The pulsatility volume index: an indicator of cerebrovascular compliance based on fast magnetic resonance imaging of cardiac and respiratory pulsatility

Bianciardi, Marta; Toschi, Nicola; Polimeni, Jon̈athan R.; Evans, Karleyton C.; Bhat, Himanshu; Keil, Boris; Rosen, Bruce R.; Boas, David A.; Wald, Lawrence L.

doi:10.1098/rsta.2015.0184

Cited by 23 publications

(35 citation statements)

References 27 publications

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“…The overall phenomenon of brain tissue motion is subtle, involving submillimetre displacements and very small flow changes in the microvasculature . General improvements in available hardware, software and imaging techniques since the early exploration of brain tissue motion using MRI have allowed renewed interest in the phenomenon of brain tissue motion in healthy subjects as well as patients .…”

Section: Introductionmentioning

confidence: 99%

“…The overall phenomenon of brain tissue motion is subtle, involving submillimetre displacements 4 and very small flow changes in the microvasculature. 5 General improvements in available hardware, software and imaging techniques since the early exploration of brain tissue motion using MRI [6][7][8][9] have allowed renewed interest in the phenomenon of brain tissue motion in healthy subjects as well as patients. 10,11 Displacement encoding via stimulated echoes (DENSE), a non-invasive MRI technique, was shown to be a feasible method for capturing the displacement vector fields that characterize brain tissue pulsatility, 4,12,13 thereby allowing the derivation of brain tissue volumetric strain.…”

Section: Introductionmentioning

confidence: 99%

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Quantifying cardiac‐induced brain tissue expansion using DENSE

et al. 2018

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Brain tissue undergoes viscoelastic deformation and volumetric strain as it expands over the cardiac cycle due to blood volume changes within the underlying microvasculature. Volumetric strain measurements may therefore provide insights into small vessel function and tissue viscoelastic properties. Displacement encoding via stimulated echoes (DENSE) is an MRI technique that can quantify the submillimetre displacements associated with brain tissue motion. Despite previous studies reporting brain tissue displacements using DENSE and other MRI techniques, a complete picture of brain tissue volumetric strain over the cardiac cycle has not yet been obtained. To address this need we implemented 3D cine‐DENSE at 7 T and 3 T to investigate the feasibility of measuring cardiac‐induced volumetric strain as a marker for small vessel blood volume changes. Volumetric strain over the entire cardiac cycle was computed for the whole brain and for grey and white matter tissue separately in six healthy human subjects. Signal‐to‐noise ratio (SNR) measurements were used to determine the voxel‐wise volumetric strain noise. Mean peak whole brain volumetric strain at 7 T (mean ± SD) was (4.5 ± 1.0) × 10 −4 (corresponding to a volume expansion of 0.48 ± 0.1 mL), which is in agreement with literature values for cerebrospinal fluid that is displaced into the spinal canal to maintain a stable intracranial pressure. The peak volumetric strain ratio of grey to white matter was 4.4 ± 2.8, reflecting blood volume and tissue stiffness differences between these tissue types. The mean peak volumetric strains of grey and white matter tissue were found to be significantly different ( p < 0.001). The mean SNR at 7 T and 3 T of the DENSE measurements was 22.0 ± 7.3 and 7.0 ± 2.8 respectively, which currently limits a voxel‐wise strain analysis at both field strengths. We demonstrate that tissue specific quantification of volumetric strain is feasible with DENSE. This metric holds potential for studying blood volume pulsations in the ageing brain in healthy and diseased states.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quantifying cardiac‐induced brain tissue expansion using DENSE

et al. 2018

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“…An experimental measurement of all components in the multi-exponential model is difficult and often a simplified mono-exponential decay is used instead ( Zhao et al., 2007 , Bianciardi et al., 2016 )

…”

Section: Theorymentioning

confidence: 99%

“…Inflow effects and partial volume fluctuations will manifest in S 0 ( τ ). This can be written more explicitly as

( Bianciardi et al., 2016 ), where M 0 is the equilibrium magnetisation and α the radio-frequency (RF) flip angle.

and

determine the amount of already RF-excited spins being replaced with fresh ones in the voxel.…”

Section: Theorymentioning

confidence: 99%

Cardiac cycle-induced EPI time series fluctuations in the brain: Their temporal shifts, inflow effects and T2∗ fluctuations

2017

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The cardiac-induced arterial pressure wave causes changes in cerebral blood flow velocities and volumes that affect the signals in echo-planar imaging (EPI). Using single-echo EPI time series data, acquired fast enough to unalias the cardiac frequency, we found that the cardiac cycle-induced signal fluctuations are delayed differentially in different brain regions. When referenced to the time series in larger arterial structures, the cortical voxels are only minimally shifted but significant shifts are observed in subcortical areas. Using double-echo EPI data we mapped the voxels’ “signal at zero echo time”, S0, and apparent T2∗ over the cardiac cycle. S0 pulsatility was maximised for voxels with a cardiac cycle-induced timing that was close to the arterial structures and is likely explained by enhanced inflow effects in the cortical areas compared to subcortical areas. Interestingly a consistent T2∗ waveform over the cardiac cycle was observed in all voxels with average amplitude ranges between 0.3-0.55% in grey matter and 0.15–0.22% in white matter. The timing of the T2∗ waveforms suggests a partial volume fluctuation where arteriolar blood volume changes are counterbalanced by changes in CSF volumes.

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“…Specifically, Bianciardi et al [31] perform an initial validation of a novel MRI indicator of cerebrovascular compliance measured at ultra-high field (7 T), which might prove useful to investigate brain-heart interactions in cerebrovascular disease and other disorders. Duggento et al [32] demonstrate that ultra-high field functional imaging coupled with physiological signal acquisition and Granger causality analysis is able to quantify directed brain-brain and brain-heart interactions reflecting central modulation of autonomic outflow.…”

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confidence: 99%

Uncovering brain–heart information through advanced signal and image processing

Valenza

Toschi

Barbieri

2016

Phil. Trans. R. Soc. A.

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Through their dynamical interplay, the brain and the heart ensure fundamental homeostasis and mediate a number of physiological functions as well as their disease-related aberrations. Although a vast number of ad hoc analytical and computational tools have been recently applied to the non-invasive characterization of brain and heart dynamic functioning, little attention has been devoted to combining information to unveil the interactions between these two physiological systems. This theme issue collects contributions from leading experts dealing with the development of advanced analytical and computational tools in the field of biomedical signal and image processing. It includes perspectives on recent advances in 7 T magnetic resonance imaging as well as electroencephalogram, electrocardiogram and cerebrovascular flow processing, with the specific aim of elucidating methods to uncover novel biological and physiological correlates of brain–heart physiology and physiopathology.

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The pulsatility volume index: an indicator of cerebrovascular compliance based on fast magnetic resonance imaging of cardiac and respiratory pulsatility

Cited by 23 publications

References 27 publications

Quantifying cardiac‐induced brain tissue expansion using DENSE

Quantifying cardiac‐induced brain tissue expansion using DENSE

Cardiac cycle-induced EPI time series fluctuations in the brain: Their temporal shifts, inflow effects and T2∗ fluctuations

Uncovering brain–heart information through advanced signal and image processing

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