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Background: Atherosclerotic carotid artery disease is associated with a high risk of major adverse cardiac events (MACE) even with optimal risk factor management and surgical interventions such as carotid endarterectomy (CEA). Aortic stenosis (AS) is an age-related valve disease that is associated with a high rate of MACE. An artificial intelligence-based AS estimation algorithm (AI-AS) can identify AS with high accuracy using electrocardiogram. This study evaluates the prognostic value of AI-AS in patients with carotid artery disease undergoing CEA. Methods: We included patients with carotid artery disease undergoing CEA at Mayo Clinic from 2002-2023 if they had >30 days of follow-up and an electrocardiogram within one year before CEA. The electrocardiogram closest to the CEA date was used to calculate AI-AS (AS probability ranging from 0-1). MACE was defined as the composite of cardiac events, ischemic cerebrovascular accidents, and all-cause mortality during follow-up after CEA. A receiver operating characteristic curve and the Youden index were used to identify the optimal AI-AS cut-off value for predicting MACE. Kaplan Meier plot was used to depict MACE-free survival. Regression models were used to evaluate the predictive value of AI-AS for future MACE adjusting for clinical covariates. Results: A total of 665 patients with a median age of 72 [IQR:66, 78] years and 438 (65.9%) males were included. Over a median follow-up time of 7.1 [IQR:2.7, 11.5] years, MACE occurred in 419 (63%) of the patients, including 187 (44.6%) mortality, 161 (38.4%) cardiac events, and 71 (16.9%) cerebrovascular accidents. Median AI-AS was 0.32 [IQR:0.09, 0.55] in the total cohort, 0.34 [IQR:0.12, 0.56] in patients with MACE, and 0.30 [IQR:0.07, 0.53] in patients without MACE (P=0.038). AI-AS was a significant predictor of MACE (HR:2.38, 95%CI:1.64-3.46, P<0.001) in univariate Cox regression analysis. The optimal cut-off value of AI-AS for MACE was 0.419 (area under the curve: 0.55). Patients with high AI-AS (≥0.419) had a significantly lower MACE-free survival in the Log-rank test ( Figure 1 ) and in the multivariable Cox regression model adjusted for covariates compared to low AI-AS (<0.419) patients ( Table 1 ). Conclusion: AI-AS is an independent predictor of MACE in patients with carotid artery disease after CEA and can be used as a risk-stratifying tool in this patient population. Additional studies are needed to elucidate the mechanistic link between AS and MACE in these patients.

Background: Systolic blood pressure (SBP) fluctuation is linked to increased death or disability in intracerebral hemorrhage (ICH) patients. We analyzed data from the Antihypertensive Treatment of Acute Cerebral Hemorrhage (ATACH)-2 trial to explore whether the association between SBP fluctuation and 90-day outcomes varies with time from randomization. Methods: We calculated hourly SBP fluctuation based on the difference between maximum and minimum SBP during the first 24 hours post-randomization. Logistic regression models assessed the impact of SBP fluctuation on: 1) death or disability (modified Rankin scale [mRS] 4-6 at 90 days); 2) hematoma expansion (>33% increase in volume on 24-hour CT scan); 3) neurological deterioration within 24 hours (defined as ≥2-point decrease on Glasgow Coma Scale or ≥4-point increase on NIH Stroke Scale); and 4) acute kidney injury (AKI) within 72 hours. Adjustments were made for baseline Glasgow Coma Scale score, intraventricular hemorrhage, hematoma volume, and maximum SBP. Results: The hourly SBP fluctuations according to 90-day outcomes (dichotomized into good outcome, mRS 0-3, and poor outcome, mRS 4-6) in 961 patients with ICH are presented in Figure. The SBP fluctuation at 5 hours (p=0.014) and 6 hours (p=0.014) post randomization were significantly associated with death or disability at 90 days, with positive, but not statistically significant associations observed at all other points up to 13 hours after randomization. Risk of neurological deterioration within 24 hours was highly associated with SBP fluctuation, with the largest association observed between 1 (p<0.001) and 5 (p<0.001) hours following randomization, with significant associations observed up to 22 hours following randomization. Risk of hematoma expansion was associated with SBP fluctuation between 3 (p=0.015) and 8 (p=0.002) hours post randomization. Statistically significant associations between SPB fluctuations and risk of AKI were not observed. Conclusions: The first 8 hours following randomization are critical for reducing SBP fluctuations, as this period most strongly influences both short- and long-term outcomes in ICH patients. These findings suggest this time window is crucial for future interventions aimed at controlling SBP in ICH patients.

Background: Previous research has suggested pericarotid fat density to be significantly linked to atherosclerotic plaque components and cerebrovascular events. Inflammatory markers within the plaques are critical in the pathogenesis and progression of carotid artery disease. However, the association between pericarotid fat and inflammatory processes within atherosclerotic plaques remains underexplored. This study hypothesizes that pericarotid fat density is directly associated with the levels of inflammatory markers within atherosclerotic plaques. Methods: Carotid plaques were prospectively collected from patients with carotid artery disease undergoing carotid endarterectomy (CEA). The levels of inflammatory plaque cytokines (MCP-1, IL-8, IFN-γ, IL-10, IL-1β, IL-6, PDGF-AA, PDGF-AB/BB, TNF-α, VEGF) were measured in tissue homogenates using a customized 10-plex Luminex assay. Baseline demographics and clinical data of our population were extracted from electronic health records. We analyzed preoperative neck computed tomography angiography (CTA) images placing regions-of-interest (ROI) in the pericarotid fat on the slice showing maximal stenosis. For each patient, we calculated the average of Hounsfield Units (HU) within the ROI. Spearman correlation test was used to assess the correlation between variables. Results: Among the 43 patients included, the median age was 73 (67, 78) years, and 33 (76.7%) patients were male. Plaque levels of PDGF-AA and VEGF showed significant positive correlations with HU (r=0.330, p=0.030; r=0.380, p=0.011, respectively), as illustrated in Figure 1 . Although plaque levels of IFN-γ demonstrated a significant negative correlation with HU (r=-0.390, p=0.010), the most cases exhibited values close to zero. Conclusions: The assessment of pericarotid fat density on CTA may allow for the estimation of plaque inflammation, suggesting that more fat density is associated with increased inflammatory activity within atherosclerotic plaques.

Introduction: Cerebral Amyloid Angiopathy (CAA) is caused by the progressive deposition of β-amyloid in the walls of small to medium-sized cerebral vessels. Although seizures represent a debilitating manifestation of CAA, little is known about their prevalence or associated factors. We aim to fill this gap by determining the prevalence of seizures in CAA and identify factors associated with an increased risk of seizures. Methods: We identified consecutive patients with CAA, evaluated within the Mayo Clinic health system between January 2010 and December 2023 using the ICD-10 code. Data on demographics and comorbidities were compared between those with and without seizures using the chi-square test for categorical variables and independent samples t-test for continuous variables. Odds ratios (OR) were estimated after adjusting for age, sex, and race in multivariable logistic regression. Results: We included 1,914 patients with CAA with a mean age of 75.4 ± 8.6 years, of whom 52.3% were female and 87.5% were white. Seizures were observed in 347 patients (18.1%). Individuals with seizures were significantly younger (mean age 67.7 ± 9.1 vs. 77.2 ± 7.5 years, p < 0.001). Multivariable modeling identified alcohol abuse (OR 1.92, 95% CI 1.03-3.56, p=0.04), diabetes mellitus (OR 2.14, 95% CI 1.13-4.06, p=0.02), hypertension (OR 1.79, 95% CI 1.33 - 2.41, p= <0.001), liver disease (OR 1.75, 95% CI 1.14-2.69, p=0.01), and ischemic stroke (OR 1.33, 95% CI 1.01-1.74, p=0.04) as independently associated with an increased risk of seizures. Conclusion: We found that seizures affect nearly one in five patients with CAA. Also, comorbidities such as alcohol abuse, diabetes mellitus, hypertension, liver disease, and ischemic stroke were found to be significantly associated with an increased risk of seizures. Longitudinal studies are warranted to confirm these risk factors, some of which may be modifiable.

Background: Identifying optimal candidates for endovascular treatment (EVT) remains an ongoing priority to maximize treatment efficacy. The recent large core trials have called into question the use of infarct volume alone for selecting patients. This study aimed at exploring the feasibility of using routinely acquired Computed Tomography Perfusion (CTP) to capture how lesion location impacts brain connectivity and how this in turn affects the ability to benefit from EVT. Methods: Consecutive patients from a multi-centric stroke imaging registry were included in this study if they had a proven anterior circulation large vessel occlusion (LVO) and available baseline CTP data. Hypoperfusion (Tmax >6 seconds) and ischemic core (relative cerebral blood flow <30%) maps were automatically generated using e-CTP (Brainomix, UK) and used to derive disconnection maps via a DTI template. A voxel-based, multivariate method (Sparse Canonical-Correlation-Analysis – LESYMAPS) was used to explore associations between disconnection maps and NIHSS subitems in recanalized patients. The mismatch between Tmax and core disconnection volumes (disconnection mismatch volume) (Figure 1) was used to predict modified Rankin Scale (mRS) at 3-months using an ordinal shift regression adjusted for age, recanalization status and infarct volume. Results: One-hundred and seventy-one patients were included. The median NIHSS was 16 (11.5 to 22). The total NIHSS was associated with disconnection predominantly within the left basal ganglia, brainstem and corpus callosum. Upper and lower limb deficits (NIHSS 5a, 5b, 6a, 6b) were associated with corticospinal tract disconnection, with negative correlations within the contralateral tracts (Figure 2). Language deficits were associated with left hemisphere tract disconnection, also showing negative correlations within the contralateral tracts. The disconnection mismatch volume was an independent predictor of functional outcome at 3-months (Table 1). Conclusion: The results from this study showed that it is possible to use routinely acquired CTP to capture the effects of stroke lesion on brain connectivity and its impact on functional outcome following recanalization treatment. Such an approach could enable more nuanced treatment selection for patients based on specific neurological deficits.

Introduction and Hypothesis: New bleeding in cerebral cavernous malformations (CCM) heralds increased risk of future hemorrhage for several years, yet conventional imaging only detects new bleeding that occurred in the prior weeks. A biomarker of hemorrhage could help identifying high risk lesions. An increase of mean lesional quantitative susceptibility mapping (QSM) ≥6% on MRI has been adjudicated as reflecting new bleeding in CCM during longitudinal follow-up. However, mean lesional QSM from a single acquisition could not diagnose or prognosticate a bleed. We hypothesize that machine learning (ML) may identify diagnostic and prognostic features of bleeding within QSM maps at a single point in time. Material and Methods: Two hundred and sixty-five QSM maps of CCM lesions were acquired in 120 patients enrolled in National Institute of Health (NIH) multisite trial readiness project (NCT03652181). Each map was classified (Yes/No) in association with symptomatic hemorrhage (SH) and/or biomarker event with QSM increase ≥6% in the prior (diagnostic association) and subsequent (prognostic association) year. Twenty-eight features were extracted including 14 texture, 5 first-order statistical, as well as 3 size, shape, and morphological. Five-fold cross-validation was conducted on a support-vector machine (SVM) with linear stepwise kernel for both diagnostic and prognostic associations. Performance of individual features and composite classifiers was evaluated using student t-test ( p <0.05) with Bonferroni-correction and receiver operating characteristic (ROC) analysis, area under the curve (AUC). Results: Lesions with SH in the prior year had lower average values for sum variance (AUC=0.79, p<0.001), variance (AUC=0.79, p<0.001), and correlation (AUC=0.71, p=0.004) as compared to lesions without SH. The SVM classification method tasked with distinguishing lesions with mean QSM increase ≥6% in the prior year included recurrent selection of sum average, mean, sphericity and margin sharpness, yielding an AUC of 0.61 (p=0.02). In the prognostic cohort, no individual feature nor any SVM classification model was able to distinguish cases with a subsequent clinical bleed or biomarker event. Conclusion: This proof-of-concept suggests that ML may assist in deriving features on QSM maps acquired at a single timepoint, which reflect prior hemorrhagic activity in CCM. Further investigation is planned in larger cohorts and in conjunction with clinical trials of bleeding in CCM.

Background: Retinal vasculopathy had been reported across the continuum of neurodegeneration. Retinal color fundus photography coupled with automated retinal vascular analysis offers potential to non-invazively screen for Alzheimer’s disease (AD) neurodegeneration. Amyloid positron emission tomography (PET) and apolipoprotein 4 (APOE4) carrier status are known biomarkers of AD risk. Herein, we examined the relationship between retinal vascular fractal dimensions in non-mydriatic color fundus photographs, amyloid-PET burden and APOE4 carrier status in a cohort of cognitively intact individuals. Methods: Our dataset included 91 macula-centered and 39 optic disc-centered images from 96 cognitively intact participants (29% male). 25 (26%) were amyloid-PET positive, defined as amyloid-PET standardized uptake value ratio centiloid cut-off > 20. AutoMorph software automatically determined retinal arteriolar and venular density, tortuosity and width, among other fractal dimensions. To test the effect of amyloid-PET status on the retinal vascular parameters, we used a generalized linear model compensated for age, sex and the interaction between APOE4 carrier and amyloid-PET status. We also compared amyloid-PET positive and negative subjects for vascular fractal dimensions correcting for age and gender. We adjusted for multiple comparisons using the False Discovery Rate correction and reported significant P values less than 0.05. Results: Compared to amyloid-PET negative, cognitively intact amyloid-PET positive cohort had greater mean age (71 vs 66 years, P=0.06), more males (60% vs 35%, P=0.02), more APOE4 carriers (P<0.001), similar vascular risk factors (hypertension, dyslipidemia, diabetes mellitus, smoking, P>0.05 for all) and significantly lower macular vessel tortuosity density (P=0.019). The amyloid-PET positive status had a significant effect on the retinal artery distance tortuosity (corrected P=8.75E-04, β=13.9, 95% CI [7.75-19.99]) and artery squared curvature tortuosity (corrected P=8.91E-10, β=464, 95% CI [359.10-569.15]). Conclusions: Automatically determined retinal vascular fractal dimension on non-mydriatic color fundus photographs predicts amyloid-PET burden in cognitively intact individuals. Future longitudinal studies should asssess the utility of automated quantitative retinal vasculopathy analysis to screen for presymptomatic AD.

Introduction: Migraine with aura may be the earliest symptom in patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). Female patients have a higher incidence of migraine with an increased associated disability. In this study, we systematically evaluate the clinical features and management of migraine in female patients with CADASIL in a multi-center health system. Methods: Clinical data was extracted from the electronic medical records of female patients diagnosed with CADASIL and managed at Mayo Clinic Enterprise. Diagnosis was confirmed by a pathogenic NOTCH3 mutation or granular osmiophilic material on skin biopsy. Results: Forty-three female patients with CADASIL were identified. Twenty-two patients (51.2%) had a diagnosis of migraine with aura and eight patients (18.6%) had a diagnosis of migraine without aura. The most common type of aura was visual (81.8%). Nineteen patients (63.3%) required at least one acute medicine and/or one preventive medicine. Acute therapy helped in 18 cases (94.7%) and preventive therapy helped in 13 cases (68.4%). Six patients (20%) tried at least three forms of acute therapy, and eleven patients (36.7%) tried at least three forms of preventive therapy. The presence of visual aura was associated with higher likelihood of need for acute therapy (OR = 3.0, 95% CI = 1.6 - 5.8, P = 0.015). However, the presence of any type of aura was associated with lower likelihood of need for or resistance to preventive therapy (OR = 0.08, 95% CI = 0.01 - 0.57, P = 0.005). Also, headache onset after age of 45 years was associated with higher likelihood of need for or resistance to preventive therapy (OR = 38.0, 95% CI = 2.7 - 528.0, P <0.001). The most common acute therapy was nonsteroidal anti-inflammatory drugs (NSAIDs) (14, 73.7%). Classes of preventive therapy involved anticonvulsants (15, 78.9%), antidepressants (11, 57.9%), Botox injections (7, 36.8%), beta blockers (6, 31.6%), calcium channel blockers (3, 15.8%), and calcitonin gene-related peptide (CGRP) inhibitors (3, 15.8%). Conclusion: Half of female patients with CADASIL had a diagnosis of migraine with aura. Around two thirds of them tried at least one form of acute therapy, most commonly NSAIDs, or preventive therapy, most commonly anticonvulsants. Resistance to preventive therapy was seen in more than 30% of the cases, highlighting the need for advances in migraine management in CADASIL.

Introduction: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is an inherited cerebral small vessel disease, yet there is currently no biomarker for early detection. This study aims to identify retinal biomarkers of NOTCH3 carriers using optical coherence tomography (OCT) from the UK Biobank. Methods: We conducted a cross-sectional, matched case-control study of individuals with or without CADASIL from the UK Biobank between 2006 and 2010. All participants had retinal OCT scan and cognitive assessment. Cases were identified based on pathogenic NOTCH3 mutations and 1:1 matched with healthy controls based on age, sex, hypertension, diabetes mellitus, and smoking status. Baseline characteristics and cognitive test scores were compared using chi-square or Mann-Whitney-U test appropriately. Macular thickness (central, inner, and outer subfields) (Figure) and retinal nerve fiber layer (RNFL) thickness were compared using Wilcoxon signed-rank test. Results: Our analysis included 134 participants (67 CADASIL cases, 67 controls) with a mean age of 54±8 years. There were no differences in visual acuity between the two groups. CADASIL performed worse in prospective memory (0.043), verbal and numerical reasoning (p=0.178), visual memory (p=0.227), and processing speed (p=0.101) than matched controls. Participants with CADASIL had significantly thinner macular inner subfield at the superior (p=0.006), temporal (p=0.008), and nasal (p=0.034) quadrants, and significantly thinner RNFL (p=0.008) compared to controls (Table). Conclusion: Individuals with CADASIL have reduced thickness in the inner macular subfield and RFNL relative to matched controls. These retinal group differences were not associated with differences in visual acuity and may reflect early pericyte dysfunction and microvascular ischemia. Longitudinal studies are needed to assess the temporal relationship between these retinal changes and disease progression.

Introduction: Informed consent (IC) plays a central role in medical care and research. Practices for endovascular thrombectomy (EVT) in acute stroke are not well elucidated. We investigated the clinical roles and medical specialties of individuals who obtain IC for EVT, aiming to provide insights for enhancing the process in contemporary stroke care. Methods: We conducted a survey from July to December 2023 among clinicians involved in acute stroke care. Utilizing Qualtrics, we disseminated a structured questionnaire through various national and international platforms including the American Academy of Neurology and StrokeNet. This analysis summarizes findings pertaining to the characteristics of those who obtain EVT IC at the respondents’ institution. Results: Among 168 participants, 71% were staff physicians, 70% practiced in the United States (US), and 70% were based at academic centers. The most common medical specialties obtaining EVT IC were neurology (77%), followed by neurosurgery (41%), radiology (30%) and emergency medicine (10%) ( Table 1 ). Staff physician (61%) was the most common clinical role involved, followed by fellows (43%), residents (48%), and advanced practice providers (APP, 36%) ( Table 2 ). Non-US institutions were more likely to utilize a provider from neurology alone (50% vs. 31%, p=0.016) and staff physicians (76% vs. 54%, p=0.008), while US institutions were more likely to utilize providers from neurosurgery (51% vs. 18%, p<0.001), APPs (43 vs. 18%, p=0.002) and residents (56% vs. 28%, p=0.001). Non-academic institutions more frequently used emergency medicine providers (25% vs. 5%, p<0.001) and APPs (50% vs. 31%, p=0.031), while academic institutions commonly utilized neurosurgery providers (48% vs. 18%, p=0.001), residents (59% vs. 13%, p<0.001) and fellows (52% vs. 18%, p<0.001). Conclusion: This study highlights the diverse medical specialties and clinical roles of persons obtaining IC for EVT, with neurologists and staff physicians being the most frequently utilized. These variations likely reflect availability and capacity of certain providers in different settings. Future efforts to optimize the IC process should be multi-disciplinary, with standardized content that addresses issues such as ischemic core volume, outcome expectations and diversity.