Navigation of frameless fixation for gamma knife radiosurgery using fixed augmented reality

Abstract

Augmented reality (AR) offers a new medical treatment approach. We aimed to evaluate frameless (mask) fixation navigation using a 3D-printed patient model with fixed-AR technology for gamma knife radiosurgery (GKRS). Fixed-AR navigation was developed using the inside-out method with visual inertial odometry algorithms, and the flexible Quick Response marker was created for object-feature recognition. Virtual 3D-patient models for AR-rendering were created via 3D-scanning utilizing TrueDepth and cone-beam computed tomography (CBCT) to generate a new GammaKnife Icon™ model. A 3D-printed patient model included fiducial markers, and virtual 3D-patient models were used to validate registration accuracy. Registration accuracy between initial frameless fixation and re-fixation navigated fixed-AR was validated through visualization and quantitative method. The quantitative method was validated through set-up errors, fiducial marker coordinates, and high-definition motion management (HDMM) values. A 3D-printed model and virtual models were correctly overlapped under frameless fixation. Virtual models from both 3D-scanning and CBCT were enough to tolerate the navigated frameless re-fixation. Although the CBCT virtual model consistently delivered more accurate results, 3D-scanning was sufficient. Frameless re-fixation accuracy navigated in virtual models had mean set-up errors within 1 mm and 1.5° in all axes. Mean fiducial marker differences from coordinates in virtual models were within 2.5 mm in all axes, and mean 3D errors were within 3 mm. Mean HDMM difference values in virtual models were within 1.5 mm of initial HDMM values. The variability from navigation fixed-AR is enough to consider repositioning frameless fixation without CBCT scanning for treating patients fractionated with large multiple metastases lesions (> 3 cm) who have difficulty enduring long beam-on time. This system could be applied to novel GKRS navigation for frameless fixation with reduced preparation time.

Simulation of Spinal Cord Reflexes

“…The knowledge from references [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] with their applications helped us to gain experience with the simulation environment. The knowledge from [21][22][23][24][25][26][27][28][29][30][31][32][33][34] made us aware of the neuroscience domain. Recent research [32][33][34] published in IEEE journals shows us that software simulations and system modeling are not only useful but a regular procedure in medical practice and rehabilitation.…”

Augmented Reality in Stereotactic Neurosurgery: Current Status and Issues

“…8,10,13,15) Researchers have applied ARN in various neurosurgical procedures, including brain tumor surgery, cerebrovascular surgery, ventriculostomy and neuroendoscopic surgery, spine surgery, and stereotactic radiosurgery, verifying these unique features of ARN that better support surgeons intraoperatively. 3,13,[16][17][18] ARN has also been applied in surgical training, resident education, and patient education. 19,20)…”

Augmented Reality (AR) for Surgical Robotic and Autonomous Systems: State of the Art, Challenges, and Solutions

“…In the existing literature, a multitude of haptic sensors have been proposed to enable high-speed performance in data pre-processing and rendering. The stereotaxy phenomena in surgical scenarios such as gamma-knife surgeries [146] create an illusion of registered and reproduced 3D haptic feedback data in the form of a sensory stimulus. In a paper by Srinivasan et al [147], the effect of visually locating markers was investigated, which allowed a correlation to be made between the perception feedback of the cues and the actual haptic feedback obtained from an object.…”