Jacob Gibby1,2, Steve Cvetko3, Ramin Javan4, Ryan Parr5, Wendell Gibby3,6,7. 1. George Washington University School of Medicine and Health Sciences, Washington, DC, 20052, USA. 2. Kaweah Delta Health Care District, 400 W Mineral King Ave, Visalia, CA, 93291, USA. 3. Novarad Corporation, 752 E 1180 S, American Fork, UT, 84003, USA. 4. George Washington University School Of Medicine and Health Sciences, Department of Radiology, Washington, DC, 20052, USA. 5. Novarad Corporation, 752 E 1180 S, American Fork, UT, 84003, USA. ryan.parr@novarad.net. 6. Riverwoods Advanced Imaging, Blue Rock Medical Center, 3152 N University Ave, Provo, UT, 84604, USA. 7. University of California San Diego, Department of Radiology, San Diego, CA, 92093, USA.
Abstract
PURPOSE: Because of its ability to superimpose imaging data on a patient, while anchoring the user's view to the immediate surroundings, augmented reality (AR) has the potential to dramatically improve the accuracy and reduce the time required for preoperative planning and performance of minimally invasive spine surgeries and procedures. Described and reported herein is the direct clinical application of AR navigation on a series of common percutaneous image-guided spine procedures. MATERIALS AND METHODS: AR, including a "virtual needle" (VN) asset, was used to guide and navigate a total of 18 procedures performed on 10 patients. Comparative control data were generated using a phantom model (n = 32). These data are used to determine the accuracy of AR for federal drug administration submissions. Optical codes were implemented to allow automatic and real-time registration. A manual process was used when the use of optical codes was not available. Target error, distance to the target and target size were measured for both phantom and clinical groups. Mean errors between the two groups were compared. RESULTS: Target error between the control and clinical data sets showed no significant difference. Moreover, the distance to the target site and the target size had no effect on target acquisition. CONCLUSIONS: This data set suggests that AR navigation, utilizing a VN, is an emerging, accurate, valuable additive method for surgical and procedural planning for percutaneous image-guided spinal procedures and has potential to be applied to a broad range of clinical and surgical applications.
PURPOSE: Because of its ability to superimpose imaging data on a patient, while anchoring the user's view to the immediate surroundings, augmented reality (AR) has the potential to dramatically improve the accuracy and reduce the time required for preoperative planning and performance of minimally invasive spine surgeries and procedures. Described and reported herein is the direct clinical application of AR navigation on a series of common percutaneous image-guided spine procedures. MATERIALS AND METHODS: AR, including a "virtual needle" (VN) asset, was used to guide and navigate a total of 18 procedures performed on 10 patients. Comparative control data were generated using a phantom model (n = 32). These data are used to determine the accuracy of AR for federal drug administration submissions. Optical codes were implemented to allow automatic and real-time registration. A manual process was used when the use of optical codes was not available. Target error, distance to the target and target size were measured for both phantom and clinical groups. Mean errors between the two groups were compared. RESULTS: Target error between the control and clinical data sets showed no significant difference. Moreover, the distance to the target site and the target size had no effect on target acquisition. CONCLUSIONS: This data set suggests that AR navigation, utilizing a VN, is an emerging, accurate, valuable additive method for surgical and procedural planning for percutaneous image-guided spinal procedures and has potential to be applied to a broad range of clinical and surgical applications.
Authors: Christopher M Andrews; Alexander B Henry; Ignacio M Soriano; Michael K Southworth; Jonathan R Silva Journal: IEEE J Transl Eng Health Med Date: 2020-12-17 Impact factor: 3.316