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Augmented Reality-based Contextual Guidance through Surgical Tool Tracking in Neurosurgery.

Publication ,  Journal Article
Eom, S; Kim, S; Jackson, J; Sykes, D; Rahimpour, S; Gorlatova, M
Published in: IEEE transactions on visualization and computer graphics
April 2024

External ventricular drain (EVD) is a common, yet challenging neurosurgical procedure of placing a catheter into the brain ventricular system that requires prolonged training for surgeons to improve the catheter placement accuracy. In this paper, we introduce NeuroLens, an Augmented Reality (AR) system that provides neurosurgeons with guidance that aides them in completing an EVD catheter placement. NeuroLens builds on prior work in AR-assisted EVD to present a registered hologram of a patient's ventricles to the surgeons, and uniquely incorporates guidance on the EVD catheter's trajectory, angle of insertion, and distance to the target. The guidance is enabled by tracking the EVD catheter. We evaluate NeuroLens via a study with 33 medical students and 9 neurosurgeons, in which we analyzed participants' EVD catheter insertion accuracy and completion time, eye gaze patterns, and qualitative responses. Our study, in which NeuroLens was used to aid students and surgeons in inserting an EVD catheter into a realistic phantom model of a human head, demonstrated the potential of NeuroLens as a tool that will aid and educate novice neurosurgeons. On average, the use of NeuroLens improved the EVD placement accuracy of the year 1 students by 39.4%, of the year 2 -4 students by 45.7%, and of the neurosurgeons by 16.7%. Furthermore, students who focused more on NeuroLens-provided contextual guidance achieved better results, and novice surgeons improved more than the expert surgeons with NeuroLens's assistance.

Duke Scholars

Published In

IEEE transactions on visualization and computer graphics

DOI

EISSN

1941-0506

ISSN

1077-2626

Publication Date

April 2024

Volume

PP

Related Subject Headings

  • Software Engineering
  • 46 Information and computing sciences
  • 0802 Computation Theory and Mathematics
  • 0801 Artificial Intelligence and Image Processing
 

Citation

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Eom, S., Kim, S., Jackson, J., Sykes, D., Rahimpour, S., & Gorlatova, M. (2024). Augmented Reality-based Contextual Guidance through Surgical Tool Tracking in Neurosurgery. IEEE Transactions on Visualization and Computer Graphics, PP. https://doi.org/10.1109/tvcg.2024.3390680
Eom, Sangjun, Seijung Kim, Joshua Jackson, David Sykes, Shervin Rahimpour, and Maria Gorlatova. “Augmented Reality-based Contextual Guidance through Surgical Tool Tracking in Neurosurgery.IEEE Transactions on Visualization and Computer Graphics PP (April 2024). https://doi.org/10.1109/tvcg.2024.3390680.
Eom S, Kim S, Jackson J, Sykes D, Rahimpour S, Gorlatova M. Augmented Reality-based Contextual Guidance through Surgical Tool Tracking in Neurosurgery. IEEE transactions on visualization and computer graphics. 2024 Apr;PP.
Eom, Sangjun, et al. “Augmented Reality-based Contextual Guidance through Surgical Tool Tracking in Neurosurgery.IEEE Transactions on Visualization and Computer Graphics, vol. PP, Apr. 2024. Epmc, doi:10.1109/tvcg.2024.3390680.
Eom S, Kim S, Jackson J, Sykes D, Rahimpour S, Gorlatova M. Augmented Reality-based Contextual Guidance through Surgical Tool Tracking in Neurosurgery. IEEE transactions on visualization and computer graphics. 2024 Apr;PP.

Published In

IEEE transactions on visualization and computer graphics

DOI

EISSN

1941-0506

ISSN

1077-2626

Publication Date

April 2024

Volume

PP

Related Subject Headings

  • Software Engineering
  • 46 Information and computing sciences
  • 0802 Computation Theory and Mathematics
  • 0801 Artificial Intelligence and Image Processing