A silent gradient axis for soundless spatial encoding to enable fast and quiet brain imaging

Purpose: A novel silent imaging method is proposed that combines a gradient insert oscillating at the inaudible frequency 20 kHz with slew rate-limited gradient waveforms to form a silent gradient axis that enable quiet and fast imaging. Methods: The gradient insert consisted of a plug-and-play (45 kg) single axis z-gradient, which operated as an additional fourth gradient axis. This insert was made resonant using capacitors and combined with an audio amplifier to allow for operation at 20 kHz. The gradient field was characterized using field measurements and the physiological effects of operating a gradient field at 20 kHz were explored using peripheral nerve stimulation experiments, tissue heating simulations and sound measurements. The imaging sequence consisted of a modified gradient-echo sequence which fills k-space in readout lanes with a width proportional to the oscillating gradient amplitude. The feasibility of the method was demonstrated in-vivo using 2D and 3D gradient echo (GRE) sequences which were reconstructed using a conjugate-gradient SENSE reconstruction. Results: Field measurements yielded a maximum gradient amplitude and slew rate of 40.8 mT/m and 5178T/m/s at 20 kHz. Physiological effects such as peripheral nerve stimulation and tissue heating were found not to be limiting at this amplitude and slew rate. For a 3D GRE sequence, a maximum sound level of 85 db(A) was measured during scanning. Imaging experiments using the silent gradient axis produced artifact free images while also featuring a 5.3-fold shorter scan time than a fully sampled acquisition. Conclusion: A silent gradient axis provides a novel pathway to fast and quiet brain imaging

A mechanistic computational framework to investigate the hemodynamic fingerprint of the blood oxygenation level-dependent signal

Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is one of the most used imaging techniques to map brain activity or to obtain clinical information about human cortical vasculature, in both healthy and disease conditions. Nevertheless, BOLD fMRI is an indirect measurement of brain functioning triggered by neurovascular coupling. The origin of the BOLD signal is quite complex, and the signal formation thus depends, among other factors, on the topology of the cortical vasculature and the associated hemodynamic changes. To understand the hemodynamic evolution of the BOLD signal response in humans, it is beneficial to have a computational framework available that virtually resembles the human cortical vasculature, and simulates hemodynamic changes and corresponding MRI signal changes via interactions of intrinsic biophysical and magnetic properties of the tissues. To this end, we have developed a mechanistic computational framework that simulates the hemodynamic fingerprint of the BOLD signal based on a statistically defined, three-dimensional, vascular model that approaches the human cortical vascular architecture. The microvasculature is approximated through a Voronoi tessellation method and the macrovasculature is adapted from two-photon microscopy mice data. Using this computational framework, we simulated hemodynamic changes—cerebral blood flow, cerebral blood volume, and blood oxygen saturation—induced by virtual arterial dilation. Then we computed local magnetic field disturbances generated by the vascular topology and the corresponding blood oxygen saturation changes. This mechanistic computational framework also considers the intrinsic biophysical and magnetic properties of nearby tissue, such as water diffusion and relaxation properties, resulting in a dynamic BOLD signal response. The proposed mechanistic computational framework provides an integrated biophysical model that can offer better insights regarding the spatial and temporal properties of the BOLD signal changes

A selection and targeting framework of cortical locations for line-scanning fMRI

Depth-resolved functional magnetic resonance imaging (fMRI) is an emerging field growing in popularity given the potential of separating signals from different computational processes in cerebral cortex. Conventional acquisition schemes suffer from low spatial and temporal resolutions. Line-scanning methods allow depth-resolved fMRI by sacrificing spatial coverage to sample blood oxygenated level-dependent (BOLD) responses at ultra-high temporal and spatial resolution. For neuroscience applications, it is critical to be able to place the line accurately to (1) sample the right neural population and (2) target that neural population with tailored stimuli or tasks. To this end, we devised a multi-session framework where a target cortical location is selected based on anatomical and functional properties. The line is then positioned according to this information in a separate second session, and we tailor the experiment to focus on the target location. Anatomically, the precision of the line placement was confirmed by projecting a nominal representation of the acquired line back onto the surface. Functional estimates of neural selectivities in the line, as quantified by a visual population-receptive field model, resembled the target selectivities well for most subjects. This functional precision was quantified in detail by estimating the distance between the visual field location of the targeted vertex and the location in visual cortex (V1) that most closely resembled the line-scanning estimates; this distance was on average ~5.5 mm. Given the dimensions of the line, differences in acquisition, session, and stimulus design, this validates that line-scanning can be used to probe local neural sensitivities across sessions. In summary, we present an accurate framework for line-scanning MRI; we believe such a framework is required to harness the full potential of line-scanning and maximize its utility. Furthermore, this approach bridges canonical fMRI experiments with electrophysiological experiments, which in turn allows novel avenues for studying human physiology non-invasively

A silent echo-planar spectroscopic imaging readout with high spectral bandwidth MRSI using an ultrasonic gradient axis

Purpose: We present a novel silent echo-planar spectroscopic imaging (EPSI) readout, which uses an ultrasonic gradient insert to accelerate MRSI while producing a high spectral bandwidth (20 kHz) and a low sound level. Methods: The ultrasonic gradient insert consisted of a single-axis (z-direction) plug-and-play gradient coil, powered by an audio amplifier, and produced 40 mT/m at 20 kHz. The silent EPSI readout was implemented in a phase-encoded MRSI acquisition. Here, the additional spatial encoding provided by this silent EPSI readout was used to reduce the number of phase-encoding steps. Spectroscopic acquisitions using phase-encoded MRSI, a conventional EPSI-readout, and the silent EPSI readout were performed on a phantom containing metabolites with resonance frequencies in the ppm range of brain metabolites (0–4 ppm). These acquisitions were used to determine sound levels, showcase the high spectral bandwidth of the silent EPSI readout, and determine the SNR efficiency and the scan efficiency. Results: The silent EPSI readout featured a 19-dB lower sound level than a conventional EPSI readout while featuring a high spectral bandwidth of 20 kHz without spectral ghosting artifacts. Compared with phase-encoded MRSI, the silent EPSI readout provided a 4.5-fold reduction in scan time. In addition, the scan efficiency of the silent EPSI readout was higher (82.5% vs. 51.5%) than the conventional EPSI readout. Conclusions: We have for the first time demonstrated a silent spectroscopic imaging readout with a high spectral bandwidth and low sound level. This sound reduction provided by the silent readout is expected to have applications in sound-sensitive patient groups, whereas the high spectral bandwidth could benefit ultrahigh-field MR systems

Hemodynamic and metabolic changes during hypercapnia with normoxia and hyperoxia using pCASL and TRUST MRI in healthy adults

Blood oxygenation level-dependent (BOLD) or arterial spin labeling (ASL) MRI with hypercapnic stimuli allow for measuring cerebrovascular reactivity (CVR). Hypercapnic stimuli are also employed in calibrated BOLD functional MRI for quantifying neuronally-evoked changes in cerebral oxygen metabolism (CMRO 2). It is often assumed that hypercapnic stimuli (with or without hyperoxia) are iso-metabolic; increasing arterial CO 2 or O 2 does not affect CMRO 2. We evaluated the null hypothesis that two common hypercapnic stimuli, 'CO 2 in air' and carbogen, are iso-metabolic. TRUST and ASL MRI were used to measure the cerebral venous oxygenation and cerebral blood flow (CBF), from which the oxygen extraction fraction (OEF) and CMRO 2 were calculated for room-air, 'CO 2 in air' and carbogen. As expected, CBF significantly increased (9.9% ± 9.3% and 12.1% ± 8.8% for 'CO 2 in air' and carbogen, respectively). CMRO 2 decreased for 'CO 2 in air' (-13.4% ± 13.0%, p < 0.01) compared to room-air, while the CMRO 2 during carbogen did not significantly change. Our findings indicate that 'CO 2 in air' is not iso-metabolic, while carbogen appears to elicit a mixed effect; the CMRO 2 reduction during hypercapnia is mitigated when including hyperoxia. These findings can be important for interpreting measurements using hypercapnic or hypercapnic-hyperoxic (carbogen) stimuli

CADASIL Affects Multiple Aspects of Cerebral Small Vessel Function on 7T-MRI

International audienceObjective: Cerebral small vessel diseases (cSVDs) are a major cause of stroke and dementia. We used cutting-edge 7T-MRI techniques in patients with Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL), to establish which aspects of cerebral small vessel function are affected by this monogenic form of cSVD. Methods: We recruited 23 CADASIL patients (age 51.1 AE 10.1 years, 52% women) and 13 age-and sex-matched controls (46.1 AE 12.6, 46% women). Small vessel function measures included: basal ganglia and centrum semiovale perforating artery blood flow velocity and pulsatility, vascular reactivity to a visual stimulus in the occipital cortex and reactivity to hypercapnia in the cortex, subcortical gray matter, white matter, and white matter hyperintensities. Results: Compared with controls, CADASIL patients showed lower blood flow velocity and higher pulsatility index within perforating arteries of the centrum semiovale (mean difference À 0.09 cm/s, p = 0.03 and 0.20, p = 0.009) and basal ganglia (mean difference À 0.98 cm/s, p = 0.003 and 0.17, p = 0.06). Small vessel reactivity to a short visual stimulus was decreased (blood-oxygen-level dependent [BOLD] mean difference À0.21%, p = 0.04) in patients, while reactivity to hypercapnia was preserved in the cortex, subcortical gray matter, and normal appearing white matter. Among patients, reactivity to hypercapnia was decreased in white matter hyperintensities compared to normal appearing white matter (BOLD mean difference À0.29%, p = 0.02). Interpretation: Multiple aspects of cerebral small vessel function on 7T-MRI were abnormal in CADASIL patients, indicative of increased arteriolar stiffness and regional abnormalities in reactivity, locally also in relation to white matter injury. These observations provide novel markers of cSVD for mechanistic and intervention studies

Zooming in on cerebral small vessel function in small vessel diseases with 7T MRI: Rationale and design of the “ZOOM@SVDs” study

Background: Cerebral small vessel diseases (SVDs) are a major cause of stroke and dementia. Yet, specific treatment strategies are lacking in part because of a limited understanding of the underlying disease processes. There is therefore an urgent need to study SVDs at their core, the small vessels themselves. Objective: This paper presents the rationale and design of the ZOOM@SVDs study, which aims to establish measures of cerebral small vessel dysfunction on 7T MRI as novel disease markers of SVDs. Methods: ZOOM@SVDs is a prospective observational cohort study with two years follow-up. ZOOM@SVDs recruits participants with Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL, N = 20), sporadic SVDs (N = 60), and healthy controls (N = 40). Participants undergo 7T brain MRI to assess different aspects of small vessel function including small vessel reactivity, cerebral perforating artery flow, and pulsatility. Extensive work-up at baseline and follow-up further includes clinical and neuropsychological assessment as well as 3T brain MRI to assess conventional SVD imaging markers. Measures of small vessel dysfunction are compared between patients and controls, and related to the severity of clinical and conventional MRI manifestations of SVDs. Discussion: ZOOM@SVDs will deliver novel markers of cerebral small vessel function in patients with monogenic and sporadic forms of SVDs, and establish their relation with disease burden and progression. These small vessel markers can support etiological studies in SVDs and may serve as surrogate outcome measures in future clinical trials to show target engagement of drugs directed at the small vessels

Assessment of aortic and cerebral haemodynamics and vascular brain injury with 3 and 7 T magnetic resonance imaging in patients with aortic coarctation

Aims: Coarctation of the aorta (CoA) is characterized by a central arteriopathy resulting in increased arterial stiffness. The condition is associated with an increased risk of stroke. We aimed to assess the aortic and cerebral haemodynamics and the presence of vascular brain injury in patients with previous surgical CoA repair. Methods and results: Twenty-seven patients with CoA (median age 22 years, range 12-72) and 25 age-and sex-matched controls (median age 24 years, range 12-64) underwent 3â T (heart, aorta, and brain) and 7â T (brain) magnetic resonance imaging scans. Haemodynamic parameters were measured using two-dimensional phase-contrast images of the ascending and descending aorta, internal carotid artery (ICA), basilar artery (BA), middle cerebral artery (MCA), and perforating arteries. Vascular brain injury was assessed by rating white matter hyperintensities, cortical microinfarcts, lacunes, and microbleeds. Pulse wave velocities in the aortic arch and descending aorta were increased and ascending aortic distensibility was decreased in patients with CoA vs. controls. Patients with CoA showed a higher mean flow velocity in the right ICA, left ICA, and BA and a reduced distensibility in the right ICA, BA, and left MCA. Haemodynamic parameters in the perforating arteries, total cerebral blood flow, intracranial volumes, and vascular brain injury were similar between the groups. Conclusion: Patients with CoA show an increased flow velocity and reduced distensibility in the aorta and proximal cerebral arteries, which suggests the presence of a generalized arteriopathy that extends into the cerebral arterial tree. No substantial vascular brain injury was observed in this relatively young CoA population, although the study was inadequately powered regarding this endpoint

Neuronal Models for EEG–fMRI Integration

Human brain activity can be measured in many ways, providing different views into its functions. Common measurements of human brain function, such as functional MRI (fMRI) and electroencephalography (EEG), are often integrated to get the best spatial and temporal resolution, but these measurements frequently show differences. This chapter therefore considers how the pooling of signals across populations of neurons affects these measurements. We consider a modeling framework in which fMRI and field potential signals integrate across transmembrane currents in a population of neurons, because synaptic activity is thought to be the largest drive of the fMRI signal and transmembrane potentials are the biggest source of field potentials. We formulate computations that provide simplified abstractions that inform how levels of synaptic activity or synchrony across neurons contribute to fMRI or electrophysiological signals and how to interpret deviations or similarities between measurements. The modeling framework and computations highlight that the level of activity in a neuronal population influences each measurement, but synchrony only has a large effect on field potentials and not on the fMRI signal. An application to data from human visual cortex explains why certain signals correlate and others do not. Advancing the fundamental understanding of how different measurements integrate neuronal activity will be important to combine fMRI and EEG measurements to better understand human brain function