Enkaoua, Aure;
Islam, Mobarakol;
Ramalhinho, João;
Dowrick, Thomas;
Booker, James;
Khan, Danyal Z;
Marcus, Hani J;
(2023)
Image-guidance in endoscopic pituitary surgery: an in-silico study of errors involved in tracker-based techniques.
Frontiers in Surgery
, 10
, Article 1222859. 10.3389/fsurg.2023.1222859.
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Abstract
Background: Endoscopic endonasal surgery is an established minimally invasive technique for resecting pituitary adenomas. However, understanding orientation and identifying critical neurovascular structures in this anatomically dense region can be challenging. In clinical practice, commercial navigation systems use a tracked pointer for guidance. Augmented Reality (AR) is an emerging technology used for surgical guidance. It can be tracker based or vision based, but neither is widely used in pituitary surgery. Methods: This pre-clinical study aims to assess the accuracy of tracker-based navigation systems, including those that allow for AR. Two setups were used to conduct simulations: (1) the standard pointer setup, tracked by an infrared camera; and (2) the endoscope setup that allows for AR, using reflective markers on the end of the endoscope, tracked by infrared cameras. The error sources were estimated by calculating the Euclidean distance between a point’s true location and the point’s location after passing it through the noisy system. A phantom study was then conducted to verify the in-silico simulation results and show a working example of image-based navigation errors in current methodologies. Results: The errors of the tracked pointer and tracked endoscope simulations were 1.7 and 2.5 mm respectively. The phantom study showed errors of 2.14 and 3.21 mm for the tracked pointer and tracked endoscope setups respectively. Discussion: In pituitary surgery, precise neighboring structure identification is crucial for success. However, our simulations reveal that the errors of tracked approaches were too large to meet the fine error margins required for pituitary surgery. In order to achieve the required accuracy, we would need much more accurate tracking, better calibration and improved registration techniques.
| Type: | Article |
|---|---|
| Title: | Image-guidance in endoscopic pituitary surgery: an in-silico study of errors involved in tracker-based techniques |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3389/fsurg.2023.1222859 |
| Publisher version: | https://doi.org/10.3389/fsurg.2023.1222859 |
| Language: | English |
| Additional information: | © 2023 Enkaoua, Islam, Ramalhinho, Dowrick, Booker, Khan, Marcus and Clarkson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
| Keywords: | augmented reality, pituitary surgery, computer-assisted surgery, tracking, neurosurgery |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10178127 |
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