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Studies in patients with brain lesions play a fundamental role in unraveling the brain's functional anatomy. Lesion‐symptom mapping (LSM) techniques can relate lesion location to cognitive performance. However, a limitation of current LSM approaches is that they can only evaluate one cognitive outcome at a time, without considering interdependencies between different cognitive tests. To overcome this challenge, we implemented canonical correlation analysis (CCA) as combined multivariable and multioutcome LSM approach. We performed a proof‐of‐concept study on 1075 patients with acute ischemic stroke to explore whether addition of CCA to a multivariable single‐outcome LSM approach (support vector regression) could identify infarct locations associated with deficits in three well‐defined verbal memory functions (encoding, consolidation, retrieval) based on four verbal memory subscores derived from the Seoul Verbal Learning Test (immediate recall, delayed recall, recognition, learning ability). We evaluated whether CCA could extract cognitive score patterns that matched prior knowledge of these verbal memory functions, and if these patterns could be linked to more specific infarct locations than through single‐outcome LSM alone. Two of the canonical modes identified with CCA showed distinct cognitive patterns that matched prior knowledge on encoding and consolidation. In addition, CCA revealed that each canonical mode was linked to a distinct infarct pattern, while with multivariable single‐outcome LSM individual verbal memory subscores were associated with largely overlapping patterns. In conclusion, our findings demonstrate that CCA can complement single‐outcome LSM techniques to help disentangle cognitive functions and their neuroanatomical correlates.

Low hemoglobin levels are known to be associated with hematoma expansion (HE) and poor functional outcome in patients with intracerebral hemorrhage (ICH). However, it is not yet known whether low hemoglobin itself causes HE directly or is merely a confounder. Thus, we investigated the mediation effect of the mean Hounsfield unit (HU) of hematoma on the relationship between low hemoglobin and expansion of ICH. Overall, 232 consecutive patients with ICH who underwent non-contrast computed tomography (NCCT) within 12 h since onset were included. The mean HU and hematoma volume on NCCT were investigated using semi-automated planimetry. HE was defined as an increase in hematoma volume > 33% or 6 mL. The respective associations among the hemoglobin level, mean HU, and HE were analyzed using multivariable regression analysis, adjusting for age, sex, and known HE predictors. Mediation analysis was performed to examine the potential causal association among the three. HE occurred in 34.5% of patients; hemoglobin levels were inversely associated with HE occurrence (adjusted odds ratio, 0.90; p  = 0.03). The mean HU of the hematoma was lower in patients with HE than in patients without HE (58.5 ± 3.3 vs. 56.8 ± 3.0; p  < 0.01). Hemoglobin levels on admission were linearly related to the mean HU (adjusted β, 0.33; p  < 0.01) after adjusting for known HE predictors (time from onset to CT, antithrombotic use, hematoma volume). Causal mediation analysis showed a significant mediation effect of the mean HU on the association between hemoglobin levels and HE ( p  = 0.04). The proportion of indirect effect through the mean HU among the total effect was 19% ( p  = 0.05). The mediation effect became nonsignificant in the when the multivariable model was adjusted with additional covariates (baseline systolic blood pressure and hematoma location). The mean HU of the hematoma mediated the association between hemoglobin levels and HE occurrence. Therefore, the mean HU of the hematoma may be a potential marker of impaired hemostasis in patients with ICH.

This study aimed to demonstrate the effectiveness of urgent extracranial-to-intracranial bypass (EIB) in acute ischemic stroke (AIS) through quantitative analysis of computed tomography perfusion (CTP) results using RAPID software. We retrospectively analyzed 41 patients who underwent urgent EIB for AIS under strict operation criteria. The quantitative data from CTP images were reconstructed to analyze changes in pre- and postoperative perfusion status in terms of objective numerical values using RAPID software. Short- and long-term clinical outcomes, including complications and neurological status, were also analyzed. Postoperatively, the volume of time-to-max (Tmax) > 6 s decreased significantly; it continued to improve significantly until 6 months postoperatively (preoperative, 78 ml (median); immediate postoperative, 23 ml; postoperative 6 months, 7 ml; p  = 0.000). Ischemic core-penumbra mismatch volumes were also significantly improved until 6 months postoperatively (preoperative, 72 ml (median); immediate postoperative, 23 ml; postoperative 6 months, 5 ml; p  = 0.000). In addition, the patients’ neurological condition improved significantly ( p  < 0.001). Only one patient (2.3%) showed progression of infarction. Urgent EIB using strict indications can be a feasible treatment for IAT-ineligible patients with AIS due to large vessel occlusion or stenosis.

Background The dietary carbohydrate-to-fiber ratio (CFR) provides a comprehensive measure of carbohydrate quality; however, its association with cognitive outcomes remains unexplored. Given the distinct health effects of different types of carbohydrates, understanding the impact of CFR on dementia risk and brain structure is valuable. Methods This prospective cohort study analyzed 107,785 UK Biobank participants aged ≥ 55 years who completed at least one 24-hour dietary recall between 2011 and 2012, with follow-up until April 2024. CFR was calculated as the ratio of daily carbohydrate intake to fiber intake. Total carbohydrate and dietary fiber intake were included as secondary exposures. CFR outliers were excluded using Tukey’s method (3.0 × interquartile range). The primary outcome was all-cause dementia incidence identified through linked hospital and death registry data. Secondary outcomes were hippocampal volume, entorhinal cortical thickness and frontal cortical thickness. Cox proportional hazards models estimated dementia risk, and multiple linear regression analyzed MRI markers. Models were adjusted for age, sex, education, BMI, physical activity, smoking, alcohol intake, hypertension, diabetes, and total energy intake. Interactions between dietary factors and polygenic risk score (PRS) were examined. Results During a median follow-up of 11.8 years, 2,000 dementia cases occurred, corresponding to incidence rates of 1.44 and 1.82 per 1,000 person-years in the lowest and highest CFR quartiles, respectively. A higher CFR was significantly associated with increased dementia risk (HR per 1 SD = 1.07, 95% CI: 1.02–1.12, p  = 0.003). The association was slightly attenuated in individuals with increased genetic susceptibility (p for interaction = 0.02). Total carbohydrate intake was associated with dementia risk (HR per 1 SD = 1.15, 95% CI: 1.05–1.25, p  = 0.001), whereas fiber intake was not ( p  = 0.99). An elevated CFR was also associated with reduced entorhinal cortical thickness (FDR p  = 0.03) and with thinner frontal pole, medial orbitofrontal cortex, and rostral middle frontal cortex (all FDR p  = 0.01) among 14,388 participants with MRI data. Conclusions A higher CFR was associated with increased dementia risk, reduced entorhinal thickness, and thinner frontal cortical regions, suggesting that CFR may serve as a practical indicator of carbohydrate quality with potential implications for dietary and public health approaches to cognitive aging.

Although the obesity paradox is an important modifiable factor in cardiovascular diseases, little research has been conducted to determine how it affects post-stroke cognitive function. We aimed to investigate the association between body mass index (BMI) and domain-specific cognitive outcomes, focusing on the subdivision of each frontal domain function in post-ischemic stroke survivors. A total of 335 ischemic stroke patients were included in the study after completion of the Korean-Mini Mental Status Examination (K-MMSE) and the vascular cognitive impairment harmonization standards neuropsychological protocol at 3 months after stroke. Frontal lobe functions were analyzed using semantic/phonemic fluency, processing speed, and mental set shifting. Our study participants were categorized into four groups according to BMI quartiles. The z-scores of K-MMSE at 3 months differed significantly between the groups after adjustment for initial stroke severity ( p  = 0.014). Global cognitive function in stroke survivors in the Q1 (the lowest quartile) BMI group was significantly lower than those in Q2 and Q4 (the highest quartile) BMI groups (K-MMSE z-scores, Q1: − 2.10 ± 3.40 vs. Q2: 0.71 ± 1.95 and Q4: − 1.21 ± 1.65). Controlled oral word association test findings indicated that phonemic and semantic word fluency was lower in Q4 BMI group participants than in Q2 BMI group participants ( p  = 0.016 and p  = 0.023 respectively). BMI might differentially affect cognitive domains after ischemic stroke. Although being underweight may negatively affect global cognition post-stroke, obesity could induce frontal lobe dysfunctions, specifically phonemic and semantic word fluency.

RAO is caused by various etiologies and subsequent vascular events may be associated with underlying etiologies. Our aim is to investigate the etiologies of RAO, the occurrence of subsequent vascular events and their association in patients with RAO. We analyzed data from 151 consecutive patients presenting with acute non-arteritic RAO between 2003 and 2013 in a single tertiary-care hospital. The primary outcome was the occurrence of a vascular event defined as stroke, myocardial infarction, and vascular death within 365 days of the RAO onset. The Kaplan-Meier survival analysis and Cox proportional hazard model were used to estimate the hazard ratio of the vascular events. Large artery atherosclerosis (LAA) was the etiology more frequently associated with of RAO (41.1%, 62/151). During the one year follow-up, ischemic stroke and vascular events occurred in 8.6% and 9.9% of patients, respectively. Ten vascular events occurred in RAO patients attributed to LAA and 4 occurred in undetermined etiology. RAO patients with LAA had a nearly four times higher risk of vascular events compared to those without LAA (hazard ratio 3.94, 95% confidence interval 1.21-12.81). More than a half of all events occurred within one month and over three fourths of ischemic strokes occurred ipsilateral to the RAO. After occurrence of RAO, there is a high risk of a subsequent vascular event, particularly ipsilateral stroke, within one month. LAA is an independent factor for the occurrence of a subsequent vascular event. Management for the prevention of secondary vascular events is necessary in patients with RAO especially with LAA. Large clinical trials are needed to confirm these findings.

Objective Evaluating leukoaraiosis (LA) on CT is challenging due to its low contrast and similarity to parenchymal gliosis. We developed and validated a deep learning algorithm for LA segmentation using CT‐MRIFLAIR paired data from a multicenter Korean registry and tested it in a US dataset. Methods We constructed a large multicenter dataset of CT–FLAIR MRI pairs. Using validated software to segment white matter hyperintensity (WMH) on FLAIR, we generated pseudo‐ground‐truth LA labels on CT through deformable image registration. A 2D nnU‐Net architecture was trained solely on CT images and registered masks. Performance was evaluated using the Dice similarity coefficient (DSC), concordance correlation coefficient (CCC), and Pearson correlation across internal, external, and US validation cohorts. Clinical associations of predicted LA volume with age, risk factors, and poststroke outcomes were also analyzed. Results The external test set yielded a DSC of 0.527, with high volume correlations against registered LA (r = 0.953) and WMH (r = 0.951). In the external testing and US datasets, predicted LA volumes correlated with Fazekas grade (r = 0.832–0.891) and the correlations were consistent across CT vendors and infarct volumes. In an independent clinical cohort (n = 867), LA volume was independently associated with age, vascular risk factors, and 3‐month functional outcomes. Interpretation Our deep learning algorithm offers a reproducible method for LA segmentation on CT, bridging the gap between CT and MRI assessments in patients with ischemic stroke.

ObjectivesThis study aimed to investigate infarct growth patterns in stroke patients with large vessel occlusion (LVO) and successful recanalization by endovascular therapy (EVT).MethodsA total of 135 patients with LVO of the internal carotid artery or proximal segment of the middle cerebral artery admitted within 12 h after onset, having baseline National Institute of Health Stroke Scale score ≥ 5 points, and successfully recanalized by EVT were enrolled. Infarct growth pattern models were developed based on infarct volumes on diffusion-weighted imaging before and after reperfusion. Single pattern models of linear, logarithmic, and exponential shapes were initially tested. Their appropriateness was predetermined. If none of these patterns was suitable, the best pattern model, which was the most suitable pattern among the three shapes selected for each individual, was tested. Clinical correlates were explored.ResultsEach single pattern model was tested for their suitability. However, none of the single pattern models successfully represented infarct growth curves: Of all subjects, only 63.7%, 62.2%, and 54.1% of patients were explained by the logarithmic, linear, and exponential model, respectively. Compared with the single pattern models, the best pattern model explained 80.7% of the subjects. The linear shape fit best in 40 patients, the logarithmic in 51, and the exponential in 44. Those fit best for the logarithmic pattern showed more favorable outcomes at discharge (31.4%) than did the others (linear, 10.0%; exponential, 9.1%; p = 0.01).ConclusionsInfarct growth patterns may vary among individual patients with acute stroke due to LVO and successful treatment with EVT.Key Points• Infarct growth during the acute stage of stroke is highly dynamic and the exact shape remains unknown.• Infarct growth pattern models were developed based on infarct volumes on diffusion-weighted imaging before and after reperfusion.• Infarct growth patterns may not be singular, rather various among individual patients with acute stroke due to LVO and successful treatment with EVT.

How short-term blood pressure variability (BPV) is affected in the acute stage of ischemic stroke and whether BPV is associated with early neurologic outcomes remains unclear. Patients who admitted for ischemic stroke within 24 h of symptom onset were consecutively identified between January 2010 and January 2015. BP profiles measured in real-time were summarized into short-term, 24-h time intervals, based on standard deviation (SD) and mean of systolic BP (SBPSD) during the first 3 days. The primary outcome was daily assessment of early neurological deterioration (END). The associations between short-term SBPSD values and the secular trend for primary outcome were examined. A total of 2,545 subjects (mean age, 67.1 ± 13.5 years old and median baseline National Institutes of Health Stroke Scale score, 3) arrived at the hospital an average of 6.1 ± 6.6 h after symptom onset. SBPSD values at day 1 (SD#D1), SD#D2, and SD#D3 were 14.4 ± 5.0, 12.5 ± 4.5, and 12.2 ± 4.6 mmHg, respectively. Multivariable analyses showed that SD#D2 was independently associated with onset of END at day 2 (adjusted odds ratio, 1.08; 95% confidence interval, 1.03-1.13), and SD#D3 was independently associated with END#D3 (1.07, 1.01-1.14), with adjustments for predetermined covariates, SBPmean, and interactions with daily SBPSD. Short-term BPV changed and stabilized from the first day of ischemic stroke. Daily high BPV may be associated with neurological deterioration independent of BPV on the previous day.

We hypothesized that the association between BP and endovascular treatment (EVT) outcomes would differ by baseline perfusion and recanalization status. We identified 388 ICA or M1 occlusion patients who underwent EVT ≤ 24 h from onset with successful recanalization (TICI ≥ 2b). BP was measured at 5-min intervals from arrival and during the procedure. Systolic BPs (SBP) were summarized as dropmax (the maximal decrease over two consecutive measurements), incmax (the maximal increase), mean, coefficient of variation (cv), and standard deviation. Adequate baseline perfusion was defined as hypoperfusion intensity ratio (HIR) ≤ 0.5; infarct proportion as the volume ratio of final infarcts within the T max  > 6 s region. In the adequate perfusion group, infarct proportion was closely associated with SBP dropmax (β ± SE ( P -value); 1.22 ± 0.48, (< 0.01)), SBP incmax (1.12 ± 0.33, (< 0.01)), SBP cv (0.61 ± 0.15 (< 0.01)), SBP sd (0.66 ± 0.08 (< 0.01)), and SBP mean (0.71 ± 0.37 (0.053) before recanalization. The associations remained significant only in SBP dropmax , SBP incmax , and SBP mean after recanalization. SBP incmax , SBP cv and SBP sd showed significant associations with modified Rankin Scale score at 3 months in the pre-recanalization period. In the poor perfusion group, none of the SBP indices was associated with any stroke outcomes regardless of recanalization status. BP may show differential associations with stroke outcomes by the recanalization and baseline perfusion status.