Barbara Carl1, Miriam Bopp2, Benjamin Saß3, Christopher Nimsky2. 1. Department of Neurosurgery, University Marburg, Marburg, Germany. Electronic address: carlb@med.uni-marburg.de. 2. Department of Neurosurgery, University Marburg, Marburg, Germany; Marburg Center for Mind, Brain and Behavior (MCMBB), Marburg, Germany. 3. Department of Neurosurgery, University Marburg, Marburg, Germany.
Abstract
OBJECTIVE: To establish microscope-based augmented reality (AR) support for degenerative spine surgery. METHODS: Head-up displays of operating microscopes were used to establish AR in a series of 10 patients. Segmentation of the vertebra and additional target structures, which were visualized by AR, was based on preoperative magnetic resonance and computed tomography (CT) images, that were nonrigidly fused to low-dose intraoperative CT (iCT) data. AR registration was achieved by automatic registration applying iCT and microscope calibration. RESULTS: AR support could be smoothly implemented in the surgical workflow. AR allowed to visualize the target structures reliably in the surgical field, facilitating surgical orientation. Flexible placement of the reference array enabled AR implementation for anterior, lateral, posterior median, and posterior paramedian approaches. Identification of bony and artificial landmarks allowed validating registration accuracy; the measured target registration error was 1.11 ± 0.42 mm (mean ± standard deviation). The effective dose for registration scanning ranged from 0.52 to 8.71 mSv, which is on average about one-third of a standard diagnostic spine scan. This depended mainly on the scan length (mean scan length cervical/thoracic/lumbar: 99/218/118 mm). Longest scan ranges were in the mid-thoracic region to ensure unambiguous vertebra assignment as prerequisite for reliable nonlinear registration (mean cervical/thoracic/lumbar effective dose: 0.52/6.14/2.99 mSv). CONCLUSIONS: Reliable microscope-based AR support is possible because of automatic registration based on intraoperative imaging. Application of AR in degenerative spine surgery has a big potential; it might be especially helpful in complex anatomical situations and resident education.
OBJECTIVE: To establish microscope-based augmented reality (AR) support for degenerative spine surgery. METHODS: Head-up displays of operating microscopes were used to establish AR in a series of 10 patients. Segmentation of the vertebra and additional target structures, which were visualized by AR, was based on preoperative magnetic resonance and computed tomography (CT) images, that were nonrigidly fused to low-dose intraoperative CT (iCT) data. AR registration was achieved by automatic registration applying iCT and microscope calibration. RESULTS:AR support could be smoothly implemented in the surgical workflow. AR allowed to visualize the target structures reliably in the surgical field, facilitating surgical orientation. Flexible placement of the reference array enabled AR implementation for anterior, lateral, posterior median, and posterior paramedian approaches. Identification of bony and artificial landmarks allowed validating registration accuracy; the measured target registration error was 1.11 ± 0.42 mm (mean ± standard deviation). The effective dose for registration scanning ranged from 0.52 to 8.71 mSv, which is on average about one-third of a standard diagnostic spine scan. This depended mainly on the scan length (mean scan length cervical/thoracic/lumbar: 99/218/118 mm). Longest scan ranges were in the mid-thoracic region to ensure unambiguous vertebra assignment as prerequisite for reliable nonlinear registration (mean cervical/thoracic/lumbar effective dose: 0.52/6.14/2.99 mSv). CONCLUSIONS: Reliable microscope-based AR support is possible because of automatic registration based on intraoperative imaging. Application of AR in degenerative spine surgery has a big potential; it might be especially helpful in complex anatomical situations and resident education.
Authors: Andrew Hersh; Smruti Mahapatra; Carly Weber-Levine; Tolulope Awosika; John N Theodore; Hesham M Zakaria; Ann Liu; Timothy F Witham; Nicholas Theodore Journal: HSS J Date: 2021-07-14
Authors: Ibrahim Hussain; Murat Cosar; Sertac Kirnaz; Franziska A Schmidt; Christoph Wipplinger; Taylor Wong; Roger Härtl Journal: Global Spine J Date: 2020-05-28