Brain frailty associated with stroke events in anterior circulation large artery occlusion.

OBJECTIVE: To investigate the factors associated with brain frailty and the effect of brain frailty in patients with anterior circulation large artery occlusion (AC-LAO). METHODS: 1100 patients with AC-LVO consecutively admitted to the Second Hospital of Hebei Medical University, North China between June 2016 and April 2018 were retrospectively analyzed. The variables associated with brain frailty and stroke outcome were analyzed by ANOVA analysis, the Mann-Whitney U test and multiple linear regression. Based on previous research. Brain frailty score comprises 1 point each for white matter hyperintensity (WMH), old infarction lesions, and cerebral atrophy among 983 participants with baseline brain magnetic resonance imaging or computed tomography. RESULTS: Among AC-LAO participants, baseline brain frailty score ≥ 1 was common (750/983, 76.3%). Duration of hypertension > 5 years (mean difference [MD] 0.236, 95% CI 0.077, 0.395, p = 0.004), multiple vessel occlusion (MD 0.339, 95% CI 0.068, 0.611, p = 0.014) and basal ganglia infarction (MD -0.308, 95% CI -0.456, -0.160, p < 0.001) were independently associated with brain frailty score. Brain frailty score was independently associated with stroke events, and higher brain frailty scores were associated with higher rates of stroke events (p < 0.001). However, brain frailty has no independent effect on short-term outcome of ACI in AC-LAO patients. CONCLUSIONS: In AC-LAO patients, older age, duration of hypertension > 5 years, and multiple vessel occlusion influenced the brain frailty score. Brain frailty score was independently associated with the occurrence of stroke events in AC-LAO patients.

Automatic segmentation of hemispheric CSF on MRI using deep learning: Quantifying cerebral edema following large hemispheric infarction.

Background and objective: Cerebral edema (CED) is a serious complication of acute ischemic stroke (AIS), especially in patients with large hemispheric infarction (LHI). Herein, a deep learning-based approach is implemented to extract CSF from T2-Weighted Imaging (T2WI) and evaluate the relationship between quantified cerebrospinal fluid and outcomes. Methods: Patients with acute LHI who underwent magnetic resonance imaging (MRI) were included. We used a deep learning algorithm to segment the CSF from T2WI. The hemispheric CSF ratio was calculated to evaluate its relationship with the degree of brain edema and prognosis in patients with LHI. Results: For the 93 included patients, the left and right cerebrospinal fluid regions were automatically extracted with a mean Dice similarity coefficient of 0.830. Receiver operating characteristic analysis indicated that hemispheric CSF ratio was an accurate marker for qualitative severe cerebral edema (area under receiver-operating-characteristic curve 0.867 [95% CI, 0.781-0.929]). Multivariate logistic regression analysis of functional prognosis showed that previous stroke (OR = 5.229, 95% CI 1.013-26.984), ASPECT≤6 (OR = 13.208, 95% CI 1.136-153.540) and low hemispheric CSF ratio (OR = 0.966, 95% CI 0.937-0.997) were significantly associated with higher chances for unfavorable functional outcome in patients with LHI. Conclusions: Automated assessment of CSF volume provides an objective biomarker of cerebral edema that can be leveraged to quantify the degree of cerebral edema and confirm its predictive effect on outcomes after LHI.