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•New MRI-based technique for whole-brain 3D quantification of venous CBV (CBVv).•Velocity-selective venous-spin-labeling with 3D GRASE for rapid CBVv mapping.•Sub-minute 3D CBVv imaging enabled via optimization of GRASE parameters.•Strong test-retest agreement observed (ICC ∼ 0.9 and a mean bias ∼ 0).•Clear depiction of bidirectional CBVv responses to breath-hold and caffeine-intake. Venous cerebral blood volume (CBVv) is an important neurophysiological parameter and contributor to the BOLD signal mechanism. However, MRI-based, noninvasive methods for CBVv mapping remain scarce, and existing approaches are limited by estimation errors resulting from a large-scale induced magnetic field or long scan times. To address these challenges, we have developed a rapid whole-brain 3D CBVv mapping technique that combines velocity-selective venous-spin-labeling (VS-VSL) and a 3D gradient-and-spin-echo (GRASE) readout. In the GRASE configuration, variable refocusing flip angles were deployed for a long echo train and a short scan, with a segmented-linear center-out k-space trajectory to minimize signal modulations from alternation of gradient- and spin-echo sampling. Simulations were performed to optimize GRASE parameters for optimal scan efficiency with minimal loss of estimation accuracy, followed by experimental validations on the optimized protocol. The performance of the proposed method was evaluated in healthy subjects in terms of repeat reproducibility, and sensitivity to breath-hold and caffeine-intake challenges, stimuli known to alter blood volume in opposite directions. The optimized VS-VSL 3D GRASE sequence allowed whole-brain 3D CBVv mapping in under one minute scan time with high test-retest reproducibility (R2/ICC = 0.88/0.93 in gray matter (GM) and 0.76/0.87 in white matter (WM)). Furthermore, the method captured the expected CBVv changes in response to both breath-hold (+26.8 % (GM) and +31.2 % (WM)) and caffeine-intake (–16.3 % (GM) and –14.1 % (WM)), all presenting statistical significance (p << 0.01). The results suggest promise of VS-VSL 3D GRASE for future studies assessing spatially and temporally resolved CBVv across the whole brain.

The human brain continuously generates predictions of incoming sensory input and calculates corresponding prediction errors from the perceived inputs to update internal predictions. In human primary somatosensory cortex (area 3b), different cortical layers are involved in receiving the sensory input and generation of error signals. It remains unknown, however, how the layers in the human area 3b contribute to the temporal prediction error processing. To investigate prediction error representation in the area 3b across layers, we acquired layer-specific functional magnetic resonance imaging (fMRI) data at 7T from human area 3b during a task of index finger poking with no-delay, short-delay and long-delay touching sequences. We demonstrate that all three tasks increased activity in both superficial and deep layers of area 3b compared to the random sensory input. The fMRI signal was differentially modulated solely in the deep layers rather than the superficial layers of area 3b by the delay time. Compared with the no-delay stimuli, activity was greater in the deep layers of area 3b during the short-delay stimuli but lower during the long-delay stimuli. This difference activity features in the superficial and deep layers suggest distinct functional contributions of area 3b layers to tactile temporal prediction error processing. The functional segregation in area 3b across layers may reflect that the excitatory and inhibitory interplay in the sensory cortex contributions to flexible communication between cortical layers or between cortical areas. [Display omitted]

•Deoxyhemoglobin sensitive blood volume (CBV) is derived from breath-hold BOLD fMRI.•This BOLD-CBV marker is compared to typical BOLD cerebrovascular reactivity (CVR).•BOLD-CBV and BOLD-CVR are compared as vascular covariates in task-evoked BOLD fMRI. BOLD fMRI signal has been used in conjunction with vasodilatory stimulation as a marker of cerebrovascular reactivity (CVR): the relative change in cerebral blood flow (CBF) arising from a unit change in the vasodilatory stimulus. Using numerical simulations, we demonstrate that the variability in the relative BOLD signal change induced by vasodilation is strongly influenced by the variability in deoxyhemoglobin-containing cerebral blood volume (CBV), as this source of variability is likely to be more prominent than that of CVR. It may, therefore, be more appropriate to describe the relative BOLD signal change induced by an isometabolic vasodilation as a proxy of deoxygenated CBV (CBVdHb) rather than CVR. With this in mind, a new method was implemented to map a marker of CBVdHb, termed BOLD-CBV, based on the normalization of voxel-wise BOLD signal variation by an estimate of the intravascular venous BOLD signal from voxels filled with venous blood. The intravascular venous BOLD signal variation, recorded during repeated breath-holding, was extracted from the superior sagittal sinus in a cohort of 27 healthy volunteers and used as a regressor across the whole brain, yielding maps of BOLD-CBV. In the same cohort, we demonstrated the potential use of BOLD-CBV for the normalization of stimulus-evoked BOLD fMRI by comparing group-level BOLD fMRI responses to a visuomotor learning task with and without the inclusion of voxel-wise vascular covariates of BOLD-CBV and the BOLD signal change per mmHg variation in end-tidal carbon dioxide (BOLD-CVR). The empirical measure of BOLD-CBV accounted for more between-subject variability in the motor task-induced BOLD responses than BOLD-CVR estimated from end-tidal carbon dioxide recordings. The new method can potentially increase the power of group fMRI studies by including a measure of vascular characteristics and has the strong practical advantage of not requiring experimental measurement of end-tidal carbon dioxide, unlike traditional methods to estimate BOLD-CVR. It also more closely represents a specific physiological characteristic of brain vasculature than BOLD-CVR, namely blood volume.

The measurement of cerebral blood volume (CBV) has been the topic of numerous neuroimaging studies. To date, however, most in vivo imaging approaches can only measure CBV summed over all types of blood vessels, including arterial, capillary and venous vessels in the microvasculature (i.e. total CBV or CBVtot). As different types of blood vessels have intrinsically different anatomy, function and physiology, the ability to quantify CBV in different segments of the microvascular tree may furnish information that is not obtainable from CBVtot, and may provide a more sensitive and specific measure for the underlying physiology. This review attempts to summarize major efforts in the development of MRI techniques to measure arterial (CBVa) and venous CBV (CBVv) separately. Advantages and disadvantages of each type of method are discussed. Applications of some of the methods in the investigation of flow-volume coupling in healthy brains, and in the detection of pathophysiological abnormalities in brain diseases such as arterial steno-occlusive disease, brain tumors, schizophrenia, Huntington's disease, Alzheimer's disease, and hypertension are demonstrated. We believe that the continual development of MRI approaches for the measurement of compartment-specific CBV will likely provide essential imaging tools for the advancement and refinement of our knowledge on the exquisite details of the microvasculature in healthy and diseased brains. •To date, most CBV MRI methods measure total CBV.•Arterial and venous blood vessels are intrinsically different.•Here, MRI methods for CBVa and CBVv measurement are reviewed.•Compartment specific flow-volume coupling is investigated using the methods.•Applications of the methods in brain diseases are demonstrated.

•We acquired in situ 3D two-photon fluorescence microscopy data in an optogenetic mouse model and applied our deep learning-based vascular segmentation and image analysis pipeline to map geometric changes across the cerebrovascular network following neuronal activation.•Following neuronal stimulation, 45 % of all vessels showed caliber changes and only 15 % of the responses were constrictions. The absolute CBV change was the largest in the capillaries and smallest in the venules.•We presented first hitherto experimentally-based profiles of resistance and pressure along brain arteriovenous paths, demonstrating U-shaped resistance and sigmoidal pressure gradients.•The flow increases were greater than local resistance decreases would predict, supporting luxurious perfusion of the activated brain region. Neurovascular coupling (NVC), or the adjustment of blood flow in response to local increases in neuronal activity is a hallmark of healthy brain function, and the physiological foundation for functional magnetic resonance imaging (fMRI). However, it remains only partly understood due to the high complexity of the structure and function of the cerebrovascular network. Here we set out to understand NVC at the network level, i.e. map cerebrovascular network reactivity to activation of neighbouring neurons within a 500×500×500 μm3 cortical volume (∼30 high-resolution 3-nL fMRI voxels). Using 3D two-photon fluorescence microscopy data, we quantified blood volume and flow changes in the brain vessels in response to spatially targeted optogenetic activation of cortical pyramidal neurons. We registered the vessels in a series of image stacks acquired before and after stimulations and applied a deep learning pipeline to segment the microvascular network from each time frame acquired. We then performed image analysis to extract the microvascular graphs, and graph analysis to identify the branch order of each vessel in the network, enabling the stratification of vessels by their branch order, designating branches 1–3 as precapillary arterioles and branches 4+ as capillaries. Forty-five percent of all vessels showed significant calibre changes; with 85 % of responses being dilations. The largest absolute CBV change was in the capillaries; the smallest, in the venules. Capillary CBV change was also the largest fraction of the total CBV change, but normalized to the baseline volume, arterioles and precapillary arterioles showed the biggest relative CBV change. From linescans along arteriole-venule microvascular paths, we measured red blood cell velocities and hematocrit, allowing for estimation of pressure and local resistance along these paths. While diameter changes following neuronal activation gradually declined along the paths; the pressure drops from arterioles to venules increased despite decreasing resistance: blood flow thus increased more than local resistance decreases would predict. By leveraging functional volumetric imaging and high throughput deep learning-based analysis, our study revealed distinct hemodynamic responses across the vessel types comprising the microvascular network. Our findings underscore the need for large, dense sampling of brain vessels for characterization of neurovascular coupling at the network level in health and disease.

PurposeImaging glioma biology holds great promise to unravel the complex nature of these tumors. Besides well-established imaging techniques such O-(2-[18F]fluoroethyl)-l-tyrosine (FET)-PET and dynamic susceptibility contrast (DSC) perfusion imaging, amide proton transfer–weighted (APTw) imaging has emerged as a promising novel MR technique. In this study, we aimed to better understand the relation between these imaging biomarkers and how well they capture cellularity and vascularity in newly diagnosed gliomas.MethodsPreoperative MRI and FET-PET data of 46 patients (31 glioblastoma and 15 lower-grade glioma) were segmented into contrast-enhancing and FLAIR-hyperintense areas. Using established cutoffs, we calculated hot-spot volumes (HSV) and their spatial overlap. We further investigated APTw and CBV values in FET-HSV. In a subset of 10 glioblastoma patients, we compared cellularity and vascularization in 34 stereotactically targeted biopsies with imaging.ResultsIn glioblastomas, the largest HSV was found for APTw, followed by PET and CBV (p < 0.05). In lower-grade gliomas, APTw–HSV was clearly lower than in glioblastomas. The spatial overlap of HSV was highest between APTw and FET in both tumor entities and regions. APTw correlated significantly with cellularity, similar to FET, while the association with vascularity was more pronounced in CBV and FET.ConclusionsWe found a relevant spatial overlap in glioblastomas between hotspots of APTw and FET both in contrast-enhancing and FLAIR-hyperintense tumor. As suggested by earlier studies, APTw was lower in lower-grade gliomas compared with glioblastomas. APTw meaningfully contributes to biological imaging of gliomas.

Introducing optogenetics into neurovascular research can provide novel insights into the cell-specific control of the hemodynamic response. To generalize findings from molecular approaches, it is crucial to determine whether light-activated circuits have the same effect on the vasculature as sensory-activated ones. For that purpose, rats expressing channelrhodopsin (ChR2) specific to excitatory glutamatergic neurons were used to measure neural activity, blood flow, hemoglobin-based optical intrinsic signal, and blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) during optogenetic and sensory stimulation. The magnitude of the evoked hemodynamic responses was monotonically correlated with optogenetic stimulus strength. The BOLD hemodynamic response function was consistent for optogenetic and sensory stimuli. The relationship between electrical activities and hemodynamic responses was comparable for optogenetic and sensory stimuli, and better explained by the local field potential (LFP) than the firing rate. The LFP was well correlated with cerebral blood flow, moderately with cerebral blood volume, and less with deoxyhemoglobin (dHb) level. The presynaptic firing rate had little impact on evoking vascular response. Contribution of the postsynaptic LFP to the blood flow response induced by optogenetic stimulus was further confirmed by the application of glutamate receptor antagonists. Overall, neurovascular coupling during optogenetic control of glutamatergic neurons largely conforms to that of a sensory stimulus.

•We developed and validated Carboxymethyl-dextran coated iron oxide nanoparticles (CION).•We disseminated a step-by-step protocol of our one-pot, cost-efficient synthesis protocol.•We performed several experiments in vivo, demonstrating the use of CION for functional and structural MRI applications. Superparamagnetic iron-oxide nanoparticles are robust contrast agents for magnetic resonance imaging (MRI) used for sensitive structural and functional mapping of the cerebral blood volume (CBV) when administered intravenously. To date, many CBV-MRI studies are conducted with Feraheme, manufactured for the clinical treatment of iron-deficiency. Unfortunately, Feraheme is currently not available outside the United States due to commercial and regulatory constraints, making CBV-MRI methods either inaccessible or very costly to achieve. To address this barrier, we developed a simple, one-pot recipe to synthesize Carboxymethyl-dextran coated Iron Oxide Nanoparticles, namely, “CION”, suitable for preclinical CBV-MRI applications. Here we disseminate a step-by-step instruction of our one-pot synthesis protocol, which allows CION to be produced in laboratories with minimal cost. We also characterized different CION-conjugations by manipulating polymer to metal stoichiometric ratio in terms of their size, surface chemistry, and chemical composition, and shifts in MR relaxivity and pharmacokinetics. We performed several proof-of-concept experiments in vivo, demonstrating the utility of CION for functional and structural MRI applications, including hypercapnic CO2 challenge, visual stimulation, targeted optogenetic stimulation, and microangiography. We also present evidence that CION can serve as a cross-modality research platform by showing concurrent in vivo optical and MRI measurement of CBV using fluorescent-labeled CION. The simplicity and cost-effectiveness of our one-pot synthesis method should allow researchers to reproduce CION and tailor the relaxivity and pharmacokinetics according to their imaging needs. It is our hope that this work makes CBV-MRI more openly available and affordable for a variety of research applications.

Cerebral blood volume (CBV) is an essential metric that indicates and evaluates various healthy and pathologic conditions. Most methods of CBV measurement are cumbersome and have a poor temporal resolution. Recently, it has been proposed that signals and derived metrics from cerebral near-infrared spectroscopy (NIRS), a non-invasive sensor, can be used to estimate CBV. However, this association remains vastly unexplored. As such, this scoping review aimed to examine the literature on the relationship between cerebral NIRS signals and CBV. A search of six databases was conducted conforming to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to assess the following search question: What are the associations between various NIRS cerebral signals and CBV? The database search yielded 3350 unique results. Seven of these articles were included in this review based on the inclusion and exclusion criteria. An additional study was identified and included while examining the articles’ reference sections. Overall, the literature for this systematic scoping review shows extreme variation in the association between cerebral NIRS signals and CBV, with few sources objectively documenting a true statistical association between the two. This review highlights the current critical knowledge gap and emphasizes the need for further research in the area.

Recent studies have highlighted the intricate relationship between cerebrospinal fluid (CSF) dynamics and global brain activity, suggesting a role in neurovascular coupling and brain waste clearance. The lateral ventricles are believed to play a key role in linking global BOLD (gBOLD) signals to CSF inflow (CSF in ) to the fourth ventricle. In this study, we developed a method to reliably quantify lateral ventricle volume (LVV) in fMRI data. Using three independent datasets, including resting-state and task-based fMRI, we assessed dynamic changes in LVV and their associations with gBOLD and CSF in . Our findings reveal a strong anti-correlation between LVV and gBOLD across all datasets, with an average gBOLD lag of approximately 1 s. The derivative of the LVV time series were positively correlated with CSF in , with CSF in lagging LVV changes by 1.4–2.4 s. A moderate negative correlation was also observed between CSF in and gBOLD, consistent with prior research. These results support the hypothesis that LVV fluctuations, driven by global cerebral blood volume oscillations, regulate CSF movement into and out of the fourth ventricle. Our findings provide a foundation for further investigations into the role of LVV dynamics in aging and neurological disorders.