Cerebrovascular activity is a major factor in the cerebrospinal fluid flow dynamics.

Cerebrospinal fluid (CSF) provides physical protection to the central nervous system as well as an essential homeostatic environment for the normal functioning of neurons. Additionally, it has been proposed that the pulsatile movement of CSF may assist in glymphatic clearance of brain metabolic waste products implicated in neurodegeneration. In awake humans, CSF flow dynamics are thought to be driven primarily by cerebral blood volume fluctuations resulting from a number of mechanisms, including a passive vascular response to blood pressure variations associated with cardiac and respiratory cycles. Recent research has shown that mechanisms that rely on the action of vascular smooth muscle cells ("cerebrovascular activity") such as neuronal activity, changes in intravascular CO2, and autonomic activation from the brainstem, may lead to CSF pulsations as well. Nevertheless, the relative contribution of these mechanisms to CSF flow remains unclear. To investigate this further, we developed an MRI approach capable of disentangling and quantifying CSF flow components of different time scales associated with these mechanisms. This approach was evaluated on human control subjects (n = 12) performing intermittent voluntary deep inspirations, by determining peak flow velocities and displaced volumes between these mechanisms in the fourth ventricle. We found that peak flow velocities were similar between the different mechanisms, while displaced volumes per cycle were about a magnitude larger for deep inspirations. CSF flow velocity peaked at around 10.4 s (range 7.1-14.8 s, n = 12) following deep inspiration, consistent with known cerebrovascular activation delays for this autonomic challenge. These findings point to an important role of cerebrovascular activity in the genesis of CSF pulsations. Other regulatory triggers for cerebral blood flow such as autonomic arousal and orthostatic challenges may create major CSF pulsatile movement as well. Future quantitative comparison of these and possibly additional types of CSF pulsations with the proposed approach may help clarify the conditions that affect CSF flow dynamics.

Autonomic arousals contribute to brain fluid pulsations during sleep.

During sleep, slow waves of neuro-electrical activity engulf the human brain and aid in the consolidation of memories. Recent research suggests that these slow waves may also promote brain health by facilitating the removal of metabolic waste, possibly by orchestrating the pulsatile flow of cerebrospinal fluid (CSF) through local neural control over vascular tone. To investigate the role of slow waves in the generation of CSF pulsations, we analyzed functional MRI data obtained across the full sleep-wake cycle and during a waking respiratory task. This revealed a novel generating mechanism that relies on the autonomic regulation of cerebral vascular tone without requiring slow electrocortical activity or even sleep. Therefore, the role of CSF pulsations in brain waste clearance may, in part, depend on proper autoregulatory control of cerebral blood flow.

Dependency of the blood oxygen level dependent-response to hyperoxic challenges on the order of gas administration in intracranial malignancies.

PURPOSE: Literature reports contradicting results on the response of brain tumors to vascular stimuli measured in T2*-weighted MRI. Here, we analyzed the potential dependency of the MRI-response to (hypercapnic) hyperoxia on the order of the gas administration. METHODS: T2* values were quantified at 3 Tesla in eight consenting patients at rest and during inhalation of hyperoxic/hypercapnic gas mixtures. Patients were randomly divided into two groups undergoing different gas administration protocols (group A: medical air-pure oxygen-carbogen; group B: medical air-carbogen-pure oxygen). Mann-Whitney U test and Wilcoxon signed rank test have been used to proof differences in T2* regarding respiratory challenge or different groups, respectively. RESULTS: T2* values at rest for gray and white matter were 50.3 ± 2.6 ms and 46.1 ± 2.0 ms, respectively, and slightly increased during challenge. In tumor areas, T2* at rest were: necrosis = 74.1 ± 10.1 ms; edema = 60.3 ± 17.6 ms; contrast-enhancing lesions = 48.6 ± 20.7 ms; and solid T2-hyperintense lesions = 45.0 ± 3.0 ms. Contrast-enhancing lesions strongly responded to oxygen (+ 20.7%) regardless on the gas protocol (p = 0.482). However, the response to carbogen significantly depended on the order of gas administration (group A, + 18.6%; group B, - 6.4%, p = 0.042). In edemas, a different trend between group was found when breathing oxygen (group A, - 9.9%; group B, + 19.5%, p = 0.057). CONCLUSION: Preliminary results show a dependency of the T2* response of contrast-enhancing brain tumor lesions on the order of the gas administration. The gas administration protocol is an important factor in the interpretation of the T2*-response in areas of abnormal vascular growth.

Contribution of systemic vascular effects to fMRI activity in white matter.

To investigate a potential contribution of systemic physiology to recently reported BOLD fMRI signals in white matter, we compared photo-plethysmography (PPG) and whole-brain fMRI signals recorded simultaneously during long resting-state scans from an overnight sleep study. We found that intermittent drops in the amplitude of the PPG signal exhibited strong and widespread correlations with the fMRI signal, both in white matter (WM) and in gray matter (GM). The WM signal pattern resembled that seen in previous resting-state fMRI studies and closely tracked the location of medullary veins. Its temporal cross-correlation with the PPG amplitude was bipolar, with an early negative value. In GM, the correlation was consistently positive. Consistent with previous studies comparing physiological signals with fMRI, these findings point to a systemic vascular contribution to WM fMRI signals. The PPG drops are interpreted as systemic vasoconstrictive events, possibly related to intermittent increases in sympathetic tone related to fluctuations in arousal state. The counter-intuitive polarity of the WM signal is explained by long blood transit times in the medullary vasculature of WM, which cause blood oxygenation loss and a substantial timing mismatch between blood volume and blood oxygenation effects. A similar mechanism may explain previous findings of negative WM signals around large draining veins during both task- and resting-state fMRI.

Intravoxel incoherent motion analysis of abdominal organs: computation of reference parameters in a large cohort of C57Bl/6 mice and correlation to microvessel density.

OBJECTIVE: Diffusion-weighted magnetic resonance imaging (DW-MRI) combined with intravoxel incoherent motion (IVIM) analysis may be applied for assessment of organ lesions, diffuse parenchymal pathologies, and therapy monitoring. The aim of this study was to determine IVIM reference parameters of abdominal organs for translational research in a large cohort of C57Bl/6 laboratory mice. MATERIALS AND METHODS: Anesthetized mice (n = 29) were measured in a 4.7 T small-animal MR scanner with a diffusion-weighted echo-planar imaging sequence at the [Formula: see text]-values 0, 13, 24, 55, 107, 260, 514, 767, 1020 s/mm(2). IVIM analysis was conducted on the liver, spleen, renal medulla and cortex, pancreas, and small bowel with computation of the true tissue diffusion coefficient [Formula: see text], the perfusion fraction [Formula: see text], and the pseudodiffusion coefficient [Formula: see text]. Microvessel density (MVD) was assessed by immunohistochemistry (IHC) against panendothelial cell antigen CD31. RESULTS: Mean values of the different organs [[Formula: see text] (10(-3) mm(2)/s); [Formula: see text] (%); [Formula: see text] (10(-3) mm(2)/s); MVD (MV/mm(2))]: liver 1.15 ± 0.14; 14.77 ± 6.15; 50.28 ± 33.21, 2008.48 ± 419.43, spleen 0.55 ± 0.12; 9.89 ± 5.69; 24.46 ± 17.31; n.d., renal medulla 1.50 ± 0.20; 14.63 ± 4.07; 35.50 ± 18.01; 1231.88 ± 290.61, renal cortex 1.34 ± 0.18; 10.83 ± 3.70; 16.74 ± 6.74; 810.09 ± 193.50, pancreas 1.23 ± 0.22; 20.12 ± 7.46; 29.35 ± 17.82, 591.15 ± 86.25 and small bowel 1.06 ± 0.13; 16.48 ± 3.63; 15.31 ± 7.00; 420.50 ± 168.42. Unlike [Formula: see text] and [Formula: see text], [Formula: see text] correlates significantly with MVD (r = 0.90, p = 0.037). CONCLUSION: This systematic evaluation of murine abdominal organs with IVIM and MVD analysis allowed to establish reference parameters for future DW-MRI translational research studies on small-animal disease models.

fMRI-based detection of alertness predicts behavioral response variability.

Levels of alertness are closely linked with human behavior and cognition. However, while functional magnetic resonance imaging (fMRI) allows for investigating whole-brain dynamics during behavior and task engagement, concurrent measures of alertness (such as EEG or pupillometry) are often unavailable. Here, we extract a continuous, time-resolved marker of alertness from fMRI data alone. We demonstrate that this fMRI alertness marker, calculated in a short pre-stimulus interval, captures trial-to-trial behavioral responses to incoming sensory stimuli. In addition, we find that the prediction of both EEG and behavioral responses during the task may be accomplished using only a small fraction of fMRI voxels. Furthermore, we observe that accounting for alertness appears to increase the statistical detection of task-activated brain areas. These findings have broad implications for augmenting a large body of existing datasets with information about ongoing arousal states, enriching fMRI studies of neural variability in health and disease.

Physiological changes in sleep that affect fMRI inference.

fMRI relies on a localized cerebral blood flow (CBF) response to changes in cortical neuronal activity. An underappreciated aspect however is its sensitivity to contributions from autonomic physiology that may affect CBF through changes in vascular resistance and blood pressure. As is reviewed here, this is crucial to consider in fMRI studies of sleep, given the close linkage between the regulation of arousal state and autonomic physiology. Typical methods for separating these effects are based on the use of reference signals that may include physiological parameters such as heart rate and respiration; however, the use of time-invariant models may not be adequate due to the possibly changing relationship between reference and fMRI signals with arousal state. In addition, recent research indicates that additional physiological reference signals may be needed to accurately describe changes in systemic physiology, including sympathetic indicators such as finger skin vascular tone and blood pressure.

All-night functional magnetic resonance imaging sleep studies.

BACKGROUND: Previous functional magnetic resonance imaging (fMRI) sleep studies have been hampered by the difficulty of obtaining extended amounts of sleep in the sleep-adverse environment of the scanner and often have resorted to manipulations such as sleep depriving subjects before scanning. These manipulations limit the generalizability of the results. NEW METHOD: The current study is a methodological validation of procedures aimed at obtaining all-night fMRI data in sleeping subjects with minimal exposure to experimentally induced sleep deprivation. Specifically, subjects slept in the scanner on two consecutive nights, allowing the first night to serve as an adaptation night. RESULTS/COMPARISON WITH EXISTING METHOD(S): Sleep scoring results from simultaneously acquired electroencephalography data on Night 2 indicate that subjects (n = 12) reached the full spectrum of sleep stages including slow-wave (M = 52.1 min, SD = 26.5 min) and rapid eye movement (REM, M = 45.2 min, SD = 27.9 min) sleep and exhibited a mean of 2.1 (SD = 1.1) nonREM-REM sleep cycles. CONCLUSIONS: It was found that by diligently applying fundamental principles and methodologies of sleep and neuroimaging science, performing all-night fMRI sleep studies is feasible. However, because the two nights of the study were performed consecutively, some sleep deprivation from Night 1 as a cause of the Night 2 results is likely, so consideration should be given to replicating the current study with a washout period. It is envisioned that other laboratories can adopt the core features of this protocol to obtain similar results.

Reduction of BOLD interference in pseudo-continuous arterial spin labeling: towards quantitative fMRI.

Fluctuations in blood-oxygenation level dependent (BOLD) signal and perfusion affect the quantification of changes in cerebral blood flow (CBF), coupled to neuronal activity, in arterial spin labeling (ASL). Subtraction methods for control and labeled MR images (i.e. pair-wise, surround subtraction, and subtraction of sinc-interpolated images), postulated to mitigate this interference in pseudo-continuous ASL (pCASL), were evaluated by comparison with quantitative 15O-water PET. At rest, a good agreement in the CBF values was found between PET and MRI for each of the subtraction methods. Stimulation of the visual system resulted in a regional CBF increase in the occipital lobe, which was detectable in both modalities. Bland-Altman analysis showed a systematic underestimation of the CBF values during activation in MRI. Evaluation of the relative CBF change induced by neuronal stimulation showed good inter-modality agreement for the three subtraction methods. Perfusion data obtained with each subtraction method followed the stimulation paradigm without significant differences in the correlation patterns or in the time lag between stimulation and perfusion response. Comparison to the gold standard confirmed the detectability of a neuronal stimulation pattern by pCASL. The results indicate that the combined use of background suppression and short TE reduces the BOLD-weighting in the pCASL signal.

Non-parametric intravoxel incoherent motion analysis in patients with intracranial lesions: Test-retest reliability and correlation with arterial spin labeling.

Intravoxel incoherent motion (IVIM) analysis of diffusion imaging data provides biomarkers of true passive water diffusion and perfusion properties. A new IVIM algorithm with variable adjustment of the b-value threshold separating diffusion and perfusion effects was applied for cerebral tissue characterization in healthy volunteers, computation of test-retest reliability, correlation with arterial spin labeling, and assessment of applicability in a small cohort of patients with malignant intracranial masses. The main results of this study are threefold: (i) accounting for regional differences in the separation of the perfusion and the diffusion components improves the reliability of the model parameters; (ii) if differences in the b-value threshold are not accounted for, a significant tissue-dependent systematic bias of the IVIM parameters occurs; (iii) accounting for voxel-wise differences in the b-value threshold improves the correlation with CBF measurements in healthy volunteers and patients. The proposed algorithm provides a robust characterization of regional micro-vascularization and cellularity without a priori assumptions on tissue diffusion properties. The glioblastoma multiforme with its inherently high variability of tumor vascularization and tumor cell density may benefit from a non-invasive clinical characterization of diffusion and perfusion properties.

In vivo quantification of cerebral r2*-response to graded hyperoxia at 3 tesla.

OBJECTIVES: This study aims to quantify the response of the transverse relaxation rate of the magnetic resonance (MR) signal of the cerebral tissue in healthy volunteers to the administration of air with step-wise increasing percentage of oxygen. MATERIALS AND METHODS: The transverse relaxation rate (R2*) of the MR signal was quantified in seven volunteers under respiratory intake of normobaric gas mixtures containing 21, 50, 75, and 100% oxygen, respectively. End-tidal breath composition, arterial blood saturation (SaO2), and heart pulse rate were monitored during the challenge. R2* maps were computed from multi-echo, gradient-echo magnetic resonance imaging (MRI) data, acquired at 3.0T. The average values in the segmented white matter (WM) and gray matter (GM) were tested by the analysis of variance (ANOVA), with Bonferroni post-hoc correction. The GM R2*-reactivity to hyperoxia was modeled using the Hill's equation. RESULTS: Graded hyperoxia resulted in a progressive and significant (P < 0.05) decrease of the R2* in GM. Under normoxia the GM-R2* was 17.2 ± 1.1 s(-1). At 75% O2 supply, the R2* had reached a saturation level, with 16.4 ± 0.7 s(-1) (P = 0.02), without a significant further decrease for 100% O2. The R2*-response of GM correlated positively with CO2 partial pressure (R = 0.69 ± 0.19) and negatively with SaO2 (R = -0.74 ± 0.17). The WM showed a similar progressive, but non-significant, decrease in the relaxation rates, with an increase in oxygen intake (P = 0.055). The Hill's model predicted a maximum R2* response of the GM, of 3.5%, with half the maximum at 68% oxygen concentration. CONCLUSIONS: The GM-R2* responds to hyperoxia in a concentration-dependent manner, suggesting that monitoring and modeling of the R2*-response may provide new oxygenation biomarkers for tumor therapy or assessment of cerebrovascular reactivity in patients.