Carotid plaque hemorrhage on magnetic resonance imaging strongly predicts recurrent ischemia and stroke

Objective There is a recognized need to improve selection of patients with carotid artery stenosis for carotid endarterectomy (CEA). We assessed the value of magnetic resonance imaging (MRI)-defined carotid plaque hemorrhage (MRIPH) to predict recurrent ipsilateral cerebral ischemic events, and stroke in symptomatic carotid stenosis. Methods One hundred seventy-nine symptomatic patients with ≥50% stenosis were prospectively recruited, underwent carotid MRI, and were clinically followed up until CEA, death, or ischemic event. MRIPH was diagnosed if the plaque signal intensity was >150% that of the adjacent muscle. Event-free survival analysis was done using Kaplan–Meier plots and Cox regression models controlling for known vascular risk factors. We also undertook a meta-analysis of reported data on MRIPH and recurrent events. Results One hundred fourteen patients (63.7%) showed MRIPH, suffering 92% (57 of 62) of all recurrent ipsilateral events and all but 1 (25 of 26) future strokes. Patients without MRIPH had an estimated annual absolute stroke risk of only 0.6%. Cox multivariate regression analysis proved MRIPH as a strong predictor of recurrent ischemic events (hazard ratio [HR] = 12.0, 95% confidence interval [CI] = 4.8–30.1, p < 0.001) and stroke alone (HR = 35.0, 95% CI = 4.7–261.6, p = 0.001). Meta-analysis of published data confirmed this association between MRIPH and recurrent cerebral ischemic events in symptomatic carotid artery stenosis (odds ratio = 12.2, 95% CI = 5.5–27.1, p < 0.00001). Interpretation MRIPH independently and strongly predicts recurrent ipsilateral ischemic events, and stroke alone, in symptomatic ≥50% carotid artery stenosis. The very low stroke risk in patients without MRIPH puts into question current risk–benefit assessment for CEA in this subgroup

Magnetic resonance imaging plaque hemorrhage for risk stratification in carotid artery disease with moderate risk under current medical therapy

Background and Purpose—Magnetic resonance imaging (MRI)–defined carotid plaque hemorrhage (MRIPH) can predict recurrent cerebrovascular ischemic events in severe symptomatic carotid stenosis. It is less clear whether MRIPH can improve risk stratification despite optimized medical secondary prevention in those with moderate risk. Methods—One-hundred fifty-one symptomatic patients with 30% to 99% carotid artery stenosis (median age: 77, 60.5% men) clinically deemed to not benefit from endarterectomy were prospectively recruited to undergo MRI and clinical follow-up (mean, 22 months). The clinical carotid artery risk score could be evaluated in 88 patients. MRIPH+ve was defined as plaque intensity >150% that of adjacent muscle. Survival analyses were performed with recurrent infarction (stroke or diffusion-positive cerebral ischemia) as the main end point. Results—Fifty-five participants showed MRIPH+ve; 47 had low, 36 intermediate, and 5 high carotid artery risk scores. Cox regression showed MRIPH as a strong predictor of future infarction (hazard ratio, 5.2; 95% confidence interval, 1.64–16.34; P=0.005, corrected for degree of stenosis), also in the subgroup with 50% to 69% stenosis (hazard ratio, 4.1; 95% confidence interval, 1–16.8; P=0.049). The absolute risk of future infarction was 31.7% at 3 years in MRIPH+ve versus 1.8% in patients without (P<0.002). MRIPH increased cumulative risk difference of future infarction by 47.1% at 3 years in those with intermediate carotid artery risk score (P=0.004). Conclusions—The study confirms MRIPH to be a powerful risk marker in symptomatic carotid stenosis with added value over current risk scores. For patients undergoing current secondary prevention medication with clinically uncertain benefit from recanalization, that is, those with moderate degree stenosis and intermediate carotid artery risk scores, MRIPH offers additional risk stratification

A comparative study of GNN and MLP based machine learning for the diagnosis of Alzheimer’s Disease involving data synthesis

Alzheimer’s Disease (AD) is a neurodegenerative disease that commonly occurs in older people. It is characterized by both cognitive and functional impairment. However, as AD has an unclear pathological cause, it can be hard to diagnose with confidence. This is even more so in the early stage of Mild Cognitive Impairment (MCI). This paper proposes a U-Net based Generative Adversarial Network (GAN) to synthesize fluorodeoxyglucose -positron emission tomography (FDG-PET) from magnetic resonance imaging - T1 weighted imaging (MRI-T1WI) for further usage in AD diagnosis including its early-stage MCI. The experiments have displayed promising results with Structural Similarity Index Measure (SSIM) reaching 0.9714. Furthermore, three types of classifiers are developed, i.e., one Multi-Layer Perceptron (MLP) based classifier, two Graph Neural Network (GNN) based classifiers where one is for graph classification and the other is for node classification. 10-fold cross-validation has been conducted on all trials of experiments for classifier comparison. The performance of these three types of classifiers has been compared with the different input modalities setting and data fusion strategies. The results have shown that GNN based node classifier surpasses the other two types of classifiers, and has achieved the state-of-the-art (SOTA) performance with the best accuracy at 90.18% for 3-class classification, namely AD, MCI and normal control (NC) with the synthesized fluorodeoxyglucose - positron emission tomography (FDG-PET) features fused at the input level. Moreover, involving synthesized FDG-PET as part of the input with proper data fusion strategies has also proved to enhance all three types of classifiers’ performance. This work provides support for the notion that machine learning-derived image analysis may be a useful approach to improving the diagnosis of AD

Lesion topography and microscopic white matter tract damage contribute to cognitive impairment in symptomatic carotid artery disease

Purpose: To investigate associations between neuroimaging markers of cerebrovascular disease, including lesion topography and extent and severity of strategic and global cerebral tissue injury, and cognition in carotid artery disease (CAD). Materials and Methods: All participants gave written informed consent to undergo brain magnetic resonance imaging and the Addenbrooke’s Cognitive Examination–Revised. One hundred eight patients with symptomatic CAD but no dementia were included, and a score less than 82 represented cognitive impairment. Group comparison and interrelations between global cognitive and fluency performance, lesion topography, and ultrastructural damage were assessed with voxel-based statistics. Associations between cognition, medial temporal lobe atrophy (MTA), lesion volumes, and global white matter ultrastructural damage indexed as increased mean diffusivity were tested with regression analysis by controlling for age. Diagnostic accuracy of imaging markers selected from a multivariate prediction model was tested with receiver operating characteristic analysis. Results: Cognitively impaired patients (n = 53 [49.1%], classified as having probable vascular cognitive disorder) were older than nonimpaired patients (P = .027) and had more frequent MTA (P<.001), more cortical infarctions (P = .016), and larger volumes of acute (P = .028) and chronic (P = .009) subcortical ischemic lesions. Lesion volumes did not correlate with global cognitive performance (lacunar infarctions, P = .060; acute lesions, P = .088; chronic subcortical ischemic lesions, P = .085). In contrast, cognitive performance correlated with presence of chronic ischemic lesions within the interhemispheric tracts and thalamic radiation (P< .05, false discovery rate corrected). Skeleton mean diffusivity showed the closest correlation with cognition (R2 = 0.311, P< .001) and promising diagnostic accuracy for vascular cognitive disorder (area under the curve, 0.82 [95% confidence interval: 0.75, 0.90]). Findings were confirmed in subjects with a low risk of preclinical Alzheimer disease indexed by the absence of MTA (n = 85). Conclusion: Subcortical white matter ischemic lesion locations and severity of ultrastructural tract damage contribute to cognitive impairment in symptomatic CAD, which suggests that subcortical disconnection within large-scale cognitive neural networks is a key mechanism of vascular cognitive disorder

Large‐scale network dysfunction in vascular cognitive disorder supports connectional diaschisis in advanced arteriosclerosis

Background and PurposeThe interrelation of cognitive performance, cerebrovascular damage and brain functional connectivity (FC) in advanced arteriosclerosis remains unclear. Our aim was to investigate the associations between FC, white matter damage and cognitive impairment in carotid artery disease.MethodsSeventy‐one participants with recent cerebrovascular event and with written informed consent underwent resting‐state functional MRI (fMRI) and the Addenbrooke's Cognitive Examination‐Revised (ACE‐R). Network and inter‐hemispheric FC metrics were compared between cognitively normal and impaired subjects, and interrelated with cognition. In order to explore the nature of FC changes, we investigated their associations with microstructural damage of related white matter tracts and cognitive performance, followed by mediation analysis.ResultsParticipants with global cognitive impairment showed reduced FC compared to the cognitively intact subjects within the central executive network (CEN), and between hemispheres. Patients with executive dysfunction had decreased CEN FC while patients with memory loss demonstrated low FC in both CEN and default mode network (DMN). Global performance correlated with connectivity metrics of the CEN hub with DMN nodes, and between hemispheres. Cingulum mean diffusivity (MD) was negatively correlated with the ACE‐R and CEN‐DMN FC. The cingulum MD‐cognition association was partially mediated by CEN DMN FC.ConclusionsLong‐range functional disconnection of CEN with DMN nodes is the main feature of cognitive impairment in elderly subjects with symptomatic carotid artery disease. Our findings provide further support for the connectional diaschisis concept of vascular cognitive disorder (VCD), and highlight a mediation role of functional disconnection to explain associations between microstructural white matter tract damage and cognitive impairment

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

The chronic neuropsychiatric sequelae of COVID?19: The need for a prospective study of viral impact on brain functioning

IntroductionThe increasing evidence of SARS‐CoV‐2 impact on the central nervous system (CNS) raises key questions on its impact for risk of later life cognitive decline, Alzheimer's disease (AD), and other dementia.MethodsThe Alzheimer's Association and representatives from more than 30 countries—with technical guidance from the World Health Organization—have formed an international consortium to study the short‐and long‐term consequences of SARS‐CoV‐2 on the CNS—including the underlying biology that may contribute to AD and other dementias. This consortium will link teams from around the world covering more than 22 million COVID‐19 cases to enroll two groups of individuals including people with disease, to be evaluated for follow‐up evaluations at 6, 9, and 18 months, and people who are already enrolled in existing international research studies to add additional measures and markers of their underlying biology.ConclusionsThe increasing evidence and understanding of SARS‐CoV‐2's impact on the CNS raises key questions on the impact for risk of later life cognitive decline, AD, and other dementia. This program of studies aims to better understand the long‐term consequences that may impact the brain, cognition, and functioning—including the underlying biology that may contribute to AD and other dementias

Altered hippocampal functional connectivity patterns in patients with cognitive impairments following ischaemic stroke: a resting-state fMRI study

Background Ischemic stroke with cognitive impairment is a considerable risk factor for developing dementia. Identifying imaging markers of cognitive impairment following ischemic stroke will help to develop prevention strategies against post-stroke dementia.Methods Here, we investigated the hippocampal functional connectivity (FC) pattern following ischemic stroke, using resting-state fMRI (rs-fMRI). Thirty-three cognitively impaired patients after ischemic stroke and sixteen age-matched controls with no known history of neurological disorder, were recruited for the study. Importantly, no patient had a direct ischaemic insult to hippocampus on examination of brain imaging. Seven subfields of hippocampus were used as a seed region for FC analyses.Results Across all hippocampal subfields, FC with the inferior parietal lobe in patients was reduced as compared with healthy controls. This decreased FC included both supramarginal gyrus and angular gyrus. The FC of hippocampal subfields with cerebellum was increased. Importantly, the degree of the altered FC between hippocampal subfields and IPL was associated with their impaired memory function.Conclusion Our results demonstrated that decreased hippocampal-IPL connectivity was associated with cognitive impairment in patients with ischemic stroke. These findings provide novel insights into the role of hippocampus in cognitive impairment following ischemic stroke

Frequency and clinical patterns of stroke in Iran - Systematic and critical review

<p>Abstract</p> <p>Background</p> <p>Cerebrovascular disease is the second commonest cause of death, and over a third of stroke deaths occur in developing countries. To fulfil the current gap on data, this systematic review is focused on the frequency of stroke, risk factors, stroke types and mortality in Iran.</p> <p>Methods</p> <p>Thirteen relevant articles were identified by keyword searching of PubMed, Iranmedex, Iranian University index Libraries and the official national data on burden of diseases.</p> <p>Results</p> <p>The publication dates ranged from 1990 to 2008. The annual stroke incidence of various ages ranged from 23 to 103 per 100,000 population. This is comparable to the figures from Arab Countries, higher than sub-Saharan Africa, but lower than developed countries, India, the Caribbean, Latin America, and China. Similarly to other countries, ischaemic stroke was the commonest subtype. Likewise, the most common related risk factor is hypertension in adults, but cardiac causes in young stroke. The 28-day case fatality rate is reported at 19-31%.</p> <p>Conclusions</p> <p>Data on the epidemiology of stroke, its pattern and risk factors from Iran is scarce, but the available data highlights relatively low incidence of stroke. This may reflect a similarity towards the neighbouring nations, and a contrast with the West.</p

Intravenous immunoglobulin and rituximab versus placebo treatment of antibody-associated psychosis: study protocol of a randomised phase IIa double-blinded placebo-controlled trial (SINAPPS2)

Abstract: Background: Evidence is conflicting about a causal role of inflammation in psychosis and, specifically, regarding antibodies binding to neuronal membrane targets, especially N-methyl-D-aspartate receptors. NMDAR, LGI1 and GABA-A antibodies were found more prevalent in people with psychosis than in healthy controls. We aim to test whether these antibodies are pathogenic and may cause isolated psychosis. The SINAPPS2 phase IIa double-blinded randomised controlled trial will test the efficacy and safety of immunoglobulin and rituximab treatment versus placebo for patients with acute psychosis symptoms as added to psychiatric standard of care. Methods: We will screen approximately 2500 adult patients with acute psychosis to identify 160 with antibody-positive psychosis without co-existing neurological disease and recruit about 80 eligible participants to the trial in the period from September 2017 to September 2021 across the UK. Eligible patients will be randomised 1:1 either to intravenous immunoglobulin (IVIG) followed by rituximab or to placebo infusions of 1% albumin followed by 0.9% sodium chloride, respectively. To detect a time-to-symptomatic-recovery hazard ratio of 0.322 with a power of 80%, 56 participants are needed to complete the trial, allowing for up to 12 participants to drop out of each group. Eligible patients will be randomised and assessed at baseline within 4 weeks of their eligibility confirmation. The treatment will start with IVIG or 1% albumin placebo infusions over 2–4 consecutive days no later than 7 days from baseline. It will continue 4–5 weeks later with a rituximab or sodium chloride placebo infusion and will end 2–3 weeks after this with another rituximab or placebo infusion. The primary outcome is the time to symptomatic recovery defined as symptomatic remission sustained for at least 6 months on the following Positive and Negative Syndrome Scale items: P1, P2, P3, N1, N4, N6, G5 and G9. Participants will be followed for 12 months from the first day of treatment or, where sustained remission begins after the first 6 months, for an additional minimum of 6 months to assess later response. Discussion: The SINAPPS2 trial aims to test whether immunotherapy is efficacious and safe in psychosis associated with anti-neuronal membrane antibodies. Trial registration: ISRCTN, 11177045. Registered on 2 May 2017. EudraCT, 2016-000118-31. Registered on 22 November 2016. ClinicalTrials.gov, NCT03194815. Registered on 21 June 2017