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Robust presurgical functional MRI at 7 T using response consistency

Functional MRI is valuable in presurgical planning due to its non‐invasive nature, repeatability, and broad availability. Using ultra‐high field MRI increases the specificity and sensitivity, increasing the localization reliability and reducing scan time. Ideally, fMRI analysis for this application...

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Autores principales: Lima Cardoso, Pedro, Fischmeister, Florian Ph. S., Dymerska, Barbara, Geißler, Alexander, Wurnig, Moritz, Trattnig, Siegfried, Beisteiner, Roland, Robinson, Simon Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5434844/
https://www.ncbi.nlm.nih.gov/pubmed/28321965
http://dx.doi.org/10.1002/hbm.23582
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author Lima Cardoso, Pedro
Fischmeister, Florian Ph. S.
Dymerska, Barbara
Geißler, Alexander
Wurnig, Moritz
Trattnig, Siegfried
Beisteiner, Roland
Robinson, Simon Daniel
author_facet Lima Cardoso, Pedro
Fischmeister, Florian Ph. S.
Dymerska, Barbara
Geißler, Alexander
Wurnig, Moritz
Trattnig, Siegfried
Beisteiner, Roland
Robinson, Simon Daniel
author_sort Lima Cardoso, Pedro
collection PubMed
description Functional MRI is valuable in presurgical planning due to its non‐invasive nature, repeatability, and broad availability. Using ultra‐high field MRI increases the specificity and sensitivity, increasing the localization reliability and reducing scan time. Ideally, fMRI analysis for this application should identify unreliable runs and work even if the patient deviates from the prescribed task timing or if there are changes to the hemodynamic response due to pathology. In this study, a model‐free analysis method—UNBIASED—based on the consistency of fMRI responses over runs was applied, to ultra‐high field fMRI localizations of the hand area. Ten patients with brain tumors and epilepsy underwent 7 Tesla fMRI with multiple runs of a hand motor task in a block design. FMRI data were analyzed with the proposed approach (UNBIASED) and the conventional General Linear Model (GLM) approach. UNBIASED correctly identified and excluded fMRI runs that contained little or no activation. Generally, less motion artifact contamination was present in UNBIASED than in GLM results. Some cortical regions were identified as activated in UNBIASED but not GLM results. These were confirmed to show reproducible delayed or transient activation, which was time‐locked to the task. UNBIASED is a robust approach to generating activation maps without the need for assumptions about response timing or shape. In presurgical planning, UNBIASED can complement model‐based methods to aid surgeons in making prudent choices about optimal surgical access and resection margins for each patient, even if the hemodynamic response is modified by pathology. Hum Brain Mapp 38:3163–3174, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
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spelling pubmed-54348442017-06-01 Robust presurgical functional MRI at 7 T using response consistency Lima Cardoso, Pedro Fischmeister, Florian Ph. S. Dymerska, Barbara Geißler, Alexander Wurnig, Moritz Trattnig, Siegfried Beisteiner, Roland Robinson, Simon Daniel Hum Brain Mapp Research Articles Functional MRI is valuable in presurgical planning due to its non‐invasive nature, repeatability, and broad availability. Using ultra‐high field MRI increases the specificity and sensitivity, increasing the localization reliability and reducing scan time. Ideally, fMRI analysis for this application should identify unreliable runs and work even if the patient deviates from the prescribed task timing or if there are changes to the hemodynamic response due to pathology. In this study, a model‐free analysis method—UNBIASED—based on the consistency of fMRI responses over runs was applied, to ultra‐high field fMRI localizations of the hand area. Ten patients with brain tumors and epilepsy underwent 7 Tesla fMRI with multiple runs of a hand motor task in a block design. FMRI data were analyzed with the proposed approach (UNBIASED) and the conventional General Linear Model (GLM) approach. UNBIASED correctly identified and excluded fMRI runs that contained little or no activation. Generally, less motion artifact contamination was present in UNBIASED than in GLM results. Some cortical regions were identified as activated in UNBIASED but not GLM results. These were confirmed to show reproducible delayed or transient activation, which was time‐locked to the task. UNBIASED is a robust approach to generating activation maps without the need for assumptions about response timing or shape. In presurgical planning, UNBIASED can complement model‐based methods to aid surgeons in making prudent choices about optimal surgical access and resection margins for each patient, even if the hemodynamic response is modified by pathology. Hum Brain Mapp 38:3163–3174, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. John Wiley and Sons Inc. 2017-03-21 /pmc/articles/PMC5434844/ /pubmed/28321965 http://dx.doi.org/10.1002/hbm.23582 Text en © 2017 Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Lima Cardoso, Pedro
Fischmeister, Florian Ph. S.
Dymerska, Barbara
Geißler, Alexander
Wurnig, Moritz
Trattnig, Siegfried
Beisteiner, Roland
Robinson, Simon Daniel
Robust presurgical functional MRI at 7 T using response consistency
title Robust presurgical functional MRI at 7 T using response consistency
title_full Robust presurgical functional MRI at 7 T using response consistency
title_fullStr Robust presurgical functional MRI at 7 T using response consistency
title_full_unstemmed Robust presurgical functional MRI at 7 T using response consistency
title_short Robust presurgical functional MRI at 7 T using response consistency
title_sort robust presurgical functional mri at 7 t using response consistency
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5434844/
https://www.ncbi.nlm.nih.gov/pubmed/28321965
http://dx.doi.org/10.1002/hbm.23582
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