Non-Newtonian and flow pulsatility effects in simulation models of a stented intracranial aneurysm

Permission to redistribute provided by publishers.Three models of different stent designs implanted in a cerebral aneurysm, originating from the Virtual Intracranial Stenting Challenge'07, are meshed and the flow characteristics simulated using commercial computational fluid dynamics (CFD) software in order to investigate the effects of non-Newtonian viscosity and pulsatile flow. Conventional mass inflow and wall shear stress (WSS) output are used as a means of comparing the cfd simulations. In addition, a WSS distribution is presented, which clearly discriminates in favour of the stent design identified by other groups. It is concluded that non-Newtonian and pulsatile effects are important to include in order to avoid underestimating wss, to understand dynamic flow effects, and to discriminate more effectively between stent designs. © Authors 2011

Investigating white matter hyperintensities in a multicenter COVID-19 study using 7T MRI

Background: Emerging evidence indicates that COVID-19 can negatively impact patient’s brain health (Douaud et al., 2022) (Cecchetti et al., 2022). Common clinical symptoms include brain fog, headaches, difficulty concentrating, and loss of sense of smell or taste. Some studies suggest that SARS-CoV-2 infection can damage the blood brain barrier either directly or through immune-inflammatory mechanisms (Zhang, et al. 2021). White matter hyperintensities (WMH) are imaging biomarkers of brain vascular or inflammatory injury. We investigated the association between severity of COVID-19 infection and burden of white matter hyperintensity volumes within a diverse multi-nation, multi-racial cohort using 7 Tesla (7T) MRI that can detect more subtle injury than conventional 1.5 or 3T MRI. Method: Participants were recruited at 4 sites: Pittsburgh, San Antonio and Houston, USA, and Nottingham, UK. To date, we have scanned and included the following participants in our analysis (Table 1). Detailed cognitive, neurological, mood and functional assessments and high-resolution MRI scans were collected. Subsequent WMH segmentation was performed using our in-house built deep learning based model (Figure 1). All segmentations were visually inspected and manually corrected before statistical analysis. Normalized WMH is calculated as a ratio of the WMH volume and the intracranial volume (WMH/ICV). Imaging data for an additional 36 age-matched controls were retrieved from the 7 Tesla Bioengineering Research Program (7TBRP) imaging bank at Pittsburgh. Result: Figure 1 shows the WMH segmentation outputs from our deep learning based model on images acquired at the 3 sites. Our Linear regression models along with our non-parametric Kruskal-Wallis test result suggests that compared to mild COVID cases and healthy control, COVID infected individuals that were ICU admitted show elevated WMH burden (Figure 2). Conclusion: Our results demonstrate that white matter hyperintensity volumes were higher among patients who had severe acute COVID infection that required ICU admission, compared to healthy age-matched controls. In contrast, no difference in white matter burden was observed in patients with mild COVID infection compared to healthy controls. Additional data (both cross-sectional and longitudinal), including more sensitive MRI measures is being collected to define the full spectrum of brain injury associated with sequelae of COVID infection

Lower locus coeruleus integrity in older COVID-19 survivors: initial findings from an international 7T MRI consortium

Background: The SARS-CoV-2 coronavirus has been associated with structural brain changes, consistent with its neurological manifestations. Recent studies showed a specific predilection for brainstem glial activation and hypometabolism, possibly indicating involvement of the locus coeruleus. The locus coeruleus (LC) modulates many cognitive functions and behaviors and its norepinephrine projections regulate both immune responses and vascular reactivity. We aimed to examine differences in LC integrity between COVID-19 survivors and controls. Method: Participants are enrolled across 3 US and 1 UK sites using harmonized cognitive and 7T MR-imaging protocols. Here, we analyzed data from 18 participants enrolled at Houston Methodist (12 COVID-19 survivors, 6 controls; Figure 1). COVID-19 survivors were required to have had a positive antigen test and an illness syndrome consistent with COVID-19. Healthy controls were required to have no significant pre-existing medical, neurologic, or psychiatric illness and no illness requiring hospitalization in the last 2 years. LC imaging was performed using a dedicated 7T MT-TFL sequence (0.4 x 0.4 x0.5mm). A site-specific normalized template was constructed using ANTs/FSL. The entire average LC integrity as well as voxel-wise integrity values were compared between COVID-19 survivors and controls using a robust linear regression (age-controlled and threshold free cluster enhancement corrected). LC integrity was correlated with age, sex, ethnicity and cognition using Spearman’s rank correlation. Result: Average LC integrity was not correlated with age, sex, or Hispanic ethnicity (p\u3e0.3). COVID-19 survivors did not differ from Controls when examining the entire LC (p=0.54). Voxel-wise analyses revealed a small cluster (19 voxels) in the middle portion of the left LC where COVID-19 survivors exhibited lower LC integrity than controls (p=0.005; Figure 2). Integrity of this cluster was not related to age or Hispanic ethnicity (p=0.9). LC integrity did not correlate with cognitive performance within the COVID-19 survivors (Trail Making Test B: p=0.43; Craft Story delayed recall p=0.47; MoCA p=0.84). Conclusion: Consistent with previous animal and human studies, our initial findings provide evidence for neuroinvasive potential of SARS-CoV-2 localized in the middle LC. In the future, we aim to expand our sample and link these observations to the neurocognitive sequelae of COVID-19

Preliminary neurocognitive finding from a multi-site study investing long-term neurological impact of COVID-19 using ultra-high field 7 Tesla MRI-based neuroimaging

Background: Globally, over six hundred million cases of SARS-CoV-2 have been confirmed. As the number of individuals in recovery rises, examining long-term neurological effects, including cognitive impairment and cerebral microstructural and microvascular changes, has become paramount., We present preliminary cognitive findings from an ongoing multi-site study investigating the long-term neurological impacts of COVID-19 using 7 Tesla MRI-based neuroimaging. Methods: Across 3 US and 1 UK sites, we identified adult (\u3e=18) COVID-19 survivors (CS) and healthy controls (HC) without significant pre-existing medical, neurological, or psychiatric illness. Using the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS-3) battery and Norms Calculator, 12 cognitive scores were adjusted for age, sex, and education and classified as either unimpaired or mild (\u3c9th percentile), moderate (\u3c2nd percentile), or severely impaired (\u3c1st percentile). The observed frequency of impairment across the two groups is reported along with proportional differences (PD) and confidence intervals (CI). Illness severity and time since infection were evaluated as potential associates of cognitive impairment. Results: Over a period of 11 months, we enrolled 108 participants. At the time of reporting, 80 (46.3% female; mean age: 60.3 ± 8.6; 61 CS, 19 HC) had completed cognitive assessments. Of the participants for whom we ascertained time since symptom onset and illness severity (n=51 and 43, respectively), 31.4% had their index COVID-19 infection within the past year, and 60.5% had a severe to critical infection (Table 1). Table 2 reports observed frequency of impairment for each metric. Aggregating all 12 cognitive metrics, we found 45 (73.8%) of CS had at least one impairment [vs HC: 10 (52.6%)]. A significantly greater proportion of CS had at least one moderate to severe or severe impairment (Figure 1). CS also had significantly higher frequencies of presenting with two or more mild to severe impairments [PD 0.33 (0.13, 0.54)]. Illness severity and time since infection were not significantly associated with cognitive impairment. Conclusion: Our preliminary results are consistent with potentially sustained COVID-associated cognitive impairment in a subset of participants. Enrollment in the multi-site cohort is ongoing, and updated results will be presented along with ultra-high field MRI-based neuroimaging correlates