The ABCs of AR and VR
By Daniel A. Ortiz, MD; Vivek Kalia, MD, MPH, MS; Theresa H. Nguyen, MD; James Vogler IV, MD; José Morey, MD; Neil U. Lall, MD; Jan Fritz, MD; Falgun H. Chokshi, MD, MS, DABR; and Korak Sarkar, MD
Vol. 19 No. 10 P. 24
Augmented and virtual reality are still new, but they may soon write a new chapter in health care.
Advancements in imaging and digital pixel technology have accelerated in recent years, alongside AI and machine learning. We are now able to display a level of photorealism that is difficult to discern from reality. Technological advancements in the disciplines of augmented, virtual, and mixed realities are being integrated into our social fabric. Their economic impact is profound as well, with global estimated growth from $11.4 billion in 2017 to nearly $215 billion in 2021.1
The arrival of powerful handheld devices such as tablets and smartphones that can manage and utilize these technologies has fueled their rapid acceptance and integration, and they stand to revolutionize how we share experiences with each other and our surroundings. Just as the internet has revolutionized the way we share information, these new interfaces will impact how we learn, telecommute, and interact across boundaries—both physical and metaphorical—and make the world smaller than it is now.
Definitions of reality and virtuality vary based on industry and application. Paul Milgram, PhD, and Herman Colquhoun, Jr, define a parallel continua model (PCM), "Reality-Virtuality Continuum" and "Extent of World Knowledge Continuum," the latter of which they define as the degree to which the world is accurately modeled in a computer system.2
At one end of the spectrum, the real environment is the physical world that we live in day to day. The PCM defines reality as a world completely unmodeled. These authors include unaltered photographs, videos, X-rays, and ultrasound in the real environment, although it has also been posited that a "perceived [virtual] environment could be a captured 'real' world just as well as a completely synthetic world."3,4
On the other end of the spectrum, a virtual reality (VR) can be defined as an environment in which the viewer is completely immersed in a synthetic world. A fully virtual environment would have no "real" input on any of the perceiver's senses. The PCM defines this end of the spectrum as a world completely modeled.2 Steven M. LaValle defines VR as "inducing targeted behavior in an organism by using artificial sensory stimulation, while the organism has little or no awareness of the interference," where the targeted behavior is "having an 'experience' that was designed by the creator."3
Most experts define the environments on the spectrum between these two extremes as mixed reality.2 Even within mixed reality, there is a spectrum including augmented reality (AR) and augmented virtuality. AR is an environment closer to the real environment on the spectrum and can be defined as an environment in which most of the stimuli are real with supplementation of virtual objects.2 Augmented virtuality is an environment closer to VR on the spectrum and can be defined as an environment in which most of the stimuli are virtual with some superimposed real objects.2
Others consider mixed reality synonymous with merged reality, which is defined by interactions with a virtual object having an impact on a real object. For instance, in IR, some new developers are creating virtual fluoroscopy suite control panels that maximize the sterility of the procedure by removing the need for a physical sterile barrier.
Applications for Medical Education
Mixed reality can be useful for enhancing medical education. Traditionally, students learn anatomy using textbooks, online resources, cadavers, and artificial models. Mixed reality offers more dimensional information and interactivity compared to texts. This technology also may be more readily accessible than cadaveric models and can be particularly helpful for visualizing deep and/or delicate structures.5 Some AR programs project internal anatomy onto the user's body and simultaneously show the cross-sectional anatomy.6-8
Clinical medicine is increasingly reliant on imaging, and these programs can be useful for integrating radiology into anatomy education. There have also been developments in mobile AR applications, which can offer more convenience in learning anatomy.10,11 With the cultural trend of increased reliance on tablets and smartphones, mobile AR could be an attractive option in modernizing medical education.
Studies evaluating the use of VR and AR for learning anatomy show that students find VR and AR applications to be enjoyable, effective, and valuable resources.8,12 Although the technology appears promising, data showing improved learning outcomes compared with traditional methods are lacking.8,12-14 Currently, major limitations to adoption of AR applications in education include availability of hardware, paucity of AR anatomy content, and lack of instructors familiar with the technology.11,14 This technology is still in its infancy, and further studies are needed to establish its utility and effectiveness.
Procedural training is another area exploring applications of AR. Box trainers and VR simulators have been used for decades in minimally invasive surgery training.15 AR laparoscopic simulators attempt to combine the advantages of box trainers and VR simulators by allowing trainees to use real instruments to operate on virtual models and providing performance feedback. While promising, the technical capabilities for interactions between real instruments and VR models need to be refined.16
Rochlen and colleagues developed an AR system for practicing central venous catheter placement that allows trainees to visualize internal anatomy with AR glasses while performing the procedure on a mannequin. Participants found this to be a useful adjunct to traditional central venous catheter training.17 It has been proposed to use AR as a platform for remote procedural training, which can be helpful in rural areas. Wang and colleagues trialed remote ultrasound training with Microsoft's HoloLens. They concluded that many features, such as connectivity and user interface, need to be optimized before these AR systems can be implemented as telemedicine training tools.18
The examples presented here demonstrate potential roles for AR in medical procedural training. We note, however, that these AR systems have only been trialed in select groups of trainees and will likely require further validation before they are widely adopted.
Thoughts on Neuroradiology
Neurosurgical procedures encompass a wide variety of interventions including spine, intracranial, endovascular, and endoscopic interventions.19,20 These procedures often carry high risks with low margins for error. Competency in these procedures requires extensive and rigorous training. Several AR and VR simulator systems have been described for neurosurgical procedures such as tumor resection, burr hole drilling, ventriculostomy, endoscopic navigation transoral robotic surgery, and orbital tumor resection.21-25 Simulation practice allows trainees to gain experience in complex and/or risky procedures while mitigating potential patient harm. Although there is emerging evidence for the benefits of simulation in surgical training, it is not certain that simulator proficiency will translate into the operating room.26 More robust data are needed to establish how AR/VR simulations affect trainee competence in the real world. The potential benefit of intraprocedural AR tools is beginning to be investigated as well.
There have been multiple studies exploring the applications of AR in spine surgery. Elmi-Terander and colleagues demonstrated the feasibility of thoracic pedicle screw placement with a hybrid AR system.27 In this case, AR consistently yielded superior placement when compared with free-hand placement. Cadaveric models, however, cannot account for motion in living patients, eg, ventilation, that create image registration issues. In 2017, Ma and colleagues attempted to address this registration issue by using ultrasound-based coregistration.28
The feasibility of AR in percutaneous spine procedures has also been demonstrated in living humans.29 Abe and colleagues showed that AR can assist in vertebroplasty in a clinical trial but also confirmed the limitations of registration in actual patients, particularly for more complex anatomy.29 Decreased fluoroscopy time and, hence, decreased radiation exposure for the patient and clinician is consistently cited as an advantage to the use of intraprocedural AR.
AR also has the potential to benefit intracranial neurosurgery. Multiple groups have looked at the use of AR in brain tumor localization and resection.30,31 Many of these studies have been performed on phantom models, but Besharati Tabrizi and colleagues used AR for virtual lines for skin incision, virtual contour of craniotomy, and optimal dissection corridor in actual patients.30 As in spine applications, intracranial applications have issues with tissue registration and data are less reliable than standard intraoperative CT. Moreover, intracranial applications revealed limitations in image distortion and depth perception with AR projection, particularly distal from the center projection axis.30
Finally, AR has been applied to endoscopic neurosurgical procedures. Endoscopic skull base surgery is traditionally limited by endoscopic view. AR-based surgical navigation systems have been developed that can provide an extended view to a conventional endoscope by coregistering 3D anatomical models derived from a patient's preprocedure medical imaging onto real-time endoscopic camera views intraoperatively.32 A group in China developed an Apple ARKit-based system to help localize and evacuate hematomas related to hemorrhagic stroke endoscopically. However, AR endoscopic systems have the traditional issues with tissue registration, and they cannot provide haptic feedback.20 Bong and colleagues also found that AR in endoscopic surgery can be accurate but requires more time.32
Mixed reality applications can improve visualization of deep, complex, and/or obscure structures for neurosurgery. To date, however, there are no prospective studies showing a significant difference, such as improved clinical outcome or decreased complication rates, between AR-aided surgeries and surgeries using conventional navigation systems.33 One advantage of AR use is decreased fluoroscopy times associated with AR-assisted procedures. Limitations in user interface and image registration remain obstacles in the wider adoption of AR intraprocedurally. For the time being, the advantages of patient safety and training accessibility make AR/VR simulators attractive adjuncts in neurosurgery training while we understand and address the technical barriers to intraprocedural use of AR in neurosurgery.
Mixed reality and AR systems have been shown to provide a more intuitive understanding of surgical anatomy and assist in orthopedic hardware placement, for example, in cases of screw placement in percutaneous fixation of pelvic fractures or for sacroiliac joint fusion.34,35 Such advances may also allow for reductions in radiation dose to the patient and operator as well as decreased operating times by decreasing the number of attempts required to achieve fixation.
Another study used an AR system to overlay preoperative tumor imaging data on a patient's body intraoperatively to help guide orthopedic oncologic surgeons when selecting the resection margin and plane in real time.36 Such a system allows for real-time updates of the position and orientation of a saw used for resection relative to a bone tumor being resected, which may greatly reduce the risk of inadvertently violating a tumor margin with cutting instruments; for instance, small changes in angulation of a saw can be detected and corrected prior to advancing. There is reason to believe that AR-based navigation for bone tumor resection may improve accuracy in both experienced and inexperienced hands.37
Though there is much promise in such techniques, using camera-augmented mobile C-arm, for instance, significant challenges remain in implementation.30 Some have found that superimposition of imaging data on the surgical field may hinder a surgeon's field of view as it becomes highly cluttered intraoperatively.31 Experimentation with new AR fusion techniques that combine camera augmentation with additional information, such as depth perception with a Kinect sensor, will be included in the next stages of development of these techniques.31 Such techniques have been shown in simulated orthopedic surgeries to provide surgeons with better overall understanding of the surgical field and depth perception.31
As in other surgical subspecialties, orthopedic surgery training programs are developing VR-based simulators, which in the future may obviate the need for many cadaveric, animal, and synthetic constructs for surgical training. Some of these haptic feedback simulation-based systems have shown incredible promise to date.38-41
Like many of the other surgical specialties, AR and VR applications in plastic surgery include presurgical planning, navigation, and training.42
Visceral surgical applications of AR and VR have also been extensively reviewed, such as mixed reality applications with a HoloLens in the operating room.43-46 AR techniques have demonstrated most widespread use in open surgical procedures of solid abdominal organs including myomectomy, partial nephrectomy, resection of liver metastases, video-assisted thoracic surgery, gallbladder surgery, and guidance of reoperation for local recurrence in the case of inadequate initial tumor resections in pediatric tumors.47-52
Heckman and colleagues found some limitations of AR-assisted partial nephrectomy to include issues of tissue deformation, prolonged operative time, and lack of proof of superiority over intraoperative ultrasound.48
AR for IR
AR navigation systems have consistently demonstrated superiority over unguided biopsy procedures with regard to adequacy of tissue sample for histopathologic diagnosis. In the clinical setting of lung nodule biopsy, successful histopathologic diagnosis was obtained in 96% of cases using AR CT guidance compared with 84% without.53,54 This benefit is exaggerated when accounting for biopsy success of small nodules with a long needle to target distances.55 AR navigation systems have demonstrated similar aptitude for biopsy procedures with different modalities and target sites: MRI-guided biopsies of osseous lesions and CT-guided renal biopsies.56
CT-guided renal biopsy may be problematic if the renal mass is inconspicuous on noncontrast-enhanced CT. In the presence of other more readily identifiable lesions on noncontrast exam and, in particular, if low-dose scanning protocols are utilized, this could lead to a nonrepresentative biopsy. The literature reports rates of nondiagnostic biopsy up to 21% and nonrepresentative biopsy up to 11%.57,58 This affords a unique opportunity for AR navigation, if it were possible to overlay the conspicuous, contrast-enhanced lesion from a previous examination. This could not only improve diagnostic yield but also prevent the need for reinjecting contrast during the biopsy procedure. To the best of our knowledge, there are no studies addressing these clinical questions.
There is an incessant drive in the field of radiology to reduce radiation exposure to patients, in particular, given increased clinical reliance upon imaging. In laboratory trials, AR-augmented fluoroscopy has demonstrated noninferiority to CT-guided biopsy.59 Beyond improving diagnostic accuracy, diminishing adverse outcomes, or reducing the number of nondiagnostic procedures, AR navigation has demonstrated potential to decrease procedure time and improve clinical efficiency. Vascular access is critical for interventional angiographic procedures, including pelvic trauma and abdominal aneurysms, though it may be difficult in settings of hemodynamic instability or loss of normal anatomic or radiographic landmarks. AR has also been used in treatment planning for coronary artery disease.60 AR ultrasound guidance for vascular access demonstrated a decreased number of needle redirections and decrease in time to vascular access from 40 to 19 seconds.61 VR hypnosis is another facet of AR, with potential to improve clinical efficiency; the procedure diminishes pain and anxiety perception intraoperatively and diminishes the need for postprocedure monitoring.62
AR navigation has been applied to technically challenging procedures with promising results. In one study, AR guidance with an MRI overlay was used with a perfect technical success rate for paravertebral sympathetic plexus injection. AR navigation has additionally been applied to routine interventional procedures including arthrography and vertebroplasty, although the clinical utility of this practice is uncertain.29,63,64
The field of radiology has always been at the tip of the spear when it comes to technological advancement. The rate of current technological change has the potential to be dislocating to many industries and medical specialties. It is vitally important that we, as radiologists, continue to explore these developing technologies and their possible use cases to ensure that we optimize them for the best outcomes for our patients and our specialty continues to thrive in the years and decades to come.
— Daniel A. Ortiz, MD, is a musculoskeletal imaging fellow at the University of California, San Diego.
— Vivek Kalia, MD, MPH, MS, is an assistant professor of radiology in the division of musculoskeletal radiology at the University of Michigan School of Medicine.
— Theresa H. Nguyen, MD, is a radiologist at Ochsner Health System in New Orleans.
— James Vogler IV, MD, is a radiology resident at Eastern Virginia Medical Center in Norfolk, Virginia.
— José Morey, MD, is a radiologist and the chief medical informatics officer of Liberty BioSecurity.
— Neil U. Lall, MD, is a radiologist at Ochsner Health System in New Orleans.
— Jan Fritz, MD, is an associate professor of radiology and radiological science at the Johns Hopkins University School of Medicine.
— Falgun H. Chokshi, MD, MS, DABR, is an assistant professor in the department of radiology and imaging services at the Emory University School of Medicine.
— Korak Sarkar, MD, is a neurologist at Ochsner Health System in New Orleans.
1. Worldwide spending on augmented and virtual reality expected to double or more every year through 2021, according to IDC. IDC website. https://www.idc.com/getdoc.jsp?containerId=prUS42959717. Updated August 3, 2017.
2. Milgram P, Colquhoun H, Jr. A taxonomy of real and virtual world display integration. University of Toronto website. http://etclab.mie.utoronto.ca/publication/1999/Milgram_Colquhoun_ISMR1999.pdf. Published 1999.
3. LaValle SM. Virtual Reality. 2017. Urbana, Illinois: University of Illinois; 2016.
4. National Research Council. Virtual Reality: Scientific and Technological Challenges. Washington, DC: The National Academies Press; 1995.
5. Thomas RG, John NW, Delieu JM. Augmented reality for anatomical education. J Vis Commun Med. 2010;33(1):6-15.
6. Blum T, Kleeberger V, Bichlmeier C, Navab N. Mirracle: an augmented reality magic mirror system for anatomy education. Technische Universität München website. http://campar.in.tum.de/pub/blum2012vr/blum2012vr.pdf. Published 2012.
7. Ma M, Fallavollita P, Blum T, et al. Kinect for interactive AR anatomy learning. Paper presented at: IEEE International Symposium on Mixed and Augmented Reality (ISMAR); October 1, 2013.
8. Kugelmann D, Stratmann L, Nuhlen N, et al. An augmented reality magic mirror as additive teaching device for gross anatomy. Ann Anat. 2018;215:71-77.
9. Hamza-Lup FG, Santhanam AP, Imielińska C, Meeks SL, Rolland JP. Distributed augmented reality with 3-D lung dynamics — a planning tool concept. IEEE Trans Inf Technol Biomed. 2007;11(1):40-46.
10. Jain N, Youngblood P, Hasel M, Srivastava S. An augmented reality tool for learning spatial anatomy on mobile devices. Clin Anat. 2017;30(6):736-741.
11. Kucuk S, Kapakin S, Goktas Y. Learning anatomy via mobile augmented reality: effects on achievement and cognitive load. Anat Sci Educ. 2016;9(5):411-421.
12. Moro C, Stromberga Z, Raikos A, Stirling A. The effectiveness of virtual and augmented reality in health sciences and medical anatomy. Anat Sci Educ. 2017;10(6):549-559.
13. Hu A, Wilson T, Ladak H, Haase P, Doyle P, Fung K. Evaluation of a three-dimensional educational computer model of the larynx: voicing a new direction. J Otolaryngol Head Neck Surg. 2010;39(3):315-322.
14. Kamphuis C, Barsom E, Schijven M, Christoph N. Augmented reality in medical education? Perspect Med Educ. 2014;3(4):300-311.
15. Botden SM, Jakimowicz JJ. What is going on in augmented reality simulation in laparoscopic surgery? Surg Endosc. 2009;23(8):1693-1700.
16. Lahanas V, Loukas C, Smailis N, Georgiou E. A novel augmented reality simulator for skills assessment in minimal invasive surgery. Surg Endosc. 2015;29(8):2224-2234.
17. Rochlen LR, Levine R, Tait AR. First-person point-of-view-augmented reality for central line insertion training: a usability and feasibility study. Simul Healthc. 2017;12(1):57-62.
18. Wang S, Parsons M, Stone-McLean J, et al. Augmented reality as a telemedicine platform for remote procedural training. Sensors (Basel). 2017;17(10).
19. Soeiro J, Claudio AP, Carmo MB, Ferreira HA. Visualizing the brain on a mixed reality smartphone application. Conf Proc IEEE Eng Med Biol Soc. 2015;2015:5090-5093.
20. Hou Y, Ma L, Zhu R, Chen X. iPhone-assisted augmented reality localization of basal ganglia hypertensive hematoma. World Neurosurg. 2016;94:480-492.
21. Scolozzi P, Bijlenga P. Removal of recurrent intraorbital tumour using a system of augmented reality. Br J Oral Maxillofac Surg. 2017;55(9):962-964.
22. Lemole GM, Jr, Banerjee PP, Luciano C, Neckrysh S, Charbel FT. Virtual reality in neurosurgical education: part-task ventriculostomy simulation with dynamic visual and haptic feedback. Neurosurgery. 2007;61(1):142-148; discussion 8-9.
23. Alaraj A, Charbel FT, Birk D, et al. Role of cranial and spinal virtual and augmented reality simulation using immersive touch modules in neurosurgical training. Neurosurgery. 2013;72(Suppl 1):115-123.
24. Choudhury N, Gélinas-Phaneuf N, Delorme S, Del Maestro R. Fundamentals of neurosurgery: virtual reality tasks for training and evaluation of technical skills. World Neurosurg. 2013;80(5):e9-e19.
25. Mazur T, Mansour TR, Mugge L, Medkour A. Virtual reality-based simulators for cranial tumor surgery: a systematic review. World Neurosurg. 2018;110:414-422.
26. Borgersen NJ, Naur TMH, Sørensen SMD, et al. Gathering validity evidence for surgical simulation: a systematic review. Ann Surg. 2018;267(6):1063-1068.
27. Elmi-Terander A, Skulason H, Söderman M, et al. Surgical navigation technology based on augmented reality and integrated 3D intraoperative imaging: a spine cadaveric feasibility and accuracy study. Spine (Phila Pa 1976). 2016;41(21):E1303-e1311.
28. Ma L, Zhao Z, Chen F, Zhang B, Fu L, Liao H. Augmented reality surgical navigation with ultrasound-assisted registration for pedicle screw placement: a pilot study. Int J Comput Assist Radiol Surg. 2017;12(12):2205-2215.
29. Abe Y, Sato S, Kato K, et al. A novel 3D guidance system using augmented reality for percutaneous vertebroplasty: technical note. J Neurosurg Spine. 2013;19(4):492-501.
30. Besharati Tabrizi L, Mahvash M. Augmented reality-guided neurosurgery: accuracy and intraoperative application of an image projection technique. J Neurosurg. 2015;123(1):206-211.
31. Cutolo F, Meola A, Carbone M, et al. A new head-mounted display-based augmented reality system in neurosurgical oncology: a study on phantom. Comput Assist Surg (Abingdon). 2017;22(1):39-53.
32. Bong JH, Song HJ, Oh Y, Park N, Kim H, Park S. Endoscopic navigation system with extended field of view using augmented reality technology. Int J Med Robot. 2018;14(2).
33. Meola A, Cutolo F, Carbone M, Cagnazzo F, Ferrari M, Ferrari V. Augmented reality in neurosurgery: a systematic review. Neurosurg Rev. 2017;40(4):537-548.
34. Lee SC, Fuerst B, Tateno K, et al. Multi-modal imaging, model-based tracking, and mixed reality visualisation for orthopaedic surgery. Healthc Technol Lett. 2017;4(5):168-173.
35. Wang H, Wang F, Leong AP, Xu L, Chen X, Wang Q. Precision insertion of percutaneous sacroiliac screws using a novel augmented reality-based navigation system: a pilot study. Int Orthop. 2016;40(9):1941-1947.
36. Choi H, Park Y, Lee S, et al. A portable surgical navigation device to display resection planes for bone tumor surgery. Minim Invasive Ther Allied Technol. 2017;26(3):144-150.
37. Cho HS, Park YK, Gupta S, et al. Augmented reality in bone tumour resection: an experimental study. Bone Joint Res. 2017;6(3):137-143.
38. Pettersson J, Palmerius KL, Knutsson H, Wahlstrom O, Tillander B, Borga M. Simulation of patient specific cervical hip fracture surgery with a volume haptic interface. IEEE Trans Biomed Eng. 2008;55(4):1255-1265.
39. Blyth P, Stott NS, Anderson IA. A simulation-based training system for hip fracture fixation for use within the hospital environment. Injury. 2007;38(10):1197-1203.
40. Vankipuram M, Kahol K, McLaren A, Panchanathan S. A virtual reality simulator for orthopedic basic skills: a design and validation study. J Biomed Inform. 2010;43(5):661-668.
41. Kovler I, Joskowicz L, Weil YA, et al. Haptic computer-assisted patient-specific preoperative planning for orthopedic fractures surgery. Int J Comput Assist Radiol Surg. 2015;10(10):1535-1546.
42. Kim Y, Kim H, Kim YO. Virtual reality and augmented reality in plastic surgery: a review. Arch Plast Surg. 2017;44(3):179-187.
43. Vavra P, Roman J, Zonca P, et al. Recent development of augmented reality in surgery: a review. J Healthc Eng. 2017;2017:4574172.
44. Sauer IM, Queisner M, Tang P, et al. Mixed reality in visceral surgery: development of a suitable workflow and evaluation of intraoperative use-cases. Ann Surg. 2017;266(5):706-712.
45. Douglas DB, Wilke CA, Gibson D, Petricoin EF, Liotta L. Virtual reality and augmented reality: advances in surgery. Biol Eng Med. 2017;3(1):1-8.
46. Tepper OM, Rudy HL, Lefkowitz A, et al. Mixed reality with HoloLens: where virtual reality meets augmented reality in the operating room. Plast Reconstr Surg. 2017;140(5):1066-1070.
47. Bourdel N, Collins T, Pizarro D, et al. Augmented reality in gynecologic surgery: evaluation of potential benefits for myomectomy in an experimental uterine model. Surg Endosc. 2017;31(1):456-461.
48. Hekman MCH, Rijpkema M, Langenhuijsen JF, Boerman OC, Oosterwijk E, Mulders PFA. Intraoperative imaging techniques to support complete tumor resection in partial nephrectomy [published online May 12, 2017]. Eur Urol Focus. doi: 10.1016/j.euf.2017.04.008.
49. Ntourakis D, Memeo R, Soler L, Marescaux J, Mutter D, Pessaux P. Augmented reality guidance for the resection of missing colorectal liver metastases: an initial experience. World J Surg. 2016;40(2):419-426.
50. Rouze S, de Latour B, Flecher E, et al. Small pulmonary nodule localization with cone beam computed tomography during video-assisted thoracic surgery: a feasibility study. Interact Cardiovasc Thorac Surg. 2016;22(6):705-711.
51. Diana M, Soler L, Agnus V, et al. Prospective evaluation of precision multimodal gallbladder surgery navigation: virtual reality, near-infrared fluorescence, and X-ray-based intraoperative cholangiography. Ann Surg. 2017;266(5):890-897.
52. Souzaki R, Ieiri S, Uemura M, et al. An augmented reality navigation system for pediatric oncologic surgery based on preoperative CT and MRI images. J Pediatr Surg. 2013;48(12):2479-2483.
53. Faiella E, Frauenfelder G, Santucci D, et al. Percutaneous low-dose CT-guided lung biopsy with an augmented reality navigation system: validation of the technique on 496 suspected lesions. Clin Imaging. 2017;49:101-105.
54. Guimarães MD, Chojniak R, Gross JL, Bitencourt AG. Predictive success factors for CT-guided fine needle aspiration biopsy of pulmonary lesions. Clinics (Sao Paulo). 2009;64(12):1139-1144.
55. Grasso RF, Faiella E, Luppi G, et al. Percutaneous lung biopsy: comparison between an augmented reality CT navigation system and standard CT-guided technique. Int J Comput Assist Radiol Surg. 2013;8(5):837-848.
56. Fritz J, U-Thainual P, Ungi T, et al. Augmented reality visualization using image overlay technology for MR-guided interventions: cadaveric bone biopsy at 1.5 T. Invest Radiol. 2013;48(6):464-470.
57. Leveridge MJ, Finelli A, Kachura JR, et al. Outcomes of small renal mass needle core biopsy, nondiagnostic percutaneous biopsy, and the role of repeat biopsy. Eur Urol. 2011;60(3):578-584.
58. Gellert LL, Mehra R, Chen YB, et al. The diagnostic accuracy of percutaneous renal needle core biopsy and its potential impact on the clinical management of renal cortical neoplasms. Arch Pathol Lab Med. 2014;138(12):1673-1679.
59. Racadio JM, Nachabe R, Homan R, Schierling R, Racadio JM, Babic D. Augmented reality on a C-arm system: a preclinical assessment for percutaneous needle localization. Radiology. 2016;281(1):249-255.
60. Li Q, Huang C, Lv S, Li Z, Chen Y, Ma L. An human-computer interactive augmented reality system for coronary artery diagnosis planning and training. J Med Syst. 2017;41(10):159.
61. Jeon Y, Choi S, Kim H. Evaluation of a simplified augmented reality device for ultrasound-guided vascular access in a vascular phantom. J Clin Anesth. 2014;26(6):485-489.
62. Li L, Yu F, Shi D, et al. Application of virtual reality technology in clinical medicine. Am J Transl Res. 2017;9(9):3867-3880.
63. Fritz J, U-Thainual P, Ungi T, et al. Augmented reality visualization with use of image overlay technology for MR imaging-guided interventions: assessment of performance in cadaveric shoulder and hip arthrography at 1.5 T. Radiology. 2012;265(1):254-259.
64. Fritz J, U-Thainual P, Ungi T, et al. MR-guided vertebroplasty with augmented reality image overlay navigation. Cardiovasc Intervent Radiol. 2014;37(6):1589-1596.