigh its current benefits [5]. Contrastingly, AR systems like Xvision have comparable profiles of improved accuracy but offer lower upfront cost [6], suggesting an opportunity for feasible integration. Other groups must not only reinforce the efficacy and practicality of AR, but also clearly analyze the fiscality of these technologies if veteran and novice surgeons alike are to adopt a new way of operating. AR is an arguably more alluring tool for neurosurgical oncologists and neurosurgeons working in remote areas seeking to collaborate with distant colleagues, which is a realm we would have appreciated for Cannizzaro and colleagues to further explore. Our review of the available AR neuro-oncology literature has been exciting—particularly, a statistically significant improvement in percent of complete glioma resection in a test group (69.6%) compared to the control group (36.4%) (p<.01) has been reported [7]. Other studies acknowledge the postoperative improvements associated with AR guided surgeries as patients who underwent AR-assisted tumor resection experienced shorter length of hospital stay and improved postoperative quality of life in comparison to non-AR guided resections [8]. Moving forward, AR enthusiasts should emphasize a need to attend to extraoperative components affiliated with AR surgeries—if patients spend less time in the hospital and report higher quality of life following AR-guided surgery, then investing in these technologies becomes clearer. Thus, if we can better pinpoint where AR aligns with the needs of both the
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002