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Iterative analysis of cerebrovascular reactivity dynamic response by temporal decomposition

OBJECTIVE: To improve quantitative cerebrovascular reactivity (CVR) measurements and CO (2) arrival times, we present an iterative analysis capable of decomposing different temporal components of the dynamic carbon dioxide‐ Blood Oxygen‐Level Dependent (CO (2)‐BOLD) relationship. EXPERIMENTAL DESIGN...

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Autores principales: van Niftrik, Christiaan Hendrik Bas, Piccirelli, Marco, Bozinov, Oliver, Pangalu, Athina, Fisher, Joseph A., Valavanis, Antonios, Luft, Andreas R., Weller, Michael, Regli, Luca, Fierstra, Jorn
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/PMC5607533/
https://www.ncbi.nlm.nih.gov/pubmed/28948064
http://dx.doi.org/10.1002/brb3.705
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author van Niftrik, Christiaan Hendrik Bas
Piccirelli, Marco
Bozinov, Oliver
Pangalu, Athina
Fisher, Joseph A.
Valavanis, Antonios
Luft, Andreas R.
Weller, Michael
Regli, Luca
Fierstra, Jorn
author_facet van Niftrik, Christiaan Hendrik Bas
Piccirelli, Marco
Bozinov, Oliver
Pangalu, Athina
Fisher, Joseph A.
Valavanis, Antonios
Luft, Andreas R.
Weller, Michael
Regli, Luca
Fierstra, Jorn
author_sort van Niftrik, Christiaan Hendrik Bas
collection PubMed
description OBJECTIVE: To improve quantitative cerebrovascular reactivity (CVR) measurements and CO (2) arrival times, we present an iterative analysis capable of decomposing different temporal components of the dynamic carbon dioxide‐ Blood Oxygen‐Level Dependent (CO (2)‐BOLD) relationship. EXPERIMENTAL DESIGN: Decomposition of the dynamic parameters included a redefinition of the voxel‐wise CO (2) arrival time, and a separation from the vascular response to a stepwise increase in CO (2) (Delay to signal Plateau – DTP) and a decrease in CO (2) (Delay to signal Baseline –DTB). Twenty‐five (normal) datasets, obtained from BOLD MRI combined with a standardized pseudo‐square wave CO (2) change, were co‐registered to generate reference atlases for the aforementioned dynamic processes to score the voxel‐by‐voxel deviation probability from normal range. This analysis is further illustrated in two subjects with unilateral carotid artery occlusion using these reference atlases. PRINCIPAL OBSERVATIONS: We have found that our redefined CO (2) arrival time resulted in the best data fit. Additionally, excluding both dynamic BOLD phases (DTP and DTB) resulted in a static CVR, that is maximal response, defined as CVR calculated only over a normocapnic and hypercapnic calibrated plateau. CONCLUSION: Decomposition and novel iterative modeling of different temporal components of the dynamic CO (2)‐BOLD relationship improves quantitative CVR measurements.
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spelling pubmed-56075332017-09-25 Iterative analysis of cerebrovascular reactivity dynamic response by temporal decomposition van Niftrik, Christiaan Hendrik Bas Piccirelli, Marco Bozinov, Oliver Pangalu, Athina Fisher, Joseph A. Valavanis, Antonios Luft, Andreas R. Weller, Michael Regli, Luca Fierstra, Jorn Brain Behav Original Research OBJECTIVE: To improve quantitative cerebrovascular reactivity (CVR) measurements and CO (2) arrival times, we present an iterative analysis capable of decomposing different temporal components of the dynamic carbon dioxide‐ Blood Oxygen‐Level Dependent (CO (2)‐BOLD) relationship. EXPERIMENTAL DESIGN: Decomposition of the dynamic parameters included a redefinition of the voxel‐wise CO (2) arrival time, and a separation from the vascular response to a stepwise increase in CO (2) (Delay to signal Plateau – DTP) and a decrease in CO (2) (Delay to signal Baseline –DTB). Twenty‐five (normal) datasets, obtained from BOLD MRI combined with a standardized pseudo‐square wave CO (2) change, were co‐registered to generate reference atlases for the aforementioned dynamic processes to score the voxel‐by‐voxel deviation probability from normal range. This analysis is further illustrated in two subjects with unilateral carotid artery occlusion using these reference atlases. PRINCIPAL OBSERVATIONS: We have found that our redefined CO (2) arrival time resulted in the best data fit. Additionally, excluding both dynamic BOLD phases (DTP and DTB) resulted in a static CVR, that is maximal response, defined as CVR calculated only over a normocapnic and hypercapnic calibrated plateau. CONCLUSION: Decomposition and novel iterative modeling of different temporal components of the dynamic CO (2)‐BOLD relationship improves quantitative CVR measurements. John Wiley and Sons Inc. 2017-07-26 /pmc/articles/PMC5607533/ /pubmed/28948064 http://dx.doi.org/10.1002/brb3.705 Text en © 2017 The Authors. Brain and Behavior published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution (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 Original Research
van Niftrik, Christiaan Hendrik Bas
Piccirelli, Marco
Bozinov, Oliver
Pangalu, Athina
Fisher, Joseph A.
Valavanis, Antonios
Luft, Andreas R.
Weller, Michael
Regli, Luca
Fierstra, Jorn
Iterative analysis of cerebrovascular reactivity dynamic response by temporal decomposition
title Iterative analysis of cerebrovascular reactivity dynamic response by temporal decomposition
title_full Iterative analysis of cerebrovascular reactivity dynamic response by temporal decomposition
title_fullStr Iterative analysis of cerebrovascular reactivity dynamic response by temporal decomposition
title_full_unstemmed Iterative analysis of cerebrovascular reactivity dynamic response by temporal decomposition
title_short Iterative analysis of cerebrovascular reactivity dynamic response by temporal decomposition
title_sort iterative analysis of cerebrovascular reactivity dynamic response by temporal decomposition
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5607533/
https://www.ncbi.nlm.nih.gov/pubmed/28948064
http://dx.doi.org/10.1002/brb3.705
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