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Artificial Intelligence in Health Artificial intelligence app for EVD navigation

single custom application that can perform EVD navigation Writing–review & editing: Andrew Abumoousa, Carolyn
on an iOS device at the bedside. This approach facilitates Quinsey, Sivakumar Jaikumar
navigation by neurosurgical providers without requiring
complex setups that delay urgent or emergent patient care. Ethics approval and consent to participate
Our data demonstrate that such an endeavor is feasible, Not applicable.
with the custom iOS application achieving high accuracy
and near-instantaneous results. Consent for publication
The development of a handheld iOS application Not applicable.
for neurosurgical navigation represents a promising
advancement in the field. Importantly, its greatest value Availability of data
is likely not for seasoned neurosurgeons who routinely Data are available from the corresponding author upon
perform EVD placements, but for those with less frequent reasonable request.
exposure—such as residents, junior faculty, or providers
who take call infrequently. By offering real-time, AR-based References
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CT in cadaveric and clinical studies, early data suggest that 4. Rahmathulla G, Nottmeier EW, Pirris SM, Deen HG,
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Acknowledgments
doi: 10.3171/2014.1.FOCUS13516
We would like to thank Xian Boles for assistance with 5. Moiraghi A, Pallud J. Intraoperative ultrasound techniques
figure illustration and 3D modeling.
for cerebral gliomas resection: Usefulness and pitfalls. Ann
Funding Transl Med. 2020;8(8):523.
doi: 10.21037/atm.2020.03.178
This work was graciously funded by UNC Health’s
Innovation Pilot Grant (Grant no.: 29201). 6. Khoshnevisan A, Allahabadi NS. Neuronavigation:
Principles, clinical applications and potential pitfalls. Iran J
Conflict of interest Psychiatry. 2012;7(2):97-103.
The authors declare they have no competing interests. 7. Harwick E, Singhal I, Conway B, Mueller W, Treffy R,
Krucoff MO. Pinless electromagnetic neuronavigation
Author contributions during awake craniotomies: Technical pearls, pitfalls, and
nuances. World Neurosurg. 2023;175:e159-e166.
Conceptualization: Andrew Abumoussa, Sivakumar doi: 10.1016/j.wneu.2023.03.045
Jaikumar, Carolyn Quinsey
Formal analysis: Andrew Abumoussa, Benjamin Succop, 8. Anwar SM, Majid M, Qayyum A, Awais M, Alnowami M,
Yueh Lee Khan MK. Medical image analysis using convolutional
Investigation: Andrew Abumoussa, Benjamin Succop neural networks: A review. J Med Syst. 2018;42:226.
Methodology: Andrew Abumoussa, Benjamin Succop, doi: 10.1007/s10916-018-1088-1
Yueh Lee 9. Ronneberger O, Fischer P, Brox T. U-net: Convolutional
Software: Andrew Abumoussa Networks for Biomedical Image Segmentation. Berlin:
Writing–original draft: Benjamin Succop Springer; 2015. p. 234-241.

Volume 2 Issue 4 (2025) 136 doi: 10.36922/aih.8195