Search

To increase granularity in human neuroimaging science, we designed and built a next-generation 7 Tesla magnetic resonance imaging scanner to reach ultra-high resolution by implementing several advances in hardware. To improve spatial encoding and increase the image signal-to-noise ratio, we developed a head-only asymmetric gradient coil (200 mT m-1, 900 T m-1s-1) with an additional third layer of windings. We integrated a 128-channel receiver system with 64- and 96-channel receiver coil arrays to boost signal in the cerebral cortex while reducing g-factor noise to enable higher accelerations. A 16-channel transmit system reduced power deposition and improved image uniformity. The scanner routinely performs functional imaging studies at 0.35-0.45 mm isotropic spatial resolution to reveal cortical layer functional activity, achieves high angular resolution in diffusion imaging and reduces acquisition time for both functional and structural imaging.

Brain arteriolosclerosis (B-ASC), characterized by pathologic arteriolar wall thickening, is a common finding at autopsy in aged persons and is associated with cognitive impairment. Hypertension and diabetes are widely recognized as risk factors for B-ASC. Recent research indicates other and more complex risk factors and pathogenetic mechanisms. Here, we describe aspects of the unique architecture of brain arterioles, histomorphologic features of B-ASC, relevant neuroimaging findings, epidemiology and association with aging, established genetic risk factors, and the co-occurrence of B-ASC with other neuropathologic conditions such as Alzheimer's disease and limbic-predominant age-related TDP-43 encephalopathy (LATE). There may also be complex physiologic interactions between metabolic syndrome (e.g., hypertension and inflammation) and brain arteriolar pathology. Although there is no universally applied diagnostic methodology, several classification schemes and neuroimaging techniques are used to diagnose and categorize cerebral small vessel disease pathologies that include B-ASC, microinfarcts, microbleeds, lacunar infarcts, and cerebral amyloid angiopathy (CAA). In clinical-pathologic studies that factored in comorbid diseases, B-ASC was independently associated with impairments of global cognition, episodic memory, working memory, and perceptual speed, and has been linked to autonomic dysfunction and motor symptoms including parkinsonism. We conclude by discussing critical knowledge gaps related to B-ASC and suggest that there are probably subcategories of B-ASC that differ in pathogenesis. Observed in over 80% of autopsied individuals beyond 80 years of age, B-ASC is a complex and under-studied contributor to neurologic disability.

Background and Purpose- Selection of patients with acute ischemic stroke for endovascular treatment generally relies on dynamic susceptibility contrast magnetic resonance imaging or computed tomography perfusion. Dynamic susceptibility contrast magnetic resonance imaging requires injection of contrast, whereas computed tomography perfusion requires high doses of ionizing radiation. The purpose of this work was to develop and evaluate a deep learning (DL)-based algorithm for assisting the selection of suitable patients with acute ischemic stroke for endovascular treatment based on 3-dimensional pseudo-continuous arterial spin labeling (pCASL). Methods- A total of 167 image sets of 3-dimensional pCASL data from 137 patients with acute ischemic stroke scanned on 1.5T and 3.0T Siemens MR systems were included for neural network training. The concurrently acquired dynamic susceptibility contrast magnetic resonance imaging was used to produce labels of hypoperfused brain regions, analyzed using commercial software. The DL and 6 machine learning (ML) algorithms were trained with 10-fold cross-validation. The eligibility for endovascular treatment was determined retrospectively based on the criteria of perfusion/diffusion mismatch in the DEFUSE 3 trial (Endovascular Therapy Following Imaging Evaluation for Ischemic Stroke). The trained DL algorithm was further applied on twelve 3-dimensional pCASL data sets acquired on 1.5T and 3T General Electric MR systems, without fine-tuning of parameters. Results- The DL algorithm can predict the dynamic susceptibility contrast-defined hypoperfusion region in pCASL with a voxel-wise area under the curve of 0.958, while the 6 ML algorithms ranged from 0.897 to 0.933. For retrospective determination for subject-level endovascular treatment eligibility, the DL algorithm achieved an accuracy of 92%, with a sensitivity of 0.89 and specificity of 0.95. When applied to the GE pCASL data, the DL algorithm achieved a voxel-wise area under the curve of 0.94 and a subject-level accuracy of 92% for endovascular treatment eligibility. Conclusions- pCASL perfusion magnetic resonance imaging in conjunction with the DL algorithm provides a promising approach for assisting decision-making for endovascular treatment in patients with acute ischemic stroke.

Purpose: Driven by the Lorentz force, acoustic noise may arguably be the next physiological challenge associated with ultra‐high field MRI scanners and powerful gradient coils. This work consisted of isolating and mitigating the main sound pathway in the NexGen 7 T scanner equipped with the investigational Impulse head gradient coil. Methods: Sound pressure level (SPL) measurements were performed with and without the RF coil to assess its acoustic impact. Vibration measurements were carried out on the gradient coil, the RF coil, and on the patient table to distinguish the different vibration mechanisms and pathways. Vibrations of the RF coil were modified by either making contact with the patient bore liner with padding material or by changing directly the RF shield with phosphor bronze mesh material. Results: SPL and vibration measurements demonstrated that eddy‐currents induced in the RF shield were the primary cause of acoustic noise. Replacing the conventional solid copper shield with phosphor bronze mesh material altered the vibrations of the RF shield and decreased SPL by 6 to 8 dB at the highest frequencies in EPI, depending on the gradient axis, while boosting the transmit B1+ field by 15%. Padding led to slightly less sound reduction on the X and Z gradient axes, but with minimal impact for the Y axis. Conclusion: This study demonstrates the potential importance of eddy‐current induced vibrations in the RF coil in terms of acoustic noise and opens new horizons for mitigation measures. [ABSTRACT FROM AUTHOR]

Purpose: To predict subject‐specific local specific absorption rate (SAR) distributions of the human head for parallel transmission (pTx) systems at 7 T. Theory and methods: Electromagnetic energy deposition in tissues is nonuniform at 7 T, and interference patterns due to individual channels of pTx systems may result in increased local SAR values, which can only be estimated with very high safety margins. We proposed, designed, and demonstrated a multichannel 3D convolutional neural network (CNN) architecture to predict local SAR maps as well as peak‐spatial SAR (ps‐SAR) levels. We hypothesized that utilizing a three‐channel 3D CNN, in which each channel is fed by a B1+$$ {B}_1^{+} $$ map, a phase‐reversed B1+$$ {B}_1^{+} $$ map, and an MR image, would improve prediction accuracies and decrease uncertainties in the predictions. We generated 10 new head–neck body models, along with 389 3D pTx MRI data having different RF shim settings, with their B1 and local SAR maps to support efforts in this field. Results: The proposed three‐channel 3D CNN predicted ps‐SAR10g levels with an average overestimation error of 20%, which was better than the virtual observation points–based estimation error (i.e., 152% average overestimation). The proposed method decreased prediction uncertainties over 20% (i.e., 22.5%–17.7%) compared to other methods. A safety factor of 1.20 would be enough to avoid underestimations for the dataset generated in this work. Conclusion: Multichannel 3D CNN networks can be promising in predicting local SAR values and perform predictions within a second, making them clinically useful as an alternative to virtual observation points–based methods. [ABSTRACT FROM AUTHOR]

Purpose: To optimize pseudo‐continuous arterial spin labeling (pCASL) for 7 T, and to further improve the labeling efficiency with parallel RF transmission transmit B1 (B1+) shimming. Methods: pCASL parameters were optimized based on B1+/B0 field distributions at 7 T with simulation. To increase labeling efficiency, the B1+ amplitude at inflowing arteries was increased with parallel RF transmission B1+ shimming. The "indv‐shim" with shimming weights calculated for each individual subject, and the "univ‐shim" with universal weights calculated on a group of 12 subjects, were compared with circular polarized (CP) shim. The optimized pCASL sequences with three B1+ shimming modes (indv‐shim, univ‐shim, and CP‐shim) were evaluated in 6 subjects who underwent two repeated scans 24 hours apart, along with a pulsed ASL sequence. Quantitative metrics including mean B1+ amplitude, perfusion, and intraclass correlation coefficient were calculated. The optimized 7T pCASL was compared with standard 3T pCASL on 5 subjects, using spatial SNR and temporal SNR. Results: The optimal pCASL parameter set (RF duration/gap = 300/250 us, Gave=0.6mT/m,gRatio=10) achieved robust perfusion measurement in the presence of B1+/B0 inhomogeneities. Both indv‐shim and univ‐shim significantly increased B1+ amplitude compared with CP‐shim in simulation and in vivo experiment (P <.01). Compared with CP‐shim, perfusion signal was increased by 9.5% with indv‐shim (P <.05) and by 5.3% with univ‐shim (P =.35). All three pCASL sequences achieved fair to good repeatability (intraclass correlation coefficient ≥ 0.5). Compared with 3T pCASL, the optimized 7T pCASL achieved 78.3% higher spatial SNR and 200% higher temporal SNR. Conclusion: The optimized pCASL achieved robust perfusion imaging at 7 T, while both indv‐shim and univ‐shim further increased labeling efficiency. [ABSTRACT FROM AUTHOR]

Purpose: Characterizing vessel territories can provide crucial information for evaluation of cerebrovascular disorders. In this study, we present a novel postprocessing pipeline for vascular territorial imaging of cerebral arteries based on a noncontrast enhanced time‐resolved 4D magnetic resonance angiography (MRA). Methods: Eight healthy participants, 1 Moyamoya patient, and 1 arteriovenous malformations patient were recruited. Territorial segmentation and relative blood flow rate calculations of cerebral arteries including left and right middle cerebral arteries and left and right posterior cerebral arteries were carried out based on the 4D MRA‐derived arterial arrival time maps of intracranial vessels. Results: Among healthy young subjects, the average relative blood flow rate values corresponding to left and right middle cerebral arteries and left and right posterior cerebral arteries were 35.9 ± 5.9%, 32.9 ± 7.5%, 15.4 ± 3.8%, and 15.9 ± 2.5%, respectively. Excellent agreement was observed between relative blood flow rate values obtained from the proposed 4D MRA‐based method and reference 2D phase contrast MRI. Abnormal cerebral circulations were visualized and quantified on both patients using the developed technique. Conclusion: The vascular territorial imaging technique developed in this study allowed for the generation of territorial maps with user‐defined level of details within a clinically feasible scan time, and as such may provide useful information to assess cerebral circulation balance in different pathologies. [ABSTRACT FROM AUTHOR]

Increased cerebroarterial pulsations are thought to be contributing factors in microvascular damage and cognitive impairment. In this study, we assessed the utility of two-dimensional (2D) phase-contrast MRI (PC-MRI) in quantifying cerebroarterial pulsations and evaluated the associations of pulsatile and non-pulsatile hemodynamic measures with cognitive performance and white matter hyperintensities (WMH). Neurocognitive assessments on 50 elderly subjects were performed using clinical dementia rating (CDR) and Montreal cognitive assessment (MoCA). An electrocardiogram-gated 2D PC-MRI sequence was used to calculate mean flow rate, pulsatility index (PI), and resistivity index (RI) of the internal carotid artery. For each subject, whole brain global cerebral blood flow (gCBF) and relative WMH volume were also quantified. Elevated RI was significantly associated with reduced cognitive performance quantified using MoCA (p = 0.04) and global CDR (p = 0.02). PI and RI were both significantly associated with relative WMH volume (p = 0.01, p < 0.01, respectively). However, non-pulsatile hemodynamic measures were not associated with cognitive impairment or relative WMH volume. This study showed that the cerebroarterial pulsatile measures obtained using PC-MRI have stronger association with the measures of cognitive impairment compared to global blood flow measurement and as such, might be useful as potential biomarkers of cerebrovascular dysfunction in preclinical populations. [ABSTRACT FROM AUTHOR]