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A Low-Cost iPhone-Assisted Augmented Reality Solution for the Localization of Intracranial Lesions

BACKGROUND: Precise location of intracranial lesions before surgery is important, but occasionally difficult. Modern navigation systems are very helpful, but expensive. A low-cost solution that could locate brain lesions and their surface projections in augmented reality would be beneficial. We used...

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Autores principales: Hou, YuanZheng, Ma, LiChao, Zhu, RuYuan, Chen, XiaoLei, Zhang, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959690/
https://www.ncbi.nlm.nih.gov/pubmed/27454518
http://dx.doi.org/10.1371/journal.pone.0159185
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author Hou, YuanZheng
Ma, LiChao
Zhu, RuYuan
Chen, XiaoLei
Zhang, Jun
author_facet Hou, YuanZheng
Ma, LiChao
Zhu, RuYuan
Chen, XiaoLei
Zhang, Jun
author_sort Hou, YuanZheng
collection PubMed
description BACKGROUND: Precise location of intracranial lesions before surgery is important, but occasionally difficult. Modern navigation systems are very helpful, but expensive. A low-cost solution that could locate brain lesions and their surface projections in augmented reality would be beneficial. We used an iPhone to partially achieve this goal, and evaluated its accuracy and feasibility in a clinical neurosurgery setting. METHODOLOGY/PRINCIPAL FINDINGS: We located brain lesions in 35 patients, and using an iPhone, we depicted the lesion’s surface projection onto the skin of the head. To assess the accuracy of this method, we pasted computed tomography (CT) markers surrounding the depicted lesion boundaries on the skin onto 15 patients. CT scans were then performed with or without contrast enhancement. The deviations (D) between the CT markers and the actual lesion boundaries were measured. We found that 97.7% of the markers displayed a high accuracy level (D ≤ 5mm). In the remaining 20 patients, we compared our iPhone-based method with a frameless neuronavigation system. Four check points were chosen on the skin surrounding the depicted lesion boundaries, to assess the deviations between the two methods. The integrated offset was calculated according to the deviations at the four check points. We found that for the supratentorial lesions, the medial offset between these two methods was 2.90 mm and the maximum offset was 4.2 mm. CONCLUSIONS/SIGNIFICANCE: This low-cost, image-based, iPhone-assisted, augmented reality solution is technically feasible, and helpful for the localization of some intracranial lesions, especially shallow supratentorial intracranial lesions of moderate size.
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spelling pubmed-49596902016-08-08 A Low-Cost iPhone-Assisted Augmented Reality Solution for the Localization of Intracranial Lesions Hou, YuanZheng Ma, LiChao Zhu, RuYuan Chen, XiaoLei Zhang, Jun PLoS One Research Article BACKGROUND: Precise location of intracranial lesions before surgery is important, but occasionally difficult. Modern navigation systems are very helpful, but expensive. A low-cost solution that could locate brain lesions and their surface projections in augmented reality would be beneficial. We used an iPhone to partially achieve this goal, and evaluated its accuracy and feasibility in a clinical neurosurgery setting. METHODOLOGY/PRINCIPAL FINDINGS: We located brain lesions in 35 patients, and using an iPhone, we depicted the lesion’s surface projection onto the skin of the head. To assess the accuracy of this method, we pasted computed tomography (CT) markers surrounding the depicted lesion boundaries on the skin onto 15 patients. CT scans were then performed with or without contrast enhancement. The deviations (D) between the CT markers and the actual lesion boundaries were measured. We found that 97.7% of the markers displayed a high accuracy level (D ≤ 5mm). In the remaining 20 patients, we compared our iPhone-based method with a frameless neuronavigation system. Four check points were chosen on the skin surrounding the depicted lesion boundaries, to assess the deviations between the two methods. The integrated offset was calculated according to the deviations at the four check points. We found that for the supratentorial lesions, the medial offset between these two methods was 2.90 mm and the maximum offset was 4.2 mm. CONCLUSIONS/SIGNIFICANCE: This low-cost, image-based, iPhone-assisted, augmented reality solution is technically feasible, and helpful for the localization of some intracranial lesions, especially shallow supratentorial intracranial lesions of moderate size. Public Library of Science 2016-07-25 /pmc/articles/PMC4959690/ /pubmed/27454518 http://dx.doi.org/10.1371/journal.pone.0159185 Text en © 2016 Hou et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hou, YuanZheng
Ma, LiChao
Zhu, RuYuan
Chen, XiaoLei
Zhang, Jun
A Low-Cost iPhone-Assisted Augmented Reality Solution for the Localization of Intracranial Lesions
title A Low-Cost iPhone-Assisted Augmented Reality Solution for the Localization of Intracranial Lesions
title_full A Low-Cost iPhone-Assisted Augmented Reality Solution for the Localization of Intracranial Lesions
title_fullStr A Low-Cost iPhone-Assisted Augmented Reality Solution for the Localization of Intracranial Lesions
title_full_unstemmed A Low-Cost iPhone-Assisted Augmented Reality Solution for the Localization of Intracranial Lesions
title_short A Low-Cost iPhone-Assisted Augmented Reality Solution for the Localization of Intracranial Lesions
title_sort low-cost iphone-assisted augmented reality solution for the localization of intracranial lesions
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959690/
https://www.ncbi.nlm.nih.gov/pubmed/27454518
http://dx.doi.org/10.1371/journal.pone.0159185
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