A practical modification to a resting state fMRI protocol for improved characterization of cerebrovascular function

Rachael C. Stickland; Kristina M. Zvolanek; Stefano Moia; Apoorva Ayyagari; César Caballero-Gaudes; Molly G. Bright

doi:10.1016/j.neuroimage.2021.118306

A practical modification to a resting state fMRI protocol for improved characterization of cerebrovascular function

Rachael C. Stickland^*, Kristina M. Zvolanek, Stefano Moia, Apoorva Ayyagari, César Caballero-Gaudes, Molly G. Bright

^*Corresponding author for this work

Physical Therapy and Human Movement Sciences

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9 Scopus citations

Abstract

Cerebrovascular reactivity (CVR), defined here as the Blood Oxygenation Level Dependent (BOLD) response to a CO₂ pressure change, is a useful metric of cerebrovascular function. Both the amplitude and the timing (hemodynamic lag) of the CVR response can bring insight into the nature of a cerebrovascular pathology and aid in understanding noise confounds when using functional Magnetic Resonance Imaging (fMRI) to study neural activity. This research assessed a practical modification to a typical resting-state fMRI protocol, to improve the characterization of cerebrovascular function. In 9 healthy subjects, we modelled CVR and lag in three resting-state data segments, and in data segments which added a 2–3 minute breathing task to the start of a resting-state segment. Two different breathing tasks were used to induce fluctuations in arterial CO₂ pressure: a breath-hold task to induce hypercapnia (CO₂ increase) and a cued deep breathing task to induce hypocapnia (CO₂ decrease). Our analysis produced voxel-wise estimates of the amplitude (CVR) and timing (lag) of the BOLD-fMRI response to CO₂ by systematically shifting the CO₂ regressor in time to optimize the model fit. This optimization inherently increases gray matter CVR values and fit statistics. The inclusion of a simple breathing task, compared to a resting-state scan only, increases the number of voxels in the brain that have a significant relationship between CO₂ and BOLD-fMRI signals, and improves our confidence in the plausibility of voxel-wise CVR and hemodynamic lag estimates. We demonstrate the clinical utility and feasibility of this protocol in an incidental finding of Moyamoya disease, and explore the possibilities and challenges of using this protocol in younger populations. This hybrid protocol has direct applications for CVR mapping in both research and clinical settings and wider applications for fMRI denoising and interpretation.

Original language	English (US)
Article number	118306
Journal	Neuroimage
Volume	239
DOIs	https://doi.org/10.1016/j.neuroimage.2021.118306
State	Published - Oct 1 2021

Funding

This research was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health under award number K12HD073945. The pediatric dataset and cerebral palsy dataset were collected with support of National Institutes of Health award R03 HD094615–01A1. The authors would like to acknowledge Marie Wasielewski and Carson Ingo for their support in acquiring these data. K.Z. was supported by an NIH-funded training program (T32EB025766). S.M. was supported by the European Union's Horizon 2020 research and innovation program (Marie Skłodowska-Curie grant agreement No. 713673), a fellowship from La Caixa Foundation (ID 100010434, fellowship code LCF/BQ/IN17/11620063) and C.C.G was supported by the Spanish Ministry of Economy and Competitiveness (Ramon y Cajal Fellowship, RYC-2017- 21845), the Basque Government (BERC 2018–2021 and PIBA_2019_104) and the Spanish Ministry of Science, Innovation and Universities (MICINN; PID2019–105520GB-100). The authors would also like to thank Kevin Murphy for the basis of the code that creates the physiological regressors, and personnel at the Center for Translation Imaging (Northwestern Radiology) for support with study set-up. This research was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health under award number K12HD073945. The pediatric dataset and cerebral palsy dataset were collected with support of National Institutes of Health award R03 HD094615?01A1. The authors would like to acknowledge Marie Wasielewski and Carson Ingo for their support in acquiring these data. K.Z. was supported by an NIH-funded training program (T32EB025766). S.M. was supported by the European Union's Horizon 2020 research and innovation program (Marie Sk?odowska-Curie grant agreement No. 713673), a fellowship from La Caixa Foundation (ID 100010434, fellowship code LCF/BQ/IN17/11620063) and C.C.G was supported by the Spanish Ministry of Economy and Competitiveness (Ramon y Cajal Fellowship, RYC-2017- 21845), the Basque Government (BERC 2018?2021 and PIBA_2019_104) and the Spanish Ministry of Science, Innovation and Universities (MICINN; PID2019?105520GB-100). The authors would also like to thank Kevin Murphy for the basis of the code that creates the physiological regressors, and personnel at the Center for Translation Imaging (Northwestern Radiology) for support with study set-up. Rachael Stickland: Conceptualization, Methodology, Software, Formal Analysis, Investigation, Data Curation, Writing (OD), Writing (RE), Visualization, Project Administration. Kristina Zvolanek: Conceptualization, Software, Investigation, Formal Analysis, Writing (RE), Visualization. Stefano Moia: Methodology, Writing (RE). Apoorva Ayyagari: Investigation. C?sar Caballero-Gaudes: Methodology, Writing (RE). Molly Bright: Conceptualization, Methodology, Software, Investigation, Resources, Writing (RE), Supervision, Project Administration, Funding Acquisition.

Keywords

BOLD-fMRI
Breathing tasks
CO
Cerebrovascular reactivity
Hemodynamic lag
Resting-state

ASJC Scopus subject areas

Neurology
Cognitive Neuroscience

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10.1016/j.neuroimage.2021.118306

Cite this

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title = "A practical modification to a resting state fMRI protocol for improved characterization of cerebrovascular function",

abstract = "Cerebrovascular reactivity (CVR), defined here as the Blood Oxygenation Level Dependent (BOLD) response to a CO2 pressure change, is a useful metric of cerebrovascular function. Both the amplitude and the timing (hemodynamic lag) of the CVR response can bring insight into the nature of a cerebrovascular pathology and aid in understanding noise confounds when using functional Magnetic Resonance Imaging (fMRI) to study neural activity. This research assessed a practical modification to a typical resting-state fMRI protocol, to improve the characterization of cerebrovascular function. In 9 healthy subjects, we modelled CVR and lag in three resting-state data segments, and in data segments which added a 2–3 minute breathing task to the start of a resting-state segment. Two different breathing tasks were used to induce fluctuations in arterial CO2 pressure: a breath-hold task to induce hypercapnia (CO2 increase) and a cued deep breathing task to induce hypocapnia (CO2 decrease). Our analysis produced voxel-wise estimates of the amplitude (CVR) and timing (lag) of the BOLD-fMRI response to CO2 by systematically shifting the CO2 regressor in time to optimize the model fit. This optimization inherently increases gray matter CVR values and fit statistics. The inclusion of a simple breathing task, compared to a resting-state scan only, increases the number of voxels in the brain that have a significant relationship between CO2 and BOLD-fMRI signals, and improves our confidence in the plausibility of voxel-wise CVR and hemodynamic lag estimates. We demonstrate the clinical utility and feasibility of this protocol in an incidental finding of Moyamoya disease, and explore the possibilities and challenges of using this protocol in younger populations. This hybrid protocol has direct applications for CVR mapping in both research and clinical settings and wider applications for fMRI denoising and interpretation.",

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AB - Cerebrovascular reactivity (CVR), defined here as the Blood Oxygenation Level Dependent (BOLD) response to a CO2 pressure change, is a useful metric of cerebrovascular function. Both the amplitude and the timing (hemodynamic lag) of the CVR response can bring insight into the nature of a cerebrovascular pathology and aid in understanding noise confounds when using functional Magnetic Resonance Imaging (fMRI) to study neural activity. This research assessed a practical modification to a typical resting-state fMRI protocol, to improve the characterization of cerebrovascular function. In 9 healthy subjects, we modelled CVR and lag in three resting-state data segments, and in data segments which added a 2–3 minute breathing task to the start of a resting-state segment. Two different breathing tasks were used to induce fluctuations in arterial CO2 pressure: a breath-hold task to induce hypercapnia (CO2 increase) and a cued deep breathing task to induce hypocapnia (CO2 decrease). Our analysis produced voxel-wise estimates of the amplitude (CVR) and timing (lag) of the BOLD-fMRI response to CO2 by systematically shifting the CO2 regressor in time to optimize the model fit. This optimization inherently increases gray matter CVR values and fit statistics. The inclusion of a simple breathing task, compared to a resting-state scan only, increases the number of voxels in the brain that have a significant relationship between CO2 and BOLD-fMRI signals, and improves our confidence in the plausibility of voxel-wise CVR and hemodynamic lag estimates. We demonstrate the clinical utility and feasibility of this protocol in an incidental finding of Moyamoya disease, and explore the possibilities and challenges of using this protocol in younger populations. This hybrid protocol has direct applications for CVR mapping in both research and clinical settings and wider applications for fMRI denoising and interpretation.

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A practical modification to a resting state fMRI protocol for improved characterization of cerebrovascular function

Abstract

Funding

Keywords

ASJC Scopus subject areas

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