Measuring brain beats: Cardiac-aligned fast functional magnetic resonance imaging signals

Coupled pulsatile vascular and paravascular fluid dynamics in the human brain

BACKGROUND

Cardiac pulsation propels blood through the cerebrovascular network to maintain cerebral homeostasis. The cerebrovascular network is uniquely surrounded by paravascular cerebrospinal fluid (pCSF), which plays a crucial role in waste removal, and its flow is suspected to be driven by arterial pulsations. Despite its importance, the relationship between vascular and paravascular fluid dynamics throughout the cardiac cycle remains poorly understood in humans.

METHODS

In this study, we developed a non-invasive neuroimaging approach to investigate the coupling between pulsatile vascular and pCSF dynamics within the subarachnoid space of the human brain. Resting-state functional MRI (fMRI) and dynamic diffusion-weighted imaging (dynDWI) were retrospectively cardiac-aligned to represent cerebral hemodynamics and pCSF motion, respectively. We measured the time between peaks (∆TTP) ind d ϕ f M R I and dynDWI waveforms and measured their coupling by calculating the waveforms correlation after peak alignment (correlation at aligned peaks). We compared the ∆TTP and correlation at aligned peaks between younger [mean age: 27.9 (3.3) years, n = 9] and older adults [mean age: 70.5 (6.6) years, n = 20], and assessed their reproducibility within subjects and across different imaging protocols.

RESULTS

Hemodynamic changes consistently precede pCSF motion. ∆TTP was significantly shorter in younger adults compared to older adults (-0.015 vs. -0.069, p < 0.05). The correlation at aligned peaks were high and did not differ between younger and older adults (0.833 vs. 0.776, p = 0.153). The ∆TTP and correlation at aligned peaks were robust across fMRI protocols (∆TTP: -0.15 vs. -0.053, p = 0.239; correlation at aligned peaks: 0.813 vs. 0.812, p = 0.985) and demonstrated good to excellent within-subject reproducibility (∆TTP: intraclass correlation coefficient = 0.36; correlation at aligned peaks: intraclass correlation coefficient = 0.89).

CONCLUSION

This study proposes a non-invasive technique to evaluate vascular and paravascular fluid dynamics. Our findings reveal a consistent and robust cardiac pulsation-driven coupling between cerebral hemodynamics and pCSF dynamics in both younger and older adults.

Robust data-driven segmentation of pulsatile cerebral vessels using functional magnetic resonance imaging

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.

Cerebrovascular Responses in a Patient with Lundberg B Waves Following Subarachnoid Haemorrhage Assessed with a Novel Non-Invasive Brain Pulse Monitor: A Case Report

Subarachnoid haemorrhage (SAH) can trigger a range of poorly understood cerebrovascular responses that may play a role in delayed cerebral ischemia. The brain pulse monitor is a novel non-invasive device that detects a brain photoplethysmography signal that provides information on intracranial pressure (ICP), compliance, blood flow and tissue oxygen saturation. We monitored the cerebrovascular responses in a patient with Lundberg B waves following a SAH. The patient presented with a Fischer grade 4 SAH that required urgent left posterior communicating artery aneurysm coiling and ventricular drain insertion. On hospital day 4 oscillations or spikes on the invasive ICP were noted, consistent with Lundberg B waves. Brain pulse monitoring demonstrated concurrent pulse waveform features consistent with reduced brain compliance and raised ICP over both brain hemispheres. Oxygen levels also demonstrated slow oscillations correlated with the ICP spikes. Brief infrequent episodes of reduced and absent brain pulses were also noted over the right hemisphere. Our findings suggest that the brain pulse monitor holds promise for early detection of delayed cerebral ischemia and could offer insights into the vascular mechanisms at play.

A characterization of cardiac-induced noise in R2 * maps of the brain

PURPOSE

Cardiac pulsation increases the noise level in brain maps of the transverse relaxation rate R2 *. Cardiac-induced noise is challenging to mitigate during the acquisition of R2 * mapping data because its characteristics are unknown. In this work, we aim to characterize cardiac-induced noise in brain maps of the MRI parameter R2 *.

METHODS

We designed a sampling strategy to acquire multi-echo 3D data in 12 intervals of the cardiac cycle, monitored with a fingertip pulse-oximeter. We measured the amplitude of cardiac-induced noise in this data and assessed the effect of cardiac pulsation on R2 * maps computed across echoes. The area of k-space that contains most of the cardiac-induced noise in R2 * maps was then identified. Based on these characteristics, we introduced a tentative sampling strategy that aims to mitigate cardiac-induced noise in R2 * maps of the brain.

RESULTS

In inferior brain regions, cardiac pulsation accounts for R2 * variations of up to 3 s-1 across the cardiac cycle (i.e., ∼35% of the overall variability). Cardiac-induced fluctuations occur throughout the cardiac cycle, with a reduced intensity during the first quarter of the cycle. A total of 50% to 60% of the overall cardiac-induced noise is localized near the k-space center (k < 0.074 mm-1 ). The tentative cardiac noise mitigation strategy reduced the variability of R2 * maps across repetitions by 11% in the brainstem and 6% across the whole brain.

CONCLUSION

We provide a characterization of cardiac-induced noise in brain R2 * maps that can be used as a basis for the design of mitigation strategies during data acquisition.