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Bhogal, A. A.

Publications and source records attributed to Bhogal, A. A..

7 recordsLinked to original sources

Cerebrovascular pulsatility differs across vascular compartments and is altered by hypercapnic stimuli: a BOLD fMRI study

Cerebral small vessel disease and neurodegenerative disorders have been associated with increased cerebrovascular pulsatility. Recently, BOLD fMRI-based methods have emerged for assessing pulsatility, however their interpretability is limited because the relation between estimated pulsatility indices (PI) and vascular anatomy and physiology remains poorly understood. To improve interpretability, we introduce a cardiac-specific BOLD fMRI- based PI, investigate its relationship to the cortical vasculature, and validate its sensitivity by introducing the known physiological vascular modulation of hypercapnia. Using high-resolution 7T BOLD fMRI with gradient-echo (GE) and spin-echo (SE) sequences, we disentangled macro- and microvascular contributions to the PI and quantified it across cortical depth. PI maps revealed anatomically plausible patterns, with elevated GE-PI near large veins and in white matter while SE-PI remained largely constant across cortical depth. GE-PI decreased during hypercapnia consistent with altered vascular tone, SE-PI on the other hand did not. PI correlated with cerebrovascular reactivity and venous blood volume suggesting sensitivity to vascular density and vessel mechanics. Our findings demonstrate that BOLD-derived PI provides a spatially and physiologically specific measure of vascular pulsatility. The BOLD fMRI-based PI method is readily applicable to existing datasets and has potential for assessing potential microvascular damage in cerebrovascular and neurodegenerative disease.

neuroscience↗

A fully synthetic three-dimensional human cerebrovascular model based on histological characteristics to investigate the hemodynamic fingerprint of the layer BOLD fMRI signal formation

Recent advances in functional magnetic resonance imaging (fMRI) at ultra-high field ([≥]7 tesla), novel hardware, and data analysis methods have enabled detailed research on neurovascular function, such as cortical layer-specific activity, in both human and nonhuman species. A widely used fMRI technique relies on the blood oxygen level-dependent (BOLD) signal. BOLD fMRI offers insights into brain function by measuring local changes in cerebral blood volume, cerebral blood flow, and oxygen metabolism induced by increased neuronal activity. Despite its potential, interpreting BOLD fMRI data is challenging as it is only an indirect measurement of neuronal activity. Computational modeling can help interpret BOLD data by simulating the BOLD signal formation. Current developments have focused on realistic 3D vascular models based on rodent data to understand the spatial and temporal BOLD characteristics. While such rodent-based vascular models highlight the impact of the angioarchitecture on the BOLD signal amplitude, anatomical differences between the rodent and human vasculature necessitate the development of human-specific models. Therefore, a computational framework integrating human cortical vasculature, hemodynamic changes, and biophysical properties is essential. Here, we present a novel computational approach: a three-dimensional VAscular MOdel based on Statistics (3D VAMOS), enabling the investigation of the hemodynamic fingerprint of the BOLD signal within a model encompassing a fully synthetic human 3D cortical vasculature and hemodynamics. Our algorithm generates microvascular and macrovascular architectures based on morphological and topological features from the literature on human cortical vasculature. By simulating specific oxygen saturation states and biophysical interactions, our framework characterizes the intravascular and extravascular signal contributions across cortical depth and voxel-wise levels for gradient-echo and spin-echo readouts. Thereby, the 3D VAMOS computational framework demonstrates that using human characteristics significantly affects the BOLD fingerprint, making it an essential step in understanding the fundamental underpinnings of layer-specific fMRI experiments.

neuroscience↗

Microvascular Specificity of Spin Echo BOLD fMRI: Impact of EPI Echo Train Length

A spatially specific fMRI acquisition requires specificity to the microvasculature that serves active neuronal sites. Macrovascular contributions will reduce the microvascular specificity but can be reduced by using spin echo (SE) sequences that use a {pi} pulse to refocus static field inhomogeneities near large veins. The microvascular specificity of a SE-echo planar imaging (SE-EPI) scan depends on the echo train length (ETL)-duration, but the dependence is not well-characterized in humans at 7T. To determine how microvascular-specific SE-EPI BOLD is in humans at 7T, we developed a Monte Carlo voxel model that computes the signal of a proton ensemble residing in a vasculature subjected to a SE-EPI pulse sequence. We characterized the ETL-duration dependence of the microvascular specificity by simulating the BOLD signal as a function of ETL, the range adhering to experimentally realistic readouts. We performed a validation experiment for our simulation observations, in which we acquired a set of SE-EPI BOLD time series with varying ETL during a hyperoxic gas challenge. Both our simulations and measurements show an increase in macrovascular contamination as a function of ETL, with an increase of 30% according to our simulation and 60% according to our validation experiment between the shortest and longest ETL durations (23.1 - 49.7 ms). We conclude that the microvascular specificity decreases heavily with increasing ETL-durations. We recommend reducing the ETL-duration as much as possible to minimize macrovascular contamination in SE-EPI BOLD experiments. We additionally recommend scanning at high resolutions to minimize partial volume effects with CSF. CSF voxels show a large BOLD response, which can be attributed to both the presence of large veins (high blood volume) and molecular oxygen-induced T1-shortening (significant in a hyperoxia experiment). The magnified BOLD signal in a GM-CSF partial volume voxel reduces the desired microvascular specificity and, therefore, will hinder the interpretation of functional MRI activation patterns.

neuroscience↗

Quantifying cerebral blood arrival times using hypoxia-mediated arterial BOLD contrast

Cerebral blood arrival and tissue transit times are sensitive measures of the efficiency of tissue perfusion and can provide clinically meaningful information on collateral blood flow status. We exploit the arterial blood oxygen level dependent (BOLD) signal contrast established by precisely modulating arterial hemoglobin saturation using hypoxic respiratory challenges (dOHb-BOLD) to quantify arterial blood arrival times throughout the brain. A combination of hemodynamic lag with a modified carpet plot analysis yielded lag, onset (blood arrival), mean transit time (MTT) and hypoxic response information, which is indicative of relative total blood volume. Onset times averaged across 12 healthy subjects were 1.1 {+/-} 0.4 and 1.9 {+/-} 0.6 for cortical gray and deep white matter, respectively. The average whole brain MTT was 4.5 {+/-} 0.9 seconds. The dOHb-BOLD response was 1.7 fold higher in grey versus white; in line with known differences in regional blood volume fraction. Our method was also applied in unilateral carotid artery occlusion patient, which revealed prolonged signal onset with normal perfusion in the affected hemisphere. In cases with exhausted reserve capacity or confounding flow effects such as vascular steal, dOHb-BOLD can potentially inform on collateral flow pathways to provide a valuable compliment to clinical vascular reactivity measures.

neuroscience↗

The many layers of BOLD. On the contribution of different vascular compartments to laminar fMRI.

Ultra-high field functional Magnetic Resonance Imaging (fMRI) offers the spatial resolution to measure neural activity at the scale of cortical layers. Most fMRI studies make use of the Blood-Oxygen-Level Dependent (BOLD) signal, arising from a complex interaction of changes in cerebral blood flow (CBF) and volume (CBV), and venous oxygenation. However, along with cyto- and myeloarchitectural changes across cortical depth, laminar fMRI is confronted with additional confounds related to vascularization differences that exist across cortical depth. In the current study, we quantify how the non-uniform distribution of macro- and micro-vascular compartments, as measured with Gradient-Echo (GE) and Spin-Echo (SE) scan sequences, respectively, affect laminar BOLD fMRI responses following evoked hypercapnic and hyperoxic breathing conditions. We find that both macro- and micro-vascular compartments are capable of comparable theoretical maximum signal intensities, as represented by the M-scaling parameter. However, the capacity for vessel dilation, as reflected by the cerebrovascular reactivity (CVR), is approximately three times larger for the macro-compared to the micro-vasculature at superficial layers. Finally, there is roughly a 35% difference in CBV estimates between the macro- and micro-vascular compartments, although this relative difference is approximately uniform across cortical depth.

neuroscience↗

Medullary vein architecture modulates the white matter BOLD cerebrovascular reactivity signal response to CO2: observations from high-resolution T2* weighted imaging at 7T

Brain stress testing using blood oxygenation level-dependent (BOLD) MRI to evaluate changes in cerebrovascular reactivity (CVR) is of growing interest for evaluating white matter integrity. However, even under healthy conditions, the white matter BOLD-CVR response differs notably from that observed in the gray matter. In addition to actual arterial vascular control, the venous draining topology may influence the WM-CVR response leading to signal delays and dispersions. These types of alterations in hemodynamic parameters are sometimes linked with pathology, but may also arise from differences in normal venous architecture. In this work, high-resolution T2*weighted anatomical images combined with BOLD imaging during a hypercapnic breathing protocol were acquired using a 7 tesla MRI system. Hemodynamic parameters including base CVR, hemodynamic lag, lag-corrected CVR, response onset and signal dispersion, and finally {Delta}CVR (corrected CVR minus base CVR) were calculated in 8 subjects. Parameter maps were spatially normalized and correlated against an MNI-registered white matter medullary vein atlas. Moderate correlations (Pearsons rho) were observed between medullary vessel frequency (MVF) and {Delta}CVR (0.52; 0.58 for total WM), MVF and hemodynamic lag (0.42; 0.54 for total WM), MVF and signal dispersion (0.44; 0.53 for total WM), and finally MVF and signal onset (0.43; 0.52 for total WM). Results indicate that, when assessed in the context of the WM venous architecture, changes in the response shape may only be partially reflective of the actual vascular reactivity response occurring further upstream by control vessels. This finding may have implications when attributing diseases mechanisms and/or progression to presumed impaired WM BOLD-CVR.

neuroscience↗

Lipid suppressed and tissue-fraction corrected metabolic distributions in human central brain structures using 2D 1H Magnetic Resonance Spectroscopic Imaging at 7 tesla

Magnetic resonance spectroscopic imaging (MRSI) has the potential to add a layer of understanding of the neurobiological mechanisms underlying brain diseases, disease progression, and treatment efficacy. Limitations related to metabolite fitting of low SNR data, signal variations due to partial volume effects, acquisition and extra-cranial lipid artefacts, along with clinically relevant aspects such as scan-time constraints, are among the factors that hinder the widespread implementation of in vivo MRSI. The aim of this work was to address these factors and to develop an acquisition, reconstruction and post-processing pipeline to derive lipid suppressed metabolite values based on Free Induction Decay (FID-MRSI) measurements made using a 7 tesla MR scanner. Anatomical images were used to perform high-resolution (1mm3) partial-volume correction to account for grey matter, white matter and cerebral-spinal fluid signal contributions. Implementation of automatic quality control thresholds and normalization of metabolic maps from 23 subjects to the MNI standard atlas facilitated the creation of high-resolution average metabolite maps of several clinically relevant metabolites in central brain regions, while accounting for macromolecular distributions. Reported metabolite values include glutamate, choline, (phospo)creatine, myo-inositol, glutathione, N-acetyl aspartyl glutamate(and glutamine) and N-acetyl aspartate. MNI-registered average metabolite maps facilitate group-based analysis; thus offering the possibility to mitigate uncertainty in variable MRSI.

neuroscience↗