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Wright AM, Xu T, Ingram J, Koo J, Zhao Y, Tong Y, Wen Q. Robust data-driven segmentation of pulsatile cerebral vessels using functional magnetic resonance imaging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.17.603932. [PMID: 39091755 PMCID: PMC11290998 DOI: 10.1101/2024.07.17.603932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Functional magnetic resonance imaging (fMRI) captures rich physiological and neuronal information that can offer insights into neurofluid dynamics, vascular health, and waste clearance function. The availability of cerebral vessel segmentation could facilitate fluid dynamics research in fMRI. However, without magnetic resonance angiography scans, cerebral vessel segmentation is challenging and time-consuming. This study leverages cardiac-induced pulsatile fMRI signal to develop a data-driven, automatic segmentation of large cerebral arteries and the superior sagittal sinus (SSS). The method was validated in a local dataset by comparing it to ground truth cerebral artery and SSS segmentations. Using the Human Connectome Project (HCP) aging dataset, the method's reproducibility was tested on 422 participants aged 36 to 100 years, each with four repeated fMRI scans. The method demonstrated high reproducibility, with an intraclass correlation coefficient > 0.7 in both cerebral artery and SSS segmentation volumes. This study demonstrates that the large cerebral arteries and SSS can be reproducibly and automatically segmented in fMRI datasets, facilitating the investigation of fluid dynamics in these regions.
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Zhong XZ, Polimeni JR, Chen JJ. Predicting the macrovascular contribution to resting-state fMRI functional connectivity at 3 Tesla: A model-informed approach. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.13.580143. [PMID: 38405829 PMCID: PMC10888884 DOI: 10.1101/2024.02.13.580143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Macrovascular biases have been a long-standing challenge for fMRI, limiting its ability to detect spatially specific neural activity. Recent experimental studies, including our own (Huck et al., 2023; Zhong et al., 2023), found substantial resting-state macrovascular BOLD fMRI contributions from large veins and arteries, extending into the perivascular tissue at 3 T and 7 T. The objective of this study is to demonstrate the feasibility of predicting, using a biophysical model, the experimental resting-state BOLD fluctuation amplitude (RSFA) and associated functional connectivity (FC) values at 3 Tesla. We investigated the feasibility of both 2D and 3D infinite-cylinder models as well as macrovascular anatomical networks (mVANs) derived from angiograms. Our results demonstrate that: 1) with the availability of mVANs, it is feasible to model macrovascular BOLD FC using both the mVAN-based model and 3D infinite-cylinder models, though the former performed better; 2) biophysical modelling can accurately predict the BOLD pairwise correlation near to large veins (with R 2 ranging from 0.53 to 0.93 across different subjects), but not near to large arteries; 3) compared with FC, biophysical modelling provided less accurate predictions for RSFA; 4) modelling of perivascular BOLD connectivity was feasible at close distances from veins (with R 2 ranging from 0.08 to 0.57), but not arteries, with performance deteriorating with increasing distance. While our current study demonstrates the feasibility of simulating macrovascular BOLD in the resting state, our methodology may also apply to understanding task-based BOLD. Furthermore, these results suggest the possibility of correcting for macrovascular bias in resting-state fMRI and other types of fMRI using biophysical modelling based on vascular anatomy.
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Golestani AM, Chen JJ. Comparing data-driven physiological denoising approaches for resting-state fMRI: implications for the study of aging. Front Neurosci 2024; 18:1223230. [PMID: 38379761 PMCID: PMC10876882 DOI: 10.3389/fnins.2024.1223230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 01/17/2024] [Indexed: 02/22/2024] Open
Abstract
Introduction Physiological nuisance contributions by cardiac and respiratory signals have a significant impact on resting-state fMRI data quality. As these physiological signals are often not recorded, data-driven denoising methods are commonly used to estimate and remove physiological noise from fMRI data. To investigate the efficacy of these denoising methods, one of the first steps is to accurately capture the cardiac and respiratory signals, which requires acquiring fMRI data with high temporal resolution. Methods In this study, we used such high-temporal resolution fMRI data to evaluate the effectiveness of several data-driven denoising methods, including global-signal regression (GSR), white matter and cerebrospinal fluid regression (WM-CSF), anatomical (aCompCor) and temporal CompCor (tCompCor), ICA-AROMA. Our analysis focused on the consequence of changes in low-frequency, cardiac and respiratory signal power, as well as age-related differences in terms of functional connectivity (fcMRI). Results Our results confirm that the ICA-AROMA and GSR removed the most physiological noise but also more low-frequency signals. These methods are also associated with substantially lower age-related fcMRI differences. On the other hand, aCompCor and tCompCor appear to be better at removing high-frequency physiological signals but not low-frequency signal power. These methods are also associated with relatively higher age-related fcMRI differences, whether driven by neuronal signal or residual artifact. These results were reproduced in data downsampled to represent conventional fMRI sampling frequency. Lastly, methods differ in performance depending on the age group. Discussion While this study cautions direct comparisons of fcMRI results based on different denoising methods in the study of aging, it also enhances the understanding of different denoising methods in broader fcMRI applications.
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Affiliation(s)
- Ali M. Golestani
- Department of Physics and Astronomy, University of Calgary, Calgary, AB, Canada
- Department of Oncology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - J. Jean Chen
- Rotman Research Institute at Baycrest, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Department of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
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Chen DY, Di X, Yu X, Biswal BB. The significance and limited influence of cerebrovascular reactivity on age and sex effects in task- and resting-state brain activity. Cereb Cortex 2024; 34:bhad448. [PMID: 38212284 PMCID: PMC10832986 DOI: 10.1093/cercor/bhad448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 10/31/2023] [Indexed: 01/13/2024] Open
Abstract
Functional MRI measures the blood-oxygen-level dependent signals, which provide an indirect measure of neural activity mediated by neurovascular responses. Cerebrovascular reactivity affects both task-induced and resting-state blood-oxygen-level dependent activity and may confound inter-individual effects, such as those related to aging and biological sex. We examined a large dataset containing breath-holding, checkerboard, and resting-state tasks. We used the breath-holding task to measure cerebrovascular reactivity, used the checkerboard task to obtain task-based activations, and quantified resting-state activity with amplitude of low-frequency fluctuations and regional homogeneity. We hypothesized that cerebrovascular reactivity would be correlated with blood-oxygen-level dependent measures and that accounting for these correlations would result in better estimates of age and sex effects. We found that cerebrovascular reactivity was correlated with checkerboard task activations in the visual cortex and with amplitude of low-frequency fluctuations and regional homogeneity in widespread fronto-parietal regions, as well as regions with large vessels. We also found significant age and sex effects in cerebrovascular reactivity, some of which overlapped with those observed in amplitude of low-frequency fluctuations and regional homogeneity. However, correcting for the effects of cerebrovascular reactivity had very limited influence on the estimates of age and sex. Our results highlight the limitations of accounting for cerebrovascular reactivity with the current breath-holding task.
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Affiliation(s)
- Donna Y Chen
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, United States
- Rutgers Biomedical and Health Sciences, Rutgers School of Graduate Studies, Newark, NJ 08901, United States
| | - Xin Di
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, United States
| | - Xin Yu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA 02114, United States
| | - Bharat B Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, United States
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Schneider SC, Kaczmarz S, Göttler J, Kufer J, Zott B, Priller J, Kallmayer M, Zimmer C, Sorg C, Preibisch C. Stronger influence of systemic than local hemodynamic-vascular factors on resting-state BOLD functional connectivity. Neuroimage 2023; 281:120380. [PMID: 37741595 DOI: 10.1016/j.neuroimage.2023.120380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 08/28/2023] [Accepted: 09/13/2023] [Indexed: 09/25/2023] Open
Abstract
Correlated fluctuations in the blood oxygenation level dependent (BOLD) signal of resting-state functional MRI (i.e., BOLD-functional connectivity, BOLD-FC) reflect a spectrum of neuronal and non-neuronal processes. In particular, there are multiple hemodynamic-vascular influences on BOLD-FC on both systemic (e.g., perfusion delay) and local levels (e.g., neurovascular coupling). While the influence of individual factors has been studied extensively, combined and comparative studies of systemic and local hemodynamic-vascular factors on BOLD-FC are scarce, notably in humans. We employed a multi-modal MRI approach to investigate and compare distinct hemodynamic-vascular processes and their impact on homotopic BOLD-FC in healthy controls and patients with unilateral asymptomatic internal carotid artery stenosis (ICAS). Asymptomatic ICAS is a cerebrovascular disorder, in which neuronal functioning is largely preserved but hemodynamic-vascular processes are impaired, mostly on the side of stenosis. Investigated indicators for local hemodynamic-vascular processes comprise capillary transit time heterogeneity (CTH) and cerebral blood volume (CBV) from dynamic susceptibility contrast (DSC) MRI, and cerebral blood flow (CBF) from pseudo-continuous arterial spin labeling (pCASL). Indicators for systemic processes are time-to-peak (TTP) from DSC MRI and BOLD lags from functional MRI. For each of these parameters, their influence on BOLD-FC was estimated by a comprehensive linear mixed model. Equally across groups, we found that individual mean BOLD-FC, local (CTH, CBV, and CBF) and systemic (TTP and BOLD lag) hemodynamic-vascular factors together explain 40.7% of BOLD-FC variance, with 20% of BOLD-FC variance explained by hemodynamic-vascular factors, with an about two-times larger contribution of systemic versus local factors. We conclude that regional differences in blood supply, i.e., systemic perfusion delays, exert a stronger influence on BOLD-FC than impairments in local neurovascular coupling.
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Affiliation(s)
- Sebastian C Schneider
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Psychiatry, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany.
| | - Stephan Kaczmarz
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany; Philips GmbH Market DACH, Hamburg, Germany
| | - Jens Göttler
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany
| | - Jan Kufer
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany; Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, United States of America
| | - Benedikt Zott
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany
| | - Josef Priller
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Psychiatry, Ismaningerstr. 22, 81675 Munich, Germany
| | - Michael Kallmayer
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for vascular surgery, Ismaningerstr. 22, 81675 Munich, Munich, Germany
| | - Claus Zimmer
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany
| | - Christian Sorg
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Psychiatry, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany
| | - Christine Preibisch
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675 Munich, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Neurology, Ismaningerstr. 22, 81675 Munich, Munich, Germany
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Chen DY, Di X, Yu X, Biswal BB. The Significance and Limited Influence of Cerebrovascular Reactivity on Age and Sex Effects in Task- and Resting-State Brain Activity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.18.553848. [PMID: 37662201 PMCID: PMC10473673 DOI: 10.1101/2023.08.18.553848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Functional MRI (fMRI) measures the blood-oxygen-level dependent (BOLD) signals, which provide an indirect measure of neural activity mediated by neurovascular responses. Cerebrovascular reactivity affects both task-induced and resting-state BOLD activity and may confound inter-individual effects observed in BOLD-based measures, such as those related to aging and biological sex. To investigate this, we examined a large open-access fMRI dataset containing a breath-holding task, checkerboard task, and resting-state scans. We used the breath-holding task to measure cerebrovascular reactivity, used the checkerboard task to obtain task-based activations, and from the resting-state data, we quantified the resting-state amplitude of low-frequency fluctuations (ALFF), and resting-state regional homogeneity (ReHo). We hypothesized that cerebrovascular reactivity would be correlated with BOLD measures and that accounting for these correlations would result in better estimates of age and sex effects. Our analysis showed that cerebrovascular reactivity was correlated with checkerboard task activations in the visual cortex and with ALFF and ReHo in widespread fronto-parietal regions, as well as regions with large vessels. We also found significant age and sex effects in cerebrovascular reactivity, some of which overlapped with those observed in ALFF and ReHo scores. Finally, we demonstrated that correcting for the effects of cerebrovascular reactivity had very limited influence on the estimates of age and sex. Our results highlight the limitations of accounting for cerebrovascular reactivity with the current breath-holding task.
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Affiliation(s)
- Donna Y. Chen
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
- Rutgers Biomedical and Health Sciences, Rutgers School of Graduate Studies, Newark, NJ, USA
| | - Xin Di
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | - Xin Yu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Bharat B. Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
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7
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Williams RJ, Specht JL, Mazerolle EL, Lebel RM, MacDonald ME, Pike GB. Correspondence between BOLD fMRI task response and cerebrovascular reactivity across the cerebral cortex. Front Physiol 2023; 14:1167148. [PMID: 37228813 PMCID: PMC10203231 DOI: 10.3389/fphys.2023.1167148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 04/24/2023] [Indexed: 05/27/2023] Open
Abstract
BOLD sensitivity to baseline perfusion and blood volume is a well-acknowledged fMRI confound. Vascular correction techniques based on cerebrovascular reactivity (CVR) might reduce variance due to baseline cerebral blood volume, however this is predicated on an invariant linear relationship between CVR and BOLD signal magnitude. Cognitive paradigms have relatively low signal, high variance and involve spatially heterogenous cortical regions; it is therefore unclear whether the BOLD response magnitude to complex paradigms can be predicted by CVR. The feasibility of predicting BOLD signal magnitude from CVR was explored in the present work across two experiments using different CVR approaches. The first utilized a large database containing breath-hold BOLD responses and 3 different cognitive tasks. The second experiment, in an independent sample, calculated CVR using the delivery of a fixed concentration of carbon dioxide and a different cognitive task. An atlas-based regression approach was implemented for both experiments to evaluate the shared variance between task-invoked BOLD responses and CVR across the cerebral cortex. Both experiments found significant relationships between CVR and task-based BOLD magnitude, with activation in the right cuneus (R 2 = 0.64) and paracentral gyrus (R 2 = 0.71), and the left pars opercularis (R 2 = 0.67), superior frontal gyrus (R 2 = 0.62) and inferior parietal cortex (R 2 = 0.63) strongly predicted by CVR. The parietal regions bilaterally were highly consistent, with linear regressions significant in these regions for all four tasks. Group analyses showed that CVR correction increased BOLD sensitivity. Overall, this work suggests that BOLD signal response magnitudes to cognitive tasks are predicted by CVR across different regions of the cerebral cortex, providing support for the use of correction based on baseline vascular physiology.
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Affiliation(s)
- Rebecca J. Williams
- Faculty of Health, School of Human Services, Charles Darwin University, Darwin, NT, Australia
| | - Jacinta L. Specht
- Department of Clinical Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Erin L. Mazerolle
- Departments of Psychology and Computer Science, St. Francis Xavier University, Antigonish, NS, Canada
| | - R. Marc Lebel
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- GE HealthCare, Calgary, AB, Canada
| | - M. Ethan MacDonald
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
- Department of Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
| | - G. Bruce Pike
- Department of Clinical Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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8
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Addeh A, Vega F, Medi PR, Williams RJ, Pike GB, MacDonald ME. Direct machine learning reconstruction of respiratory variation waveforms from resting state fMRI data in a pediatric population. Neuroimage 2023; 269:119904. [PMID: 36709788 DOI: 10.1016/j.neuroimage.2023.119904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 01/20/2023] [Accepted: 01/25/2023] [Indexed: 01/27/2023] Open
Abstract
In many functional magnetic resonance imaging (fMRI) studies, respiratory signals are unavailable or do not have acceptable quality due to issues with subject compliance, equipment failure or signal error. In large databases, such as the Human Connectome Projects, over half of the respiratory recordings may be unusable. As a result, the direct removal of low frequency respiratory variations from the blood oxygen level-dependent (BOLD) signal time series is not possible. This study proposes a deep learning-based method for reconstruction of respiratory variation (RV) waveforms directly from BOLD fMRI data in pediatric participants (aged 5 to 21 years old), and does not require any respiratory measurement device. To do this, the Lifespan Human Connectome Project in Development (HCP-D) dataset, which includes respiratory measurements, was used to both train a convolutional neural network (CNN) and evaluate its performance. Results show that a CNN can capture informative features from the BOLD signal time course and reconstruct accurate RV timeseries, especially when the subject has a prominent respiratory event. This work advances the use of direct estimation of physiological parameters from fMRI, which will eventually lead to reduced complexity and decrease the burden on participants because they may not be required to wear a respiratory bellows.
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Affiliation(s)
- Abdoljalil Addeh
- Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Canada; Department of Electrical & Software Engineering, Schulich School of Engineering, University of Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Canada; Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Canada
| | - Fernando Vega
- Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Canada; Department of Electrical & Software Engineering, Schulich School of Engineering, University of Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Canada; Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Canada
| | - Prathistith Raj Medi
- Data Science and Artificial Intelligence, International Institute of Information Technology, Naya Raipur, India
| | - Rebecca J Williams
- Department of Radiology, Cumming School of Medicine, University of Calgary, Canada; Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Canada; Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Canada
| | - G Bruce Pike
- Department of Radiology, Cumming School of Medicine, University of Calgary, Canada; Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Canada; Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Canada
| | - M Ethan MacDonald
- Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Canada; Department of Electrical & Software Engineering, Schulich School of Engineering, University of Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Canada; Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Canada
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Chan ST, Sanders WR, Fischer D, Kirsch JE, Napadow V, Bodien YG, Edlow BL. Correcting cardiorespiratory noise in resting-state functional MRI data acquired in critically ill patients. Brain Commun 2022; 4:fcac280. [PMID: 36382222 PMCID: PMC9665273 DOI: 10.1093/braincomms/fcac280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 07/25/2022] [Accepted: 10/28/2022] [Indexed: 11/06/2022] Open
Abstract
Resting-state functional MRI is being used to develop diagnostic, prognostic and therapeutic biomarkers for critically ill patients with severe brain injuries. In studies of healthy volunteers and non-critically ill patients, prospective cardiorespiratory data are routinely collected to remove non-neuronal fluctuations in the resting-state functional MRI signal during analysis. However, the feasibility and utility of collecting cardiorespiratory data in critically ill patients on a clinical MRI scanner are unknown. We concurrently acquired resting-state functional MRI (repetition time = 1250 ms) and cardiac and respiratory data in 23 critically ill patients with acute severe traumatic brain injury and in 12 healthy control subjects. We compared the functional connectivity results from two approaches that are commonly used to correct cardiorespiratory noise: (i) denoising with cardiorespiratory data (i.e. image-based method for retrospective correction of physiological motion effects in functional MRI) and (ii) standard bandpass filtering. Resting-state functional MRI data in 7 patients could not be analysed due to imaging artefacts. In 6 of the remaining 16 patients (37.5%), cardiorespiratory data were either incomplete or corrupted. In patients (n = 10) and control subjects (n = 10), the functional connectivity results corrected with the image-based method for retrospective correction of physiological motion effects in functional MRI did not significantly differ from those corrected with bandpass filtering of 0.008-0.125 Hz. Collectively, these findings suggest that, in critically ill patients with severe traumatic brain injury, there is limited feasibility and utility to denoising the resting-state functional MRI signal with prospectively acquired cardiorespiratory data.
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Affiliation(s)
- Suk-Tak Chan
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - William R Sanders
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - David Fischer
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - John E Kirsch
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Vitaly Napadow
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA 02129, USA
| | - Yelena G Bodien
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA 02129, USA
| | - Brian L Edlow
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
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Guilbert J, Légaré A, De Koninck P, Desrosiers P, Desjardins M. Toward an integrative neurovascular framework for studying brain networks. NEUROPHOTONICS 2022; 9:032211. [PMID: 35434179 PMCID: PMC8989057 DOI: 10.1117/1.nph.9.3.032211] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 03/11/2022] [Indexed: 05/28/2023]
Abstract
Brain functional connectivity based on the measure of blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals has become one of the most widely used measurements in human neuroimaging. However, the nature of the functional networks revealed by BOLD fMRI can be ambiguous, as highlighted by a recent series of experiments that have suggested that typical resting-state networks can be replicated from purely vascular or physiologically driven BOLD signals. After going through a brief review of the key concepts of brain network analysis, we explore how the vascular and neuronal systems interact to give rise to the brain functional networks measured with BOLD fMRI. This leads us to emphasize a view of the vascular network not only as a confounding element in fMRI but also as a functionally relevant system that is entangled with the neuronal network. To study the vascular and neuronal underpinnings of BOLD functional connectivity, we consider a combination of methodological avenues based on multiscale and multimodal optical imaging in mice, used in combination with computational models that allow the integration of vascular information to explain functional connectivity.
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Affiliation(s)
- Jérémie Guilbert
- Université Laval, Department of Physics, Physical Engineering, and Optics, Québec, Canada
- Université Laval, Centre de recherche du CHU de Québec, Québec, Canada
| | - Antoine Légaré
- Université Laval, Department of Physics, Physical Engineering, and Optics, Québec, Canada
- Centre de recherche CERVO, Québec, Canada
- Université Laval, Department of Biochemistry, Microbiology, and Bioinformatics, Québec, Canada
| | - Paul De Koninck
- Centre de recherche CERVO, Québec, Canada
- Université Laval, Department of Biochemistry, Microbiology, and Bioinformatics, Québec, Canada
| | - Patrick Desrosiers
- Université Laval, Department of Physics, Physical Engineering, and Optics, Québec, Canada
- Centre de recherche CERVO, Québec, Canada
| | - Michèle Desjardins
- Université Laval, Department of Physics, Physical Engineering, and Optics, Québec, Canada
- Université Laval, Centre de recherche du CHU de Québec, Québec, Canada
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11
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Golestani AM, Chen JJ. Performance of Temporal and Spatial Independent Component Analysis in Identifying and Removing Low-Frequency Physiological and Motion Effects in Resting-State fMRI. Front Neurosci 2022; 16:867243. [PMID: 35757543 PMCID: PMC9226487 DOI: 10.3389/fnins.2022.867243] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 05/16/2022] [Indexed: 11/13/2022] Open
Abstract
Effective separation of signal from noise (including physiological processes and head motion) is one of the chief challenges for improving the sensitivity and specificity of resting-state fMRI (rs-fMRI) measurements and has a profound impact when these noise sources vary between populations. Independent component analysis (ICA) is an approach for addressing these challenges. Conventionally, due to the lower amount of temporal than spatial information in rs-fMRI data, spatial ICA (sICA) is the method of choice. However, with recent developments in accelerated fMRI acquisitions, the temporal information is becoming enriched to the point that the temporal ICA (tICA) has become more feasible. This is particularly relevant as physiological processes and motion exhibit very different spatial and temporal characteristics when it comes to rs-fMRI applications, leading us to conduct a comparison of the performance of sICA and tICA in addressing these types of noise. In this study, we embrace the novel practice of using theory (simulations) to guide our interpretation of empirical data. We find empirically that sICA can identify more noise-related signal components than tICA. However, on the merit of functional-connectivity results, we find that while sICA is more adept at reducing whole-brain motion effects, tICA performs better in dealing with physiological effects. These interpretations are corroborated by our simulation results. The overall message of this study is that if ICA denoising is to be used for rs-fMRI, there is merit in considering a hybrid approach in which physiological and motion-related noise are each corrected for using their respective best-suited ICA approach.
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Affiliation(s)
- Ali M Golestani
- Department of Psychology, Toronto Neuroimaging Facility, University of Toronto, Toronto, ON, Canada
| | - J Jean Chen
- Rotman Research Institute at Baycrest, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.,Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
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12
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Stickland RC, Zvolanek KM, Moia S, Caballero-Gaudes C, Bright MG. Lag-Optimized Blood Oxygenation Level Dependent Cerebrovascular Reactivity Estimates Derived From Breathing Task Data Have a Stronger Relationship With Baseline Cerebral Blood Flow. Front Neurosci 2022; 16:910025. [PMID: 35801183 PMCID: PMC9254683 DOI: 10.3389/fnins.2022.910025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 05/11/2022] [Indexed: 11/13/2022] Open
Abstract
Cerebrovascular reactivity (CVR), an important indicator of cerebrovascular health, is commonly studied with the Blood Oxygenation Level Dependent functional MRI (BOLD-fMRI) response to a vasoactive stimulus. Theoretical and empirical evidence suggests that baseline cerebral blood flow (CBF) modulates BOLD signal amplitude and may influence BOLD-CVR estimates. We address how acquisition and modeling choices affect the relationship between baseline cerebral blood flow (bCBF) and BOLD-CVR: whether BOLD-CVR is modeled with the inclusion of a breathing task, and whether BOLD-CVR amplitudes are optimized for hemodynamic lag effects. We assessed between-subject correlations of average GM values and within-subject spatial correlations across cortical regions. Our results suggest that a breathing task addition to a resting-state acquisition, alongside lag-optimization within BOLD-CVR modeling, can improve BOLD-CVR correlations with bCBF, both between- and within-subjects, likely because these CVR estimates are more physiologically accurate. We report positive correlations between bCBF and BOLD-CVR, both between- and within-subjects. The physiological explanation of this positive correlation is unclear; research with larger samples and tightly controlled vasoactive stimuli is needed. Insights into what drives variability in BOLD-CVR measurements and related measurements of cerebrovascular function are particularly relevant when interpreting results in populations with altered vascular and/or metabolic baselines or impaired cerebrovascular reserve.
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Affiliation(s)
- Rachael C. Stickland
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Kristina M. Zvolanek
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
| | - Stefano Moia
- Basque Center on Cognition, Brain and Language, Donostia, Spain
- University of the Basque Country EHU/UPV, Donostia, Spain
| | | | - Molly G. Bright
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
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13
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Champagne AA, Coverdale NS, Allen MD, Tremblay JC, MacPherson REK, Pyke KE, Olver TD, Cook DJ. The physiological basis underlying functional connectivity differences in older adults: A multi-modal analysis of resting-state fMRI. Brain Imaging Behav 2022; 16:1575-1591. [PMID: 35092574 DOI: 10.1007/s11682-021-00570-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Accepted: 09/27/2021] [Indexed: 11/02/2022]
Abstract
The purpose of this study was to determine if differences in functional connectivity strength (FCS) with age were confounded by vascular parameters including resting cerebral blood flow (CBF0), cerebrovascular reactivity (CVR), and BOLD-CBF coupling. Neuroimaging data were collected from 13 younger adults (24 ± 2 years) and 14 older adults (71 ± 4 years). A dual-echo resting state pseudo-continuous arterial spin labeling sequence was performed, as well as a BOLD breath-hold protocol. A group independent component analysis was used to identify networks, which were amalgamated into a region of interest (ROI). Within the ROI, FC strength (FCS) was computed for all voxels and compared across the groups. CBF0, CVR and BOLD-CBF coupling were examined within voxels where FCS was different between young and older adults. FCS was greater in old compared to young (P = 0.001). When the effect of CBF0, CVR and BOLD-CBF coupling on FCS was examined, BOLD-CBF coupling had a significant effect (P = 0.003) and group differences in FCS were not present once all vascular parameters were considered in the statistical model (P = 0.07). These findings indicate that future studies of FCS should consider vascular physiological markers in order to improve our understanding of aging processes on brain connectivity.
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Affiliation(s)
- Allen A Champagne
- Centre for Neuroscience Studies, Queen's University, Room 260, Kingston, ON, K7L 3N6, Canada
| | - Nicole S Coverdale
- Centre for Neuroscience Studies, Queen's University, Room 260, Kingston, ON, K7L 3N6, Canada
| | - Matti D Allen
- Department of Physical Medicine and Rehabilitation, Queen's University, Kingston, ON, Canada.,School of Kinesiology and Health Studies, Cardiovascular Stress Response Laboratory, Queen's University, Kingston, ON, K7L 3N6, Canada.,Department of Physical Medicine and Rehabilitation, Providence Care Hospital, 752 King St., Ontario, West Kingston, Canada
| | - Joshua C Tremblay
- School of Kinesiology and Health Studies, Cardiovascular Stress Response Laboratory, Queen's University, Kingston, ON, K7L 3N6, Canada
| | - Rebecca E K MacPherson
- Department of Health Sciences, Faculty of Applied Health Sciences, Brock University, 1812 Sir Isaac Brock Way, St Catharines, ON, L2S 3A1, Canada
| | - Kyra E Pyke
- School of Kinesiology and Health Studies, Cardiovascular Stress Response Laboratory, Queen's University, Kingston, ON, K7L 3N6, Canada
| | - T Dylan Olver
- Biomedical Sciences, Western College of Veterinarian Medicine, University of Saskatchewan, 52 Campus Drive, Saskatoon, Saskatchewan, S7N 5B4, Canada
| | - Douglas J Cook
- Centre for Neuroscience Studies, Queen's University, Room 260, Kingston, ON, K7L 3N6, Canada. .,Department of Surgery, Queen's University, Room 232, 18 Stuart St, Kingston, ON, K7L 3N6, Canada.
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14
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Fesharaki NJ, Mathew AB, Mathis JR, Huddleston WE, Reuss JL, Pillai JJ, DeYoe EA. Effects of Thresholding on Voxel-Wise Correspondence of Breath-Hold and Resting-State Maps of Cerebrovascular Reactivity. Front Neurosci 2021; 15:654957. [PMID: 34504411 PMCID: PMC8421787 DOI: 10.3389/fnins.2021.654957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 07/22/2021] [Indexed: 11/13/2022] Open
Abstract
Functional magnetic resonance imaging for presurgical brain mapping enables neurosurgeons to identify viable tissue near a site of operable pathology which might be at risk of surgery-induced damage. However, focal brain pathology (e.g., tumors) may selectively disrupt neurovascular coupling while leaving the underlying neurons functionally intact. Such neurovascular uncoupling can result in false negatives on brain activation maps thereby compromising their use for surgical planning. One way to detect potential neurovascular uncoupling is to map cerebrovascular reactivity using either an active breath-hold challenge or a passive resting-state scan. The equivalence of these two methods has yet to be fully established, especially at a voxel level of resolution. To quantitatively compare breath-hold and resting-state maps of cerebrovascular reactivity, we first identified threshold settings that optimized coverage of gray matter while minimizing false responses in white matter. When so optimized, the resting-state metric had moderately better gray matter coverage and specificity. We then assessed the spatial correspondence between the two metrics within cortical gray matter, again, across a wide range of thresholds. Optimal spatial correspondence was strongly dependent on threshold settings which if improperly set tended to produce statistically biased maps. When optimized, the two CVR maps did have moderately good correspondence with each other (mean accuracy of 73.6%). Our results show that while the breath-hold and resting-state maps may appear qualitatively similar they are not quantitatively identical at a voxel level of resolution.
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Affiliation(s)
- Nooshin J Fesharaki
- College of Health Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI, United States.,Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Amy B Mathew
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Jedidiah R Mathis
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Wendy E Huddleston
- College of Health Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI, United States
| | - James L Reuss
- Prism Clinical Imaging, Inc., Milwaukee, WI, United States
| | - Jay J Pillai
- Neuroradiology Division, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Edgar A DeYoe
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
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15
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Stickland RC, Zvolanek KM, Moia S, Ayyagari A, Caballero-Gaudes C, Bright MG. A practical modification to a resting state fMRI protocol for improved characterization of cerebrovascular function. Neuroimage 2021; 239:118306. [PMID: 34175427 PMCID: PMC8552969 DOI: 10.1016/j.neuroimage.2021.118306] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 06/18/2021] [Accepted: 06/23/2021] [Indexed: 12/22/2022] Open
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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Affiliation(s)
- Rachael C Stickland
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.
| | - Kristina M Zvolanek
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States; Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
| | - Stefano Moia
- Basque Center on Cognition, Brain and Language, Donostia, Gipuzkoa, Spain; University of the Basque Country EHU/UPV, Donostia, Gipuzkoa, Spain
| | - Apoorva Ayyagari
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States; Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
| | | | - Molly G Bright
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States; Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
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16
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Sharma N, Murari G, Vandermorris S, Verhoeff NPLG, Herrmann N, Chen JJ, Mah L. Functional Connectivity Between the Posterior Default Mode Network and Parahippocampal Gyrus Is Disrupted in Older Adults with Subjective Cognitive Decline and Correlates with Subjective Memory Ability. J Alzheimers Dis 2021; 82:435-445. [PMID: 34024823 DOI: 10.3233/jad-201579] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Subjective cognitive decline (SCD) is associated with increased risk of developing Alzheimer's disease (AD). However, the underlying mechanisms for this association remain unclear. Neuroimaging studies suggest the earliest AD-related changes are large-scale network disruptions, beginning in the posterior default mode (pDMN) network. OBJECTIVE To examine the association between SCD and pDMN network connectivity with medial temporal lobe (MTL) regions using resting-state functional magnetic resonance imaging. METHODS Forty-nine participants with either SCD (n = 23, 12 females; mean age: 70.7 (5.5)) or who were cognitively unimpaired (CU; n = 26, 16 females, mean age: 71.42 (7.3)) completed the Memory Functioning Questionnaire, a measure of subjective memory, and underwent resting state functional MRI at 3 Tesla. Functional connectivity between the posterior cingulate cortex (PCC), as the key pDMN node, and MTL regions were compared between SCD and CU groups. Further, the association between pDMN-MTL connectivity and the Frequency of Forgetting subscale of the Memory Functioning Questionnaire was examined. RESULTS Connectivity between the PCC-MTL was observed in the CU group but was absent in SCD (t(47) = 2.69, p = 0.01). Across all participants, self-perception of frequency of forgetting, but not objective memory, was strongly correlated with connectivity between the PCC-left parahippocampal gyrus (r = 0.43, p = 0.002). CONCLUSION These findings support the hypothesis that increased AD risk in SCD may be mediated by disrupted pDMN-parahippocampal connectivity. In addition, these findings suggest that frequency of forgetting may serve as a potential biomarker of SCD due to incipient AD.
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Affiliation(s)
- Namita Sharma
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Geetanjali Murari
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | | | - Nicolaas Paul L G Verhoeff
- Baycrest Health Sciences, Toronto, Ontario, Canada.,Department of Psychiatry, Geriatric Psychiatry Division, University of Toronto, Toronto, ON, Canada
| | - Nathan Herrmann
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Psychiatry, Geriatric Psychiatry Division, University of Toronto, Toronto, ON, Canada
| | - J Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Linda Mah
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.,Department of Psychiatry, Geriatric Psychiatry Division, University of Toronto, Toronto, ON, Canada
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17
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Chen JJ, Gauthier CJ. The Role of Cerebrovascular-Reactivity Mapping in Functional MRI: Calibrated fMRI and Resting-State fMRI. Front Physiol 2021; 12:657362. [PMID: 33841190 PMCID: PMC8027080 DOI: 10.3389/fphys.2021.657362] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 03/02/2021] [Indexed: 12/14/2022] Open
Abstract
Task and resting-state functional MRI (fMRI) is primarily based on the same blood-oxygenation level-dependent (BOLD) phenomenon that MRI-based cerebrovascular reactivity (CVR) mapping has most commonly relied upon. This technique is finding an ever-increasing role in neuroscience and clinical research as well as treatment planning. The estimation of CVR has unique applications in and associations with fMRI. In particular, CVR estimation is part of a family of techniques called calibrated BOLD fMRI, the purpose of which is to allow the mapping of cerebral oxidative metabolism (CMRO2) using a combination of BOLD and cerebral-blood flow (CBF) measurements. Moreover, CVR has recently been shown to be a major source of vascular bias in computing resting-state functional connectivity, in much the same way that it is used to neutralize the vascular contribution in calibrated fMRI. Furthermore, due to the obvious challenges in estimating CVR using gas challenges, a rapidly growing field of study is the estimation of CVR without any form of challenge, including the use of resting-state fMRI for that purpose. This review addresses all of these aspects in which CVR interacts with fMRI and the role of CVR in calibrated fMRI, provides an overview of the physiological biases and assumptions underlying hypercapnia-based CVR and calibrated fMRI, and provides a view into the future of non-invasive CVR measurement.
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Affiliation(s)
- J Jean Chen
- Baycrest Centre for Geriatric Care, Rotman Research Institute, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Claudine J Gauthier
- Department of Physics, Concordia University, Montreal, QC, Canada.,Montreal Heart Institute, Montreal, QC, Canada
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18
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Linke A, Mash L, Fong C, Kinnear M, Kohli J, Wilkinson M, Tung R, Keehn RJ, Carper R, Fishman I, Müller R.A. Dynamic time warping outperforms Pearson correlation in detecting atypical functional connectivity in autism spectrum disorders. Neuroimage 2020; 223:117383. [PMID: 32949710 PMCID: PMC9851773 DOI: 10.1016/j.neuroimage.2020.117383] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 09/12/2020] [Indexed: 01/21/2023] Open
Abstract
Resting state fMRI (rsfMRI) is frequently used to study brain function, including in clinical populations. Similarity of blood-oxygen-level-dependent (BOLD) fluctuations during rsfMRI between brain regions is thought to reflect intrinsic functional connectivity (FC), potentially due to history of coactivation. To quantify similarity, studies have almost exclusively relied on Pearson correlation, which assumes linearity and can therefore underestimate FC if the hemodynamic response function differs regionally or there is BOLD signal lag between timeseries. Here we show in three cohorts of children, adolescents and adults, with and without autism spectrum disorders (ASDs), that measuring the similarity of BOLD signal fluctuations using non-linear dynamic time warping (DTW) is more robust to global signal regression (GSR), has higher test-retest reliability and is more sensitive to task-related changes in FC. Additionally, when comparing FC between individuals with ASDs and typical controls, more group differences are detected using DTW. DTW estimates are also more related to ASD symptom severity and executive function, while Pearson correlation estimates of FC are more strongly associated with respiration during rsfMRI. Together these findings suggest that non-linear methods such as DTW improve estimation of resting state FC, particularly when studying clinical populations whose hemodynamics or neurovascular coupling may be altered compared to typical controls.
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Affiliation(s)
- A.C. Linke
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, 6363 Alvarado Ct., Suite 200, San Diego, CA 92120, United States,Corresponding author. (A.C. Linke)
| | - L.E. Mash
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, 6363 Alvarado Ct., Suite 200, San Diego, CA 92120, United States,San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, United States
| | - C.H. Fong
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, 6363 Alvarado Ct., Suite 200, San Diego, CA 92120, United States,San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, United States
| | - M.K. Kinnear
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, 6363 Alvarado Ct., Suite 200, San Diego, CA 92120, United States
| | - J.S. Kohli
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, 6363 Alvarado Ct., Suite 200, San Diego, CA 92120, United States,San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, United States
| | - M. Wilkinson
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, 6363 Alvarado Ct., Suite 200, San Diego, CA 92120, United States,San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, United States
| | - R. Tung
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, 6363 Alvarado Ct., Suite 200, San Diego, CA 92120, United States
| | - R.J. Jao Keehn
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, 6363 Alvarado Ct., Suite 200, San Diego, CA 92120, United States
| | - R.A. Carper
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, 6363 Alvarado Ct., Suite 200, San Diego, CA 92120, United States,San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, United States
| | - I. Fishman
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, 6363 Alvarado Ct., Suite 200, San Diego, CA 92120, United States,San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, United States
| | - R.-.A. Müller
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, 6363 Alvarado Ct., Suite 200, San Diego, CA 92120, United States,San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, United States
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19
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Chen JJ, Herman P, Keilholz S, Thompson GJ. Editorial: Origins of the Resting-State fMRI Signal. Front Neurosci 2020; 14:594990. [PMID: 33192281 PMCID: PMC7653173 DOI: 10.3389/fnins.2020.594990] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 09/10/2020] [Indexed: 01/17/2023] Open
Affiliation(s)
- J Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Peter Herman
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, United States
| | - Shella Keilholz
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
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20
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Weiss F, Zamoscik V, Schmidt SN, Halli P, Kirsch P, Gerchen MF. Just a very expensive breathing training? Risk of respiratory artefacts in functional connectivity-based real-time fMRI neurofeedback. Neuroimage 2020; 210:116580. [DOI: 10.1016/j.neuroimage.2020.116580] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 01/15/2020] [Accepted: 01/20/2020] [Indexed: 10/25/2022] Open
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21
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Hussein A, Matthews JL, Syme C, Macgowan C, MacIntosh BJ, Shirzadi Z, Pausova Z, Paus T, Chen JJ. The association between resting-state functional magnetic resonance imaging and aortic pulse-wave velocity in healthy adults. Hum Brain Mapp 2020; 41:2121-2135. [PMID: 32034832 PMCID: PMC7268071 DOI: 10.1002/hbm.24934] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 01/08/2020] [Accepted: 01/09/2020] [Indexed: 12/11/2022] Open
Abstract
Resting‐state functional magnetic resonance imaging (rs‐fMRI) is frequently used to study brain function; but, it is unclear whether BOLD‐signal fluctuation amplitude and functional connectivity are associated with vascular factors, and how vascular‐health factors are reflected in rs‐fMRI metrics in the healthy population. As arterial stiffening is a known age‐related cardiovascular risk factor, we investigated the associations between aortic stiffening (as measured using pulse‐wave velocity [PWV]) and rs‐fMRI metrics. We used cardiac MRI to measure aortic PWV (an established indicator of whole‐body vascular stiffness), as well as dual‐echo pseudo‐continuous arterial‐spin labeling to measure BOLD and CBF dynamics simultaneously in a group of generally healthy adults. We found that: (1) higher aortic PWV is associated with lower variance in the resting‐state BOLD signal; (2) higher PWV is also associated with lower BOLD‐based resting‐state functional connectivity; (3) regions showing lower connectivity do not fully overlap with those showing lower BOLD variance with higher PWV; (4) CBF signal variance is a significant mediator of the above findings, only when averaged across regions‐of‐interest. Furthermore, we found no significant association between BOLD signal variance and systolic blood pressure, which is also a known predictor of vascular stiffness. Age‐related vascular stiffness, as measured by PWV, provides a unique scenario to demonstrate the extent of vascular bias in rs‐fMRI signal fluctuations and functional connectivity. These findings suggest that a substantial portion of age‐related rs‐fMRI differences may be driven by vascular effects rather than directly by brain function.
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Affiliation(s)
- Ahmad Hussein
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Jacob L Matthews
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Catriona Syme
- SickKids Hospital, Toronto, Canada.,Department of Physiology, University of Toronto, Toronto, Canada
| | - Christopher Macgowan
- SickKids Hospital, Toronto, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Bradley J MacIntosh
- Department of Medical Biophysics, University of Toronto, Toronto, Canada.,Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada
| | - Zahra Shirzadi
- Department of Medical Biophysics, University of Toronto, Toronto, Canada.,Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada
| | - Zdenka Pausova
- SickKids Hospital, Toronto, Canada.,Department of Physiology, University of Toronto, Toronto, Canada
| | - Tomáš Paus
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada.,Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada
| | - J Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Canada
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22
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Champagne AA, Coverdale NS, Ross A, Chen Y, Murray CI, Dubowitz D, Cook DJ. Multi-modal normalization of resting-state using local physiology reduces changes in functional connectivity patterns observed in mTBI patients. Neuroimage Clin 2020; 26:102204. [PMID: 32058317 PMCID: PMC7013121 DOI: 10.1016/j.nicl.2020.102204] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 02/02/2020] [Accepted: 02/03/2020] [Indexed: 12/25/2022]
Abstract
Blood oxygenation level dependent (BOLD) resting-state functional magnetic resonance imaging (rs-fMRI) may serve as a sensitive marker to identify possible changes in the architecture of large-scale networks following mild traumatic brain injury (mTBI). Differences in functional connectivity (FC) measurements derived from BOLD rs-fMRI may however be confounded by changes in local cerebrovascular physiology and neurovascular coupling mechanisms, without changes in the underlying neuronally driven connectivity of networks. In this study, multi-modal neuroimaging data including BOLD rs-fMRI, baseline cerebral blood flow (CBF0) and cerebrovascular reactivity (CVR; acquired using a hypercapnic gas breathing challenge) were collected in 23 subjects with reported mTBI (14.6±14.9 months post-injury) and 27 age-matched healthy controls. Despite no group differences in CVR within the networks of interest (P > 0.05, corrected), significantly higher CBF0 was documented in the mTBI subjects (P < 0.05, corrected), relative to the controls. A normalization method designed to account for differences in CBF0 post-mTBI was introduced to evaluate the effects of such an approach on reported group differences in network connectivity. Inclusion of regional perfusion measurements in the computation of correlation coefficients within and across large-scale networks narrowed the differences in FC between the groups, suggesting that this approach may elucidate unique changes in connectivity post-mTBI while accounting for shared variance with CBF0. Altogether, our results provide a strong paradigm supporting the need to account for changes in physiological modulators of BOLD in order to expand our understanding of the effects of brain injury on large-scale FC of cortical networks.
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Affiliation(s)
- Allen A Champagne
- Centre for Neuroscience Studies, Room 260, Queen's University, Kingston ON K7L 3N6 Canada.
| | - Nicole S Coverdale
- Centre for Neuroscience Studies, Room 260, Queen's University, Kingston ON K7L 3N6 Canada.
| | - Andrew Ross
- Performance Phenomics, 180 John St., Toronto ON M5T 1 × 5 Canada.
| | - Yining Chen
- Centre for Neuroscience Studies, Room 260, Queen's University, Kingston ON K7L 3N6 Canada.
| | | | - David Dubowitz
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand.
| | - Douglas J Cook
- Centre for Neuroscience Studies, Room 260, Queen's University, Kingston ON K7L 3N6 Canada; Department of Surgery, Queen's University, Kingston, ON, Canada.
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23
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Co-localized impaired regional cerebrovascular reactivity in chronic concussion is associated with BOLD activation differences during a working memory task. Brain Imaging Behav 2020; 14:2438-2449. [PMID: 31903527 DOI: 10.1007/s11682-019-00194-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
The purpose of this study was to quantify differences in blood oxygen level dependent (BOLD) activation on a working memory task, baseline cerebral blood flow (CBF0), and cerebrovascular reactivity (CVR) between participants with and without a history of concussion. A dual-echo pseudo-continuous arterial spin labelling (pCASL) sequence was performed on a group of 10 subjects with a previous concussion (126 ± 15 days prior) and on a control group (n = 10) during a visual working memory protocol. A separate dual-echo pCASL sequence was used to derive CVR and CBF0 measurements from a boxcar hypercapnic breathing protocol. Brain areas with significant activation differences on the working memory task between groups were identified and combined as an aggregate region of interest for CBF and CVR analyses. Areas of reduced BOLD activation during the working memory task in the concussed group included the ventral anterior cingulate cortex (ACC), the medial temporal gyrus (MTG), and the lateral occipital cortex in two loci. A single area of increased activation was located in the parietal operculum. Further analyses of CBF0 and CVR in these regions revealed reduced CVR in the concussed group in the MTG and ACC, while CBF0 did not differ. The differences in CVR between the two groups in these regions suggest that concussive injury may result in microvascular dysfunction. In turn, the decreased BOLD response during the task could be due to altered neurovascular coupling, rather than an impairment in neural activation alone. However, in other regions associated with working memory, unchanged CBF0 and CVR suggests that neural injury also persists after concussion. In the future, BOLD results should be normalized to CVR in order achieve a clearer understanding of the neural and vascular contributions to the differences in the signal.
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Champagne AA, Coverdale NS, Nashed JY, Fernandez-Ruiz J, Cook DJ. Resting CMRO 2 fluctuations show persistent network hyper-connectivity following exposure to sub-concussive collisions. Neuroimage Clin 2019; 22:101753. [PMID: 30884366 PMCID: PMC6424143 DOI: 10.1016/j.nicl.2019.101753] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2018] [Revised: 02/20/2019] [Accepted: 03/09/2019] [Indexed: 12/20/2022]
Abstract
Exposure to head impacts may alter brain connectivity within cortical hubs such as the default-mode network (DMN). However, studies have yet to consider the confounding effects of altered resting cerebral blood flow (CBF0) and cerebrovascular reactivity (CVR) on changes in connectivity following sub-concussive impacts. Here, 23 Canadian collegiate football players were followed during a season using calibrated resting-state MRI and helmet accelerometers to examine the interplay between the neural and vascular factors that determine functional connectivity (FC). Connectivity-based analyses using blood oxygen level dependent (BOLD) and cerebral metabolic rate of oxygen consumption (CMRO2) mapping were used to study the DMN longitudinally. Network-specific decreases in CBF0 were observed one month following the season, while impaired CVR was documented at both mid-season and one month following the season, compared to pre-season baseline. Alterations in CBF0 and BOLD-based CVR throughout the season suggest that neurophysiological markers may show different susceptibility timelines following head impacts. DMN connectivity was increased throughout the season, independent of changes in cerebrovascular physiology, suggesting that alterations in FC following sub-concussive impacts are robust and independent of changes in brain hemodynamics. No significant correlations between impact kinematics and DMN connectivity changes were documented in this study. Altogether, these findings create a strong paradigm for future studies to examine the underlying neural and vascular mechanisms associated with increases in network connectivity following repeated exposure to sub-concussive collisions, in an effort to improve management of head impacts in contact sports.
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Affiliation(s)
- Allen A Champagne
- Centre for Neuroscience Studies, Room 260, Queen's University, Kingston, ON K7L 3N6, Canada.
| | - Nicole S Coverdale
- Centre for Neuroscience Studies, Room 260, Queen's University, Kingston, ON K7L 3N6, Canada.
| | - Joseph Y Nashed
- Centre for Neuroscience Studies, Room 260, Queen's University, Kingston, ON K7L 3N6, Canada.
| | - Juan Fernandez-Ruiz
- Departamento de Fisiología, Facultad de Medicina, Universidad Nacional Autónoma de México, Av. Universidad 3000, Coyoacán, Ciudad de México 04510, México.
| | - Douglas J Cook
- Centre for Neuroscience Studies, Room 260, Queen's University, Kingston, ON K7L 3N6, Canada; Department of Surgery, Queen's University, Room 232, 18 Stuart St, Kingston, ON K7L 3N6, Canada.
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Li H, Cao W, Zhang X, Sun B, Jiang S, Li J, Liu C, Yin W, Wu Y, Liu T, Yao D, Luo C. BOLD-fMRI reveals the association between renal oxygenation and functional connectivity in the aging brain. Neuroimage 2019; 186:510-517. [DOI: 10.1016/j.neuroimage.2018.11.030] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2018] [Revised: 11/19/2018] [Accepted: 11/20/2018] [Indexed: 01/23/2023] Open
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26
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Liao P, Zhang J, Zeng K, Yang Y, Cai S, Guo G, Cai C. Referenceless distortion correction of gradient-echo echo-planar imaging under inhomogeneous magnetic fields based on a deep convolutional neural network. Comput Biol Med 2018; 100:230-238. [DOI: 10.1016/j.compbiomed.2018.07.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Revised: 07/14/2018] [Accepted: 07/14/2018] [Indexed: 12/15/2022]
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27
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Chen JJ. Cerebrovascular-Reactivity Mapping Using MRI: Considerations for Alzheimer's Disease. Front Aging Neurosci 2018; 10:170. [PMID: 29922153 PMCID: PMC5996106 DOI: 10.3389/fnagi.2018.00170] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Accepted: 05/18/2018] [Indexed: 01/14/2023] Open
Abstract
Alzheimer’s disease (AD) is associated with well-established macrostructural and cellular markers, including localized brain atrophy and deposition of amyloid. However, there is growing recognition of the link between cerebrovascular dysfunction and AD, supported by continuous experimental evidence in the animal and human literature. As a result, neuroimaging studies of AD are increasingly aiming to incorporate vascular measures, exemplified by measures of cerebrovascular reactivity (CVR). CVR is a measure that is rooted in clinical practice, and as non-invasive CVR-mapping techniques become more widely available, routine CVR mapping may open up new avenues of investigation into the development of AD. This review focuses on the use of MRI to map CVR, paying specific attention to recent developments in MRI methodology and on the emerging stimulus-free approaches to CVR mapping. It also summarizes the biological basis for the vascular contribution to AD, and provides critical perspective on the choice of CVR-mapping techniques amongst frail populations.
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Affiliation(s)
- J J Chen
- Rotman Research Institute, Baycrest, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
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