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Real‐time trajectory guide tracking for intraoperative MRI‐guided neurosurgery
PURPOSE: In current intraoperative MRI (IMRI) methods, an iterative approach is used to aim trajectory guides at intracerebral targets: image MR‐visible features, determine current aim by fitting model to image, manipulate device, repeat. Infrequent updates are produced by such methods, compared to...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9930741/ https://www.ncbi.nlm.nih.gov/pubmed/36128887 http://dx.doi.org/10.1002/mrm.29426 |
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author | Olsen, Miles E. Brodsky, Ethan K. Oler, Jonathan A. Riedel, Marissa K. Mueller, Sascha A. L. Vermilyea, Scott C. Metzger, Jeanette M. Tao, Yunlong Brunner, Kevin G. Ahmed, Azam S. Zhang, Su‐Chun Emborg, Marina E. Kalin, Ned H. Block, Walter F. |
author_facet | Olsen, Miles E. Brodsky, Ethan K. Oler, Jonathan A. Riedel, Marissa K. Mueller, Sascha A. L. Vermilyea, Scott C. Metzger, Jeanette M. Tao, Yunlong Brunner, Kevin G. Ahmed, Azam S. Zhang, Su‐Chun Emborg, Marina E. Kalin, Ned H. Block, Walter F. |
author_sort | Olsen, Miles E. |
collection | PubMed |
description | PURPOSE: In current intraoperative MRI (IMRI) methods, an iterative approach is used to aim trajectory guides at intracerebral targets: image MR‐visible features, determine current aim by fitting model to image, manipulate device, repeat. Infrequent updates are produced by such methods, compared to rapid optically tracked stereotaxy used in the operating room. Our goal was to develop a real‐time interactive IMRI method for aiming. METHODS: The current trajectory was computed from two points along the guide's central axis, rather than by imaging the entire device. These points were determined by correlating one‐dimensional spokes from a radial sequence with the known cross‐sectional projection of the guide. The real‐time platform RTHawk was utilized to control MR sequences and data acquisition. On‐screen updates were viewed by the operator while simultaneously manipulating the guide to align it with the planned trajectory. Accuracy was quantitated in a phantom, and in vivo validation was demonstrated in nonhuman primates undergoing preclinical gene ([Formula: see text]) and cell ([Formula: see text]) delivery surgeries. RESULTS: Updates were produced at 5 Hz In 10 phantom experiments at a depth of 48 mm, the cannula tip was placed with radial error of (min, mean, max) = (0.16, 0.29, 0.68) mm. Successful in vivo delivery of payloads to all 14 targets was demonstrated across nine surgeries with depths of (min, mean, max) = (33.3, 37.9, 42.5) mm. CONCLUSION: A real‐time interactive update rate was achieved, reducing operator fatigue without compromising accuracy. Qualitative interpretation of images during aiming was rendered unnecessary by objectively computing device alignment. |
format | Online Article Text |
id | pubmed-9930741 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99307412023-02-15 Real‐time trajectory guide tracking for intraoperative MRI‐guided neurosurgery Olsen, Miles E. Brodsky, Ethan K. Oler, Jonathan A. Riedel, Marissa K. Mueller, Sascha A. L. Vermilyea, Scott C. Metzger, Jeanette M. Tao, Yunlong Brunner, Kevin G. Ahmed, Azam S. Zhang, Su‐Chun Emborg, Marina E. Kalin, Ned H. Block, Walter F. Magn Reson Med Technical Notes—Imaging Methodology PURPOSE: In current intraoperative MRI (IMRI) methods, an iterative approach is used to aim trajectory guides at intracerebral targets: image MR‐visible features, determine current aim by fitting model to image, manipulate device, repeat. Infrequent updates are produced by such methods, compared to rapid optically tracked stereotaxy used in the operating room. Our goal was to develop a real‐time interactive IMRI method for aiming. METHODS: The current trajectory was computed from two points along the guide's central axis, rather than by imaging the entire device. These points were determined by correlating one‐dimensional spokes from a radial sequence with the known cross‐sectional projection of the guide. The real‐time platform RTHawk was utilized to control MR sequences and data acquisition. On‐screen updates were viewed by the operator while simultaneously manipulating the guide to align it with the planned trajectory. Accuracy was quantitated in a phantom, and in vivo validation was demonstrated in nonhuman primates undergoing preclinical gene ([Formula: see text]) and cell ([Formula: see text]) delivery surgeries. RESULTS: Updates were produced at 5 Hz In 10 phantom experiments at a depth of 48 mm, the cannula tip was placed with radial error of (min, mean, max) = (0.16, 0.29, 0.68) mm. Successful in vivo delivery of payloads to all 14 targets was demonstrated across nine surgeries with depths of (min, mean, max) = (33.3, 37.9, 42.5) mm. CONCLUSION: A real‐time interactive update rate was achieved, reducing operator fatigue without compromising accuracy. Qualitative interpretation of images during aiming was rendered unnecessary by objectively computing device alignment. John Wiley and Sons Inc. 2022-09-21 2023-02 /pmc/articles/PMC9930741/ /pubmed/36128887 http://dx.doi.org/10.1002/mrm.29426 Text en © 2022 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Technical Notes—Imaging Methodology Olsen, Miles E. Brodsky, Ethan K. Oler, Jonathan A. Riedel, Marissa K. Mueller, Sascha A. L. Vermilyea, Scott C. Metzger, Jeanette M. Tao, Yunlong Brunner, Kevin G. Ahmed, Azam S. Zhang, Su‐Chun Emborg, Marina E. Kalin, Ned H. Block, Walter F. Real‐time trajectory guide tracking for intraoperative MRI‐guided neurosurgery |
title | Real‐time trajectory guide tracking for intraoperative MRI‐guided neurosurgery |
title_full | Real‐time trajectory guide tracking for intraoperative MRI‐guided neurosurgery |
title_fullStr | Real‐time trajectory guide tracking for intraoperative MRI‐guided neurosurgery |
title_full_unstemmed | Real‐time trajectory guide tracking for intraoperative MRI‐guided neurosurgery |
title_short | Real‐time trajectory guide tracking for intraoperative MRI‐guided neurosurgery |
title_sort | real‐time trajectory guide tracking for intraoperative mri‐guided neurosurgery |
topic | Technical Notes—Imaging Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9930741/ https://www.ncbi.nlm.nih.gov/pubmed/36128887 http://dx.doi.org/10.1002/mrm.29426 |
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