Towards mapping CSF volume change at high resolutions at 7T
Poster No:
1990
Submission Type:
Abstract Submission
Authors:
Stephanie Swegle1, Renzo Huber1, Rüdiger Stirnberg2, Peter Molfese1, Linqing Li1, Catherine Walsh1, A. Tyler Morgan1, Peter Bandettini1
Institutions:
1National Institute of Mental Health, Bethesda, MD, 2German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
First Author:
Co-Author(s):
Introduction:
Dynamic CSF acts as a clearance system in the human brain. Current research has focused on quantifying changes of CSF flow during sleep and brain activity and found dynamic changes of CSF during task activation (Fultz, 2019; Kim, 2022). Since CSF flow imaging is constrained by low velocities and directional dependencies, CSF volume imaging may be more straightforwardly measured. In this abstract, we aim to develop, implement, and validate a new imaging approach to quantify functional changes of CSF volume across the human brain.
Previous fMRI literature on cerebral blood volume (CBV) imaging (Lu, 2013) shows that CSF volume changes can be a contributor and contaminant in Vascular Space Occupancy (VASO) (Donahue, 2006; Scouten, 2008). So, we use a VASO-like inversion recovery (IR) sequence to capture CSF volume changes. Specifically, we propose an inversion recovery 7T 3D-EPI protocol that uses CSF's specific relaxation "fingerprint" to capture voxel-specific CSF volume fractions independent of dynamic changes in CBV and BOLD.
Previous fMRI literature on cerebral blood volume (CBV) imaging (Lu, 2013) shows that CSF volume changes can be a contributor and contaminant in Vascular Space Occupancy (VASO) (Donahue, 2006; Scouten, 2008). So, we use a VASO-like inversion recovery (IR) sequence to capture CSF volume changes. Specifically, we propose an inversion recovery 7T 3D-EPI protocol that uses CSF's specific relaxation "fingerprint" to capture voxel-specific CSF volume fractions independent of dynamic changes in CBV and BOLD.
Methods:
We use a multi-echo multi-TI approach to quantify BOLD independent of MZ modulation of CSF to separate CBV volume changes from CSF volume changes. We collected images with three echoes and three inversion times at 7T (N=8 sessions at 7T (Siemens, Germany) with 8Tx/32Rx head coil (Nova, USA)). The TE, TI, T1 and T2* values that we used are shown in Figure 1C (Ivanov, 2013; Donahue, 2011). The sequence developments conducted here are implemented in a 3D-EPI with Skipped-CAIPI framework (Stirnberg, 2021).
To validate the sensitivity of our sequence to simultaneously capture CBV/CSF/BOLD, we employed a 12-14 minute block designed (30sec blocks) flashing checkerboards.
In-scanner eye tracking (EyeLink-1000Plus, SR-Research) and physiological monitoring (BioPack) was done during fMRI resting state scans to obtain a measure of drowsiness and respiratory volume as correlates of CSF volume dynamics (Aktas, 2019).
Images were processed using AFNI_24.2.01, LayNii_v2.7.0, SPM12, and FSL 1.12.4. We use an additive multi-compartment model to estimate functional contributions of CSF volume, CBV, and BOLD.
Parameters: https://github.com/nimh-sfim/mapping_CSF_volume
To validate the sensitivity of our sequence to simultaneously capture CBV/CSF/BOLD, we employed a 12-14 minute block designed (30sec blocks) flashing checkerboards.
In-scanner eye tracking (EyeLink-1000Plus, SR-Research) and physiological monitoring (BioPack) was done during fMRI resting state scans to obtain a measure of drowsiness and respiratory volume as correlates of CSF volume dynamics (Aktas, 2019).
Images were processed using AFNI_24.2.01, LayNii_v2.7.0, SPM12, and FSL 1.12.4. We use an additive multi-compartment model to estimate functional contributions of CSF volume, CBV, and BOLD.
Parameters: https://github.com/nimh-sfim/mapping_CSF_volume
Results:
Figure 1A-B shows unique signal fingerprints of tissue types across TI and TE combinations. Dependent on T1-weighting of CSF/CBV and T2*-weighting of BOLD, the fMRI contrast is modulated in polarity and strength. This is an indication of concomitant changes of volume redistributions independent of BOLD. Figure 1C-E shows task-induced activation in the visual cortex at high resolution, in time courses, and at whole brain. Panel D shows variation in activation responding to visual stimuli for the different TI-TE combinations; early TI resulted in negative signal changes, while later TIs resulted in increasingly positive signal changes. Functional responses were stronger at later echo times, as expected from GE-BOLD.
Figure 2 confirms that the method can spatially map CSF. There are indications of a small CSF volume reduction in voxels above the cortical ribbon consistent with previous work (Donahue, 2011). CSF-weighted signal changes are largest above the cortex, while CBV and BOLD show relatively more signal changes within GM. GE-BOLD exhibits a signal increase towards the cortical surface, as expected from draining vein effects.
Figure 2H shows that as eyes get more drowsy, CSF volume increases. Figure 2I-J also shows preliminary results of potential correlates of vigilance during eye tracking at both high resolution and low resolution.
Figure 2 confirms that the method can spatially map CSF. There are indications of a small CSF volume reduction in voxels above the cortical ribbon consistent with previous work (Donahue, 2011). CSF-weighted signal changes are largest above the cortex, while CBV and BOLD show relatively more signal changes within GM. GE-BOLD exhibits a signal increase towards the cortical surface, as expected from draining vein effects.
Figure 2H shows that as eyes get more drowsy, CSF volume increases. Figure 2I-J also shows preliminary results of potential correlates of vigilance during eye tracking at both high resolution and low resolution.
Conclusions:
We created a novel sequence that can dynamically track functional changes of CSF, CBV, and BOLD concomitantly. Our multi-inversion and multi-echo data can track how the signal of blood differs from the signal of CSF, at both high resolution and whole brain. This method could help researchers better understand the crucial roles that CSF plays, like removal of waste in the brain.
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 2
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Neuroanatomy Other
Novel Imaging Acquisition Methods:
BOLD fMRI
Non-BOLD fMRI 1
Physiology, Metabolism and Neurotransmission:
Physiology, Metabolism and Neurotransmission Other
Keywords:
Acquisition
Blood
Cerebro Spinal Fluid (CSF)
fMRI CONTRAST MECHANISMS
FUNCTIONAL MRI
HIGH FIELD MR
1|2Indicates the priority used for review
Abstract Information
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