Biology subjects

van Heeswijk, R. B.

Publications and source records attributed to van Heeswijk, R. B..

4 recordsLinked to original sources

bioRxiv2025

ISME - Incoherent Sampling of Multi-Echo data to minimize cardiac-induced noise in brain maps of R2* and magnetic susceptibility

AbstractO_ST_ABSPurposeC_ST_ABSMaps of the MRI parameters R2* and magnetic susceptibility () enable the investigation of microscopic tissue changes in brain disease. However, cardiac-induced signal instabilities increase the variability of brain maps of R2* and . In this study, we introduce ISME - a sampling strategy that minimizes the level of cardiac-induced instabilities in brain maps of R2* and . MethodsISME uses phase-encoding gradients to shift the k-space frequency of the acquired data between consecutive readouts of a multi-echo train. As a result, the multi-echo data at a given k-space index is acquired at different phases of the cardiac cycle. We compare the variability of R2* and maps acquired with ISME and with standard multi-echo trajectories in N=10 healthy volunteers. We investigate the effect of both trajectories on the spatial aliasing of pulsating MR signals and propose a weighted-least squares (NWLS) approach for the estimation of R2* that accounts for the increase of the residuals with echo time. ResultsISME reduces the variability of R2* and maps across repetitions by 25/26/21% and 24/32/23% in the cerebellum/brainstem/whole brain, respectively. With ISME, the spatial aliasing of pulsating MR signals is incoherent between raw echo images, leading to visually sharper R2* maps. The proposed NWLS approach for the estimation of R2* reduces the dependence of the fitting residuals on echo time and the variability of R2* by an additional 3/2/1% in the cerebellum/brainstem/whole brain. ConclusionISME allows the mitigation of cardiac-induced signal instabilities in brain maps of R2* and , improving reproducibility.

neuroscience↗

bioRxiv2024

Data acquisition strategies to reduce cardiac-induced noise in brain maps of R2* and magnetic susceptibility

Maps of the transverse relaxation rate R2* and magnetic susceptibility () are computed from gradient- echo data acquired at multiple echo times and are sensitive to signal instabilities induced by cardiac pulsation. Here, we introduce two k-space sampling strategies that aim to mitigate the impact of cardiac-induced noise in brain maps of R2* and . The proposed strategies are based on the higher level of cardiac-induced noise near the k-space centre compared to the periphery. Using a CArtesian trajectory with Spiral PRofile (CASPR), the first strategy allows for the acquisition of a specific number of averages at each k-space location, derived from the local level of cardiac-induced noise. The second strategy synchronizes the acquisition near the k-space centre with the cardiac cycle in real time. We compared the variability across 4 repetitions of R2* and maps computed from data acquired using both strategies and with a standard linear trajectory. Data was acquired in 10 healthy volunteers. Compared to linear trajectory, the CASPR trajectory reduced the variability of R2* and maps across repetitions by 26/28/22% and 19/18/16% in the brainstem/cerebellum/whole brain, for a 14% increase in scan time. The CASPR trajectory also reduced the level of aliasing artifacts from pulsating blood vessels. The synchronized trajectory did not reduce the variability of R2* or maps. CASPR trajectories can be designed to mitigate cardiac-induced noise in brain maps of the MRI parameters R2* and . Synchronization of data acquisition with the cardiac cycle did not reduce the level of cardiac-induced noise.

neuroscience↗

bioRxiv2023

Hi-Fi fMRI: High-resolution, fast-sampled and sub-second whole-brain functional MRI at 3T in humans

Functional magnetic resonance imaging (fMRI) is a methodological cornerstone of neuroscience. Most studies measure blood-oxygen-level-dependent (BOLD) signal using echo-planar imaging (EPI), Cartesian sampling, and image reconstruction with a one-to-one correspondence between the number of acquired volumes and reconstructed images. However, EPI schemes are subject to trade-offs between spatial and temporal resolutions. We make strides in overcoming these limitations by measuring BOLD with a gradient recalled echo (GRE) with a 3D radial-spiral phyllotaxis trajectory at a high sampling rate (28.49ms) on standard 3T field strength. The framework enables the reconstruction of 3D signal time courses with whole-brain coverage at simultaneously higher nominal spatial (1mm3) and temporal (up to 250ms) resolutions, as compared to optimized EPI schemes. Additionally, we apply motion correction directly to the k-space raw data, enabling flexible motion-corrected reconstructions; the desired temporal resolution to observe hemodynamic responses can be chosen after scanning. By showing activation in the calcarine sulcus of 20 participants completing an ON-OFF visual paradigm, we demonstrate the reliability of our method for applications in cognitive neuroscience research.

neuroscience↗

bioRxiv2022

Characterization of cardiac-induced noise in R2* maps of the brain

PurposeCardiac 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 therefore aim to characterize cardiac-induced noise in brain maps of the MRI parameter R2*. MethodsWe 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. ResultsIn inferior brain regions, cardiac pulsation accounts for R2* variations of up to 3s-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. 50-60% of the overall cardiac-induced noise is localized near the k-space centre (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. ConclusionWe provide a characterisation of cardiac-induced noise in brain R2* maps that can be used as a basis for the design of mitigation strategies during data acquisition.

neuroscience↗