scholarly journals Corrigendum to: “Clinical Accuracy, Technical Precision, and Workflow of the First in Human Use of an Augmented-Reality Head Mound Display Stereotactic Navigation System for Spine Surgery” by Camilo A Molina, MD, Daniel M Sciubba, MD, Jacob K Greenberg, MD, MSCI, Majid Khan, MD, Timothy Witham, MD. Operative Neurosurgery, opaa398, https://doi.org/10.1093/ons/opaa398

2021 ◽  
Vol 20 (4) ◽  
pp. 433-433
Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 522
Author(s):  
Henrik Frisk ◽  
Eliza Lindqvist ◽  
Oscar Persson ◽  
Juliane Weinzierl ◽  
Linda K. Bruetzel ◽  
...  

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.


2020 ◽  
Author(s):  
Camilo A Molina ◽  
Daniel M Sciubba ◽  
Jacob K Greenberg ◽  
Majid Khan ◽  
Timothy Witham

Abstract BACKGROUND Augmented reality mediated spine surgery is a novel technology for spine navigation. Benchmark cadaveric data have demonstrated high accuracy and precision leading to recent regulatory approval. Absence of respiratory motion in cadaveric studies may positively bias precision and accuracy results and analogous investigations are prudent in live clinical scenarios. OBJECTIVE To report a technical note, accuracy, precision analysis of the first in-human deployment of this technology. METHODS A 78-yr-old female underwent an L4-S1 decompression, pedicle screw, and rod fixation for degenerative spine disease. Six pedicle screws were inserted via AR-HMD (xvision; Augmedics, Chicago, Illinois) navigation. Intraoperative computed tomography was used for navigation registration as well as implant accuracy and precision assessment. Clinical accuracy was graded per the Gertzbein-Robbins (GS) scale by an independent neuroradiologist. Technical precision was analyzed by comparing 3-dimensional (3D) (x, y, z) virtual implant vs real implant position coordinates and reported as linear (mm) and angular (°) deviation. Present data were compared to benchmark cadaveric data. RESULTS Clinical accuracy (per the GS grading scale) was 100%. Technical precision analysis yielded a mean linear deviation of 2.07 mm (95% CI: 1.62-2.52 mm) and angular deviation of 2.41° (95% CI: 1.57-3.25°). In comparison to prior cadaveric data (99.1%, 2.03 ± 0.99 mm, 1.41 ± 0.61°; GS accuracy 3D linear and angular deviation, respectively), the present results were not significantly different (P > .05). CONCLUSION The first in human deployment of the single Food and Drug Administration approved AR-HMD stereotactic spine navigation platform demonstrated clinical accuracy and technical precision of inserted hardware comparable to previously acquired cadaveric studies.


2011 ◽  
Vol 131 (7) ◽  
pp. 897-906
Author(s):  
Kengo Akaho ◽  
Takashi Nakagawa ◽  
Yoshihisa Yamaguchi ◽  
Katsuya Kawai ◽  
Hirokazu Kato ◽  
...  

2021 ◽  
Vol 151 ◽  
pp. 290
Author(s):  
Alexander J. Schupper ◽  
Jeremy Steinberger ◽  
Yakov Gologorsky

2020 ◽  
Author(s):  
Faiella Eliodoro ◽  
Pacella Giuseppina ◽  
Altomare Carlo ◽  
Andresciani Flavio ◽  
Zobel Beomonte Bruno ◽  
...  

2021 ◽  
Vol 11 (5) ◽  
pp. 2315
Author(s):  
Yu-Cheng Lo ◽  
Guan-An Chen ◽  
Yin Chun Liu ◽  
Yuan-Hou Chen ◽  
Jui-Ting Hsu ◽  
...  

To improve the accuracy of bracket placement in vivo, a protocol and device were introduced, which consisted of operative procedures for accurate control, a computer-aided design, and an augmented reality–assisted bracket navigation system. The present study evaluated the accuracy of this protocol. Methods: Thirty-one incisor teeth were tested from four participators. The teeth were bonded by novice and expert orthodontists. Compared with the control group by Boone gauge and the experiment group by augmented reality-assisted bracket navigation system, our study used for brackets measurement. To evaluate the accuracy, deviations of positions for bracket placement were measured. Results: The augmented reality-assisted bracket navigation system and control group were used in the same 31 cases. The priority of bonding brackets between control group or experiment group was decided by tossing coins, and then the teeth were debonded and the other technique was used. The medium vertical (incisogingival) position deviation in the control and AR groups by the novice orthodontist was 0.90 ± 0.06 mm and 0.51 ± 0.24 mm, respectively (p < 0.05), and by the expert orthodontist was 0.40 ± 0.29 mm and 0.29 ± 0.08 mm, respectively (p < 0.05). No significant changes in the horizontal position deviation were noted regardless of the orthodontist experience or use of the augmented reality–assisted bracket navigation system. Conclusion: The augmented reality–assisted bracket navigation system increased the accuracy rate by the expert orthodontist in the incisogingival direction and helped the novice orthodontist guide the bracket position within an acceptable clinical error of approximately 0.5 mm.


2012 ◽  
Vol 180 (2) ◽  
pp. 43-54 ◽  
Author(s):  
Kengo Akaho ◽  
Takashi Nakagawa ◽  
Yoshihisa Yamaguchi ◽  
Katsuya Kawai ◽  
Hirokazu Kato ◽  
...  

2021 ◽  
pp. 1-19
Author(s):  
Eimei Oyama ◽  
Kohei Tokoi ◽  
Ryo Suzuki ◽  
Sousuke Nakamura ◽  
Naoji Shiroma ◽  
...  

Spine ◽  
2018 ◽  
Vol 43 (22) ◽  
pp. E1329-E1333 ◽  
Author(s):  
Jingwei Zhao ◽  
Yajun Liu ◽  
Mingxing Fan ◽  
Bo Liu ◽  
Da He ◽  
...  

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