Multiparametric measurement of cerebral physiology using calibrated fMRI

Bright, Molly G.; Croal, Paula; Blockley, Nicholas P.; Bulte, Daniel P.

doi:10.1016/j.neuroimage.2017.12.049

Cited by 22 publications

(24 citation statements)

References 192 publications

(218 reference statements)

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“… β is a magnetic field‐specific constant describing the coupling between the reversible transverse relaxation rate,

R_{2}^{'}

, induced by inhomogeneous external fields and [dHb]. In general, it depends on the vessel size but may be approximated as β ≈ 1 at 7 T, where intravascular signal contributions become negligible at typical TE values (Bright, Croal, Blockley, & Bulte, ; Kida, Kennan, Rothman, Behar, & Hyder, ; Martindale, Kennerley, Johnston, Zheng, & Mayhew, ). Consequently, the change in

R_{2}^{'}

is approximately linear in [dHb].…”

Section: Methodsmentioning

confidence: 99%

Cortical laminar resting‐state signal fluctuations scale with the hypercapnic blood oxygenation level‐dependent response

Guidi

Huber

Lampe

et al. 2020

Human Brain Mapping

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Calibrated functional magnetic resonance imaging can remove unwanted sources of signal variability in the blood oxygenation level-dependent (BOLD) response. This is achieved by scaling, using information from a perfusion-sensitive scan during a purely vascular challenge, typically induced by a gas manipulation or a breath-hold task. In this work, we seek for a validation of the use of the resting-state fluctuation amplitude (RSFA) as a scaling factor to remove vascular contributions from the BOLD response. Given the peculiarity of depth-dependent vascularization in gray matter, BOLD and vascular space occupancy (VASO) data were acquired at submillimeter resolution and averaged across cortical laminae. RSFA from the primary motor cortex was, thus, compared to the amplitude of hypercapnia-induced signal changes (tSD hc ) and with the M factor of the Davis model on a laminar level. High linear correlations were observed for RSFA and tSD hc (R 2 = 0.92 ± 0.06) and somewhat reduced for RSFA and M (R 2 = 0.62 ± 0.19). Laminar profiles of RSFAnormalized BOLD signal changes yielded good agreement with corresponding VASO profiles. Overall, this suggests that RSFA contains strong vascular components and is also modulated by baseline quantities contained in the M factor. We Occupancy; WM, white matter; Mathematical symbols: CBF, cerebral blood flow; CBV, cerebral blood volume; CMR O2 , cerebral metabolic rate of oxygen consumption; CVR, cerebrovascular reactivity; f, normalized CBF; M, calibration constant corresponding to the maximal BOLD signal change; P ET CO 2 , end-tidal partial pressure of carbon dioxide; P ET O 2 , end-tidal partial pressure of oxygen; R 2 , coefficient of determination; R 0 2 , reversible transverse relaxation rate; RSFA, fluctuation amplitude of the resting-state timeseries; r, normalized CMRO2; S, signal amplitude; ΔS, relative BOLD signal change; ΔS hc , relative BOLD signal change induced by mild hypercapnia; T 1 , longitudinal relaxation time; TE, echo time; TI, inversion time; TR, repetition time; tSD hc , temporal standard deviation of the hypercapnia timeseries; tSD rs , temporal standard deviation of the resting-state timeseries; tSNR, temporal signal-to-noise ratio; p, error probability; v, normalized CBV; Z, Z-score; α, Grubb exponent; β, constant describing the coupling between R 0 2 and [dHb]; κ, proportionality constant; 0 , index indicating a baseline ("resting") level; full , index indicating the entire frequency band; high, index indicating the high-frequency band; low, index indicating the low-frequency band; t, index indicating the total blood compartment; v, index indicating the venous compartment; [X], concentration of compound X.Maria Guidi and Laurentius Huber contributed equally to this study.

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“… β is a magnetic field‐specific constant describing the coupling between the reversible transverse relaxation rate,

R_{2}^{'}

R_{2}^{'}

is approximately linear in [dHb].…”

Section: Methodsmentioning

confidence: 99%

Cortical laminar resting‐state signal fluctuations scale with the hypercapnic blood oxygenation level‐dependent response

Guidi

Huber

Lampe

et al. 2020

Human Brain Mapping

View full text Add to dashboard Cite

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“…In addition, it provides a means of evaluating if the measured changes in

and CBF are accurate, considering there should be no corresponding change in

. 46 To assess depth sensitivity, the TR-NIRS data were acquired at a short source–detector distance (

) of 1 cm, which is predominately sensitivity to the scalp, and two longer distances (

and 4 cm) to increase the sensitivity to the brain. In addition, moment analysis was applied to recorded DTOFs since higher moments are more sensitive to late-arriving photons due to the right skewness of these distributions.…”

Section: Introductionmentioning

confidence: 99%

Direct assessment of extracerebral signal contamination on optical measurements of cerebral blood flow, oxygenation, and metabolism

et al. 2020

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Significance: Near-infrared spectroscopy (NIRS) combined with diffuse correlation spectroscopy (DCS) provides a noninvasive approach for monitoring cerebral blood flow (CBF), oxygenation, and oxygen metabolism. However, these methods are vulnerable to signal contamination from the scalp. Our work evaluated methods of reducing the impact of this contamination using time-resolved (TR) NIRS and multidistance (MD) DCS. Aim: The magnitude of scalp contamination was evaluated by measuring the flow, oxygenation, and metabolic responses to a global hemodynamic challenge. Contamination was assessed by collecting data with and without impeding scalp blood flow. Approach: Experiments involved healthy participants. A pneumatic tourniquet was used to cause scalp ischemia, as confirmed by contrast-enhanced NIRS, and a computerized gas system to generate a hypercapnic challenge. Results: Comparing responses acquired with and without the tourniquet demonstrated that the TR-NIRS technique could reduce scalp contributions in hemodynamic signals up to 4 times (r SD ¼ 3 cm) and 6 times (r SD ¼ 4 cm). Similarly, blood flow responses from the scalp and brain could be separated by analyzing MD DCS data with a multilayer model. Using these techniques, there was no change in metabolism during hypercapnia, as expected, despite large increases in CBF and oxygenation. Conclusion: NIRS/DCS can accurately monitor CBF and metabolism with the appropriate enhancement to depth sensitivity, highlighting the potential of these techniques for neuromonitoring.

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“…Non-invasive measurements of CVR have found clinical applications in a broad spectrum of brain diseases including arterial stenosis ( De Vis et al, 2015 ; Liu et al, 2017 ; Mandell et al, 2008 ), stroke ( Geranmayeh et al, 2015 ; Taneja et al, 2019 ), brain tumors ( Fierstra et al, 2016 ), traumatic brain injury ( Chan et al, 2015 ), dementia ( Yezhuvath et al, 2012 ), multiple sclerosis ( Marshall et al, 2014 ), and normal aging ( Lu et al, 2011 ; McKetton et al, 2018 ; Peng et al, 2018 ). Additionally, CVR has also been used for the calibration of fMRI signal and estimation of cerebral metabolic rate of oxygen consumption (CMRO 2 ) ( Bright et al, 2017 ; Davis et al, 1998 ; Gauthier and Hoge, 2013 ; Hoge et al, 1999 ; Liu et al, 2013 ; Murphy et al, 2011 ).…”

Section: Introductionmentioning

confidence: 99%

The association between BOLD-based cerebrovascular reactivity (CVR) and end-tidal CO2 in healthy subjects

Hou

Liu

et al. 2020

NeuroImage

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Cerebrovascular reactivity (CVR) mapping using CO 2 -inhalation can provide important insight into vascular health. At present, blood-oxygenation-level-dependent (BOLD) MRI acquisition is the most commonly used CVR method due to its high sensitivity, high spatial resolution, and relatively straightforward processing. However, large variations in CVR across subjects and across different sessions of the same subject are often observed, which can cloud the ability of this promising measure in detecting diseases or monitoring treatment responses. The present work aims to identify the physiological components underlying the observed variability in CVR data. When studying the association between CVR value and the subject’s CO 2 levels in a total of N = 253 healthy participants, we found that CVR was lower in individuals with a higher basal end-tidal CO 2 , EtCO 2 (slope = −0.0036 ± 0.0008%/mmHg 2 , p < 0.001), or with a greater EtCO 2 change (ΔEtCO 2 ) with hypercapnic condition (slope = −0.0072 ± 0.0018%/mmHg 2 , p < 0.001). In a within-subject setting, when studying the CVR difference between two repeated scans (with repositioning) in relation to the corresponding differences in basal EtCO 2 and ΔEtCO 2 (n = 11), it was found that CVR values were lower if the basal EtCO 2 or ΔEtCO 2 during that particular scan session was greater. The present work suggests that basal physiological state and the level of hypercapnic stimulus intensity should be considered in application studies of CVR in order to reduce inter-subject and intra-subject variations in the data. Potential approaches to use these findings to reduce noise and augment sensitivity are proposed.

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Multiparametric measurement of cerebral physiology using calibrated fMRI

Cited by 22 publications

References 192 publications

Cortical laminar resting‐state signal fluctuations scale with the hypercapnic blood oxygenation level‐dependent response

Cortical laminar resting‐state signal fluctuations scale with the hypercapnic blood oxygenation level‐dependent response

Direct assessment of extracerebral signal contamination on optical measurements of cerebral blood flow, oxygenation, and metabolism

The association between BOLD-based cerebrovascular reactivity (CVR) and end-tidal CO2 in healthy subjects

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