Dataset Information

Quantitative mapping of cerebrovascular reactivity using resting-state BOLD fMRI: Validation in healthy adults.

ABSTRACT: In conventional neuroimaging, cerebrovascular reactivity (CVR) is quantified primarily using the blood-oxygenation level-dependent (BOLD) functional MRI (fMRI) signal, specifically, as the BOLD response to intravascular carbon dioxide (CO2) modulations, in units of [%?BOLD/mmHg]. While this method has achieved wide appeal and clinical translation, the tolerability of CO2-related tasks amongst patients and the elderly remains a challenge in more routine and large-scale applications. In this work, we propose an improved method to quantify CVR by exploiting intrinsic fluctuations in CO2 and corresponding changes in the resting-state BOLD signal (rs-qCVR). Our rs-qCVR approach requires simultaneous monitoring of PETCO2, cardiac pulsation and respiratory volume. In 16 healthy adults, we compare our quantitative CVR estimation technique to the prospective CO2-targeting based CVR quantification approach (qCVR, the "standard"). We also compare our rs-CVR to non-quantitative alternatives including the resting-state fluctuation amplitude (RSFA), amplitude of low-frequency fluctuation (ALFF) and global-signal regression. When all subjects were pooled, only RSFA and ALFF were significantly associated with qCVR. However, for characterizing regional CVR variations within each subject, only the PETCO2-based rs-qCVR measure is strongly associated with standard qCVR in 100% of the subjects (p?0.1). In contrast, for the more qualitative CVR measures, significant within-subject association with qCVR was only achieved in 50-70% of the subjects. Our work establishes the feasibility of extracting quantitative CVR maps using rs-fMRI, opening the possibility of mapping functional connectivity and qCVR simultaneously.

SUBMITTER: Golestani AM

PROVIDER: S-EPMC5148619 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Quantitative mapping of cerebrovascular reactivity using resting-state BOLD fMRI: Validation in healthy adults.

Golestani Ali M AM Wei Luxi L LL Chen J Jean JJ

NeuroImage 20160511

In conventional neuroimaging, cerebrovascular reactivity (CVR) is quantified primarily using the blood-oxygenation level-dependent (BOLD) functional MRI (fMRI) signal, specifically, as the BOLD response to intravascular carbon dioxide (CO2) modulations, in units of [%ΔBOLD/mmHg]. While this method has achieved wide appeal and clinical translation, the tolerability of CO2-related tasks amongst patients and the elderly remains a challenge in more routine and large-scale applications. In this work, ...[more]

PMID: 27177763

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Project description:Performing a BOLD functional MRI (fMRI) acquisition during breath-hold (BH) tasks is a non-invasive, robust method to estimate cerebrovascular reactivity (CVR). However, movement and breathing-related artefacts caused by the BH can substantially hinder CVR estimates due to their high temporal collinearity with the effect of interest, and attention has to be paid when choosing which analysis model should be applied to the data. In this study, we evaluate the performance of multiple analysis strategies based on lagged general linear models applied on multi-echo BOLD fMRI data, acquired in ten subjects performing a BH task during ten sessions, to obtain subject-specific CVR and haemodynamic lag estimates. The evaluated approaches range from conventional regression models, i.e. including drifts and motion timecourses as nuisance regressors, applied on single-echo or optimally-combined data, to more complex models including regressors obtained from multi-echo independent component analysis with different grades of orthogonalization in order to preserve the effect of interest, i.e. the CVR. We compare these models in terms of their ability to make signal intensity changes independent from motion, as well as the reliability as measured by voxelwise intraclass correlation coefficients of both CVR and lag maps over time. Our results reveal that a conservative independent component analysis model applied on the optimally-combined multi-echo fMRI signal offers the largest reduction of motion-related effects in the signal, while yielding reliable CVR amplitude and lag estimates, although a conventional regression model applied on the optimally-combined data results in similar estimates. This work demonstrates the usefulness of multi-echo based fMRI acquisitions and independent component analysis denoising for precision mapping of CVR in single subjects based on BH paradigms, fostering its potential as a clinically-viable neuroimaging tool for individual patients. It also proves that the way in which data-driven regressors should be incorporated in the analysis model is not straight-forward due to their complex interaction with the BH-induced BOLD response.

Project description:The exact neurophysiological basis of chronic tinnitus, which affects 10-15% of the population, remains unknown and is controversial at many levels. It is an open question whether phantom sound perception results from increased central neural gain or not, a crucial question for any future therapeutic intervention strategies for tinnitus. We performed a comprehensive study of mild hearing-impaired participants with and without tinnitus, excluding participants with co-occurrences of hyperacusis. A right-hemisphere correlation between tinnitus loudness and auditory perceptual difficulty was observed in the tinnitus group, independent of differences in hearing thresholds. This correlation was linked to reduced and delayed sound-induced suprathreshold auditory brain responses (ABR wave V) in the tinnitus group, suggesting subsided rather than exaggerated central neural responsiveness. When anatomically predefined auditory regions of interest were analysed for altered sound-evoked BOLD fMRI activity, it became evident that subcortical and cortical auditory regions and regions involved in sound detection (posterior insula, hippocampus), responded with reduced BOLD activity in the tinnitus group, emphasizing reduced, rather than increased, central neural gain. Regarding previous findings of evoked BOLD activity being linked to positive connectivities at rest, we additionally analysed r-fcMRI responses in anatomically predefined auditory regions and regions associated with sound detection. A profound reduction in positive interhemispheric connections of homologous auditory brain regions and a decline in the positive connectivities between lower auditory brainstem regions and regions involved in sound detection (hippocampus, posterior insula) were observed in the tinnitus group. The finding went hand-in-hand with the emotional (amygdala, anterior insula) and temporofrontal/stress-regulating regions (prefrontal cortex, inferior frontal gyrus) that were no longer positively connected with auditory cortex regions in the tinnitus group but were instead positively connected to lower-level auditory brainstem regions. Delayed sound processing, reduced sound-evoked BOLD fMRI activity and altered r-fcMRI in the auditory midbrain correlated in the tinnitus group and showed right hemisphere dominance as did tinnitus loudness and perceptual difficulty. The findings suggest that reduced central neural gain in the auditory stream may lead to phantom perception through a failure to energize attentional/stress-regulating networks for contextualization of auditory-specific information. Reduced auditory-specific information flow in tinnitus has until now escaped detection in humans, as low-level auditory brain regions were previously omitted from neuroimaging studies.Trial registrationGerman Clinical Trials Register DRKS0006332.

Project description:Accurate identification of brain function is necessary to understand neurocognitive aging, and thereby promote health and well-being. Many studies of neurocognitive aging have investigated brain function with the blood-oxygen level-dependent (BOLD) signal measured by functional magnetic resonance imaging. However, the BOLD signal is a composite of neural and vascular signals, which are differentially affected by aging. It is, therefore, essential to distinguish the age effects on vascular versus neural function. The BOLD signal variability at rest (known as resting state fluctuation amplitude, RSFA), is a safe, scalable, and robust means to calibrate vascular responsivity, as an alternative to breath-holding and hypercapnia. However, the use of RSFA for normalization of BOLD imaging assumes that age differences in RSFA reflecting only vascular factors, rather than age-related differences in neural function (activity) or neuronal loss (atrophy). Previous studies indicate that two vascular factors, cardiovascular health (CVH) and cerebrovascular function, are insufficient when used alone to fully explain age-related differences in RSFA. It remains possible that their joint consideration is required to fully capture age differences in RSFA. We tested the hypothesis that RSFA no longer varies with age after adjusting for a combination of cardiovascular and cerebrovascular measures. We also tested the hypothesis that RSFA variation with age is not associated with atrophy. We used data from the population-based, lifespan Cam-CAN cohort. After controlling for cardiovascular and cerebrovascular estimates alone, the residual variance in RSFA across individuals was significantly associated with age. However, when controlling for both cardiovascular and cerebrovascular estimates, the variance in RSFA was no longer associated with age. Grey matter volumes did not explain age differences in RSFA, after controlling for CVH. The results were consistent between voxel-level analysis and independent component analysis. Our findings indicate that cardiovascular and cerebrovascular signals are together sufficient predictors of age differences in RSFA. We suggest that RSFA can be used to separate vascular from neuronal factors, to characterize neurocognitive aging. We discuss the implications and make recommendations for the use of RSFA in the research of aging.

Dataset Information

Quantitative mapping of cerebrovascular reactivity using resting-state BOLD fMRI: Validation in healthy adults.

Publications

Quantitative mapping of cerebrovascular reactivity using resting-state BOLD fMRI: Validation in healthy adults.

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