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ObjectiveTo determine whether thrombectomy is safe in children up to 24 hours after onset of symptoms when selected by mismatch between clinical deficit and infarct.MethodsA secondary analysis of the Save ChildS Study (January 2000–December 2018) was performed, including all pediatric patients (ResultsTwenty children with a median age of 10.5 (interquartile range [IQR] 7–14.6) years were included. Of those, 7 were male (35%), and median time from onset to thrombectomy was 9.8 (IQR 7.8–16.2) hours. Neurologic outcome improved from a median Pediatric NIH Stroke Scale score of 12.0 (IQR 8.8–20.3) at admission to 2.0 (IQR 1.2–6.8) at day 7. Median modified Rankin Scale (mRS) score was 1.0 (IQR 0–1.6) at 3 months and 0.0 (IQR 0–1.0) at 24 months. One patient developed transient peri-interventional vasospasm; no other complications were observed. A comparison of the mRS score to the mRS score in the DAWN and DEFUSE 3 trials revealed a higher proportion of good outcomes in the pediatric compared to the adult study population.ConclusionsThrombectomy in pediatric ischemic stroke in an extended time window of up to 24 hours after onset of symptoms seems safe and neurologic outcomes are generally good if patients are selected by a mismatch between clinical deficit and infarct.Classification of EvidenceThis study provides Class IV evidence that for children with acute ischemic stroke with a mismatch between clinical deficit and infarct size, thrombectomy is safe.

Background and Purpose— The introduction of stent retrievers allows for a complete extraction and histological analysis of human clots. Initial studies describe an impact of preinterventional clot migration on technical and clinical success of thrombectomy and an association with worse clinical outcome. We, therefore, performed a large study of consecutive patients whose clots have been histologically analyzed and tried to determine whether clot composition influences the rates of clot migration and thereby interventional and clinical outcome. Methods— We retrospectively evaluated data of a prospectively collected cohort of 198 consecutive patients with occlusion of the middle cerebral artery. We investigated the relationship between clot histology expressed as percentage of the main components (fibrin, erythrocytes [red blood cell], and white blood cells), the preinterventional computed tomography attenuation of the emboli, embolus length, and clot migration. We defined a binary outcome (clot migration versus no clot migration). The impact of embolus composition and computed tomography features was assessed in univariable and multivariable logistic regression models. Results— One hundred sixty-three patients fulfilled the inclusion criteria, of which 36 (22.1%) showed a clot migration. Patients with proven clot migration had significantly higher levels of red blood cells than patients without clot migration (median 50% versus 26%, P P P P Conclusions— Erythrocyte-rich clots and a shorter embolus length are independent reliable predictors for clot migration. This finding is clinically important as clot migration might have a negative impact on technical and clinical outcomes of patients suffering from emergent vessel occlusions of the middle cerebral artery undergoing endovascular therapy.

Futile recanalization with poor clinical outcome after endovascular treatment of acute ischemic stroke is poorly understood. Recently, vessel recanalization has been associated with reduced ischemic brain edema in patients with good clinical outcome. As edema volume (EV) may be quantified in computed tomography (CT), we hypothesized that higher EV after revascularization predicts futile recanalization with poor outcome.In this observational study, 67 ischemic stroke patients with M1 middle cerebral artery occlusion fulfilled all inclusion criteria and were analyzed. All patients received successful endovascular recanalization (thrombolysis in cerebral infarction scale 2b/3) and subsequent follow-up CT 24 hours later. Edema volume within the infarct lesion was calculated in follow-up CT applying lesion water uptake quantification and was used to predict clinical outcome (Modified Rankin Scale [mRS] after 90 days) compared with infarct volume.The median EV after thrombectomy was 1.6 mL (interquartile range, 0.2-4.2 mL) in patients with mRS 0 to 4 and 8.6 mL (interquartile range, 2.0-49.8 mL) in patients with mRS 5 to 6 (P = 0.0008). In regression analysis, an EV increase of 1 mL was associated with an 8.0% increased likelihood of poor outcome (95% confidence interval, 2.8%-15.4%; P = 0.008). Based on univariate receiver operating characteristic curve analysis, absolute EV over 4.2 mL predicted poor outcome (mRS 5-6) with good discriminative power (area under curve, 0.74; 95% confidence interval, 0.62-0.84; specificity, 77%; sensitivity, 68%). In comparison, the area under curve for infarct volume was 0.68.Elevated EV after endovascular thrombectomy was associated with poor clinical outcome and may indicate futile recanalization.

Background and Purpose— The early growth of ischemic lesions has been described as being nonlinear, with lesion growth rates at their highest during the earliest period after stroke onset. We hypothesized that the time gap from imaging to revascularization results in higher lesion growth in patients with hyperacute presentation. Methods— Fifty-one patients with ischemic stroke with initial multimodal computed tomography (CT), follow-up CT after 24 hours, and successful endovascular recanalization were included and separated into 2 groups according to their median time from symptom onset to imaging (eg, hyperacute versus acute). The difference in Alberta Stroke Program Early CT Score (ASPECTS) between initial CT and follow-up CT was assessed, as well as volumetric lesion growth from early ischemic core in admission perfusion CT and total lesion volume in follow-up CT. Results— The median time from onset to imaging was 1.85 hours. There was no significant difference in admission ASPECTS (mean, 8.5 versus 8.2) or time from imaging to recanalization in both groups (median, 2.7 versus 2.4 hours; P =0.4). The mean (SD) lesion growth assessed by ASPECTS difference was 2.7 (2.3) in the hyperacute group and 1.6 (1.3) in the acute group ( P =0.03). The mean (SD) volumetric difference in the hyperacute group was 26.6 mL (43.2 mL) and 17.2 mL (26.3 mL; P =0.36) in the acute group, respectively. For every passing hour after onset, ASPECTS lesion growth was reduced by 0.4. Conclusions— Patients in the hyperacute phase showed increased ASPECTS lesion growth from imaging to recanalization suggesting a particular benefit of faster recanalization times in this group of patients with stroke.

Background and Purpose— Arterial ischemic stroke (AIS) in childhood is a severe disease with potentially lifelong restrictions. Apart from cardiac or prothrombotic embolism, arteriopathy has been identified as a major cause and significant target of secondary stroke prevention. The Childhood Arterial Ischemic Stroke Standardized Classification and Diagnostic Evaluation (CASCADE) criteria facilitate a structured tool for categorizing and reporting childhood strokes according to the underlying cause. Our study aims to identify the prognostic value of CASCADE classification on admission for further course of arteriopathy and risk of stroke recurrence. Moreover, we give recommendations for follow-up imaging based on different CASCADE subgroups. Methods— Between 2004 and 2017, we identified 86 children with an acute arterial ischemic stroke classified in the 7-basic and 19-expanded subgroups of the acute CASCADE criteria. All included children were diagnosed and followed-up by magnetic resonance imaging. All arteriopathic strokes (basic subgroups 1–4 of acute CASCADE criteria) were further categorized into the chronic CASCADE criteria, including progressive, stable, reversible, and indeterminate course. Outcomes were defined as stroke recurrence and course of arteriopathy according to chronic CASCADE criteria. Associations between acute CASCADE criteria classification and stroke recurrence were assessed by Fisher exact test and between acute CASCADE criteria and chronic CASCADE criteria by Fisher exact test and Mann-Whitney U test. Results— A total of 86 children were included; of these, 57 presented with arteriopathic stroke (CASCADE 1–4) and 29 as nonarteriopathic. Unilateral cerebral arteriopathy (CASCADE 2; P =0.036) and bilateral cerebral arteriopathy (CASCADE 3; P =0.016) significantly correlated with stroke recurrence, and progressive arteriopathy significantly correlated with unilateral focal cerebral arteriopathy ( P P =0.005). Conclusions— Initial CASCADE classification is associated with risk of recurrent strokes and progress of arteriopathy. Moreover, time points of arteriopathic progress vary according to the underlying cause.

Background: Intracranial hemorrhage (ICH) requires prompt diagnosis to optimize patient outcomes 1 . We hypothesized that machine learning algorithms could automatically analyze non-contrast computed tomography (NECT) of the head and predict clinical outcome of ICH patients 2 . Methods: 300 NECTs with acute spontaneous ICH between 2014-2019 were retrospectively included from the database at a tertiary university hospital. A binary outcome was defined as Modified Ranking Scale (mRS) 0-3 (good outcome) and mRS 4-6 (bad outcome) at discharge. Radiomic features including shape, histogram and texture markers were extracted from non- , wavelet- and log-sigma-filtered images using regions of interest of ICH. The quantitative predictors were evaluated utilizing random forest algorithms with 5-fold model-external cross-validation. Results: The model achieved an area under the ROC curve of 0.81 (95% CI [0.077; 0.86]; P Discussion: In conclusion, quantitative features of acute NECT images in a machine learning algorithm provided high discriminatory power in predicting functional outcome. In clinical routine, this proposed approach could allow early triage of high-risk patients for poor outcome. Indication of source:1 Qureshi, A. I. et al. Intracerebral haemorrhage. Lancet. 2009. 2 Mohammad R. Arbabshirani et al. Advanced machine learning in action: identification of intracranial hemorrhage on computed tomography scans of the head with clinical workflow integration. npj Digital Medicine. 2018.

BACKGROUND Malignant cerebellar edema (MCE) is a life-threatening complication of ischemic posterior circulation stroke that requires timely diagnosis and management. Yet, there is no established imaging biomarker that may serve as predictor of MCE. Early edematous water uptake can be determined using quantitative lesion water uptake, but this biomarker has only been applied in anterior circulation strokes. OBJECTIVE To test the hypothesis that lesion water uptake in early posterior circulation stroke predicts MCE. METHODS A total 179 patients with posterior circulation stroke and multimodal admission CT were included. A total of 35 (19.5%) patients developed MCE defined by using an established 10-point scale in follow-up CT, of which ≥4 points are considered malignant. Posterior circulation net water uptake (pcNWU) was quantified in admission CT based on CT densitometry and compared with posterior circulation Acute Stroke Prognosis Early CT Score (pc-ASPECTS) as predictor of MCE using receiver operating curve (ROC) analysis and logistic regression analysis. RESULTS Acute pcNWU within the early ischemic lesion was 24.6% (±8.4) for malignant and 7.2% (±7.4) for nonmalignant infarctions, respectively (P

Purpose: Severity of white matter (WM) lesion load is difficult to quantify precisely in computed tomography (CT) even though it is the most frequently used imaging modality for brain. This pilot study addressed the need for reliable automated observer-independent quantification of white matter disease in CT. The purpose was to present and evaluate a CT-based automated rater independent method for assessment of microangiopathic WM changes. Methods and Materials: A probabilistic WM-tissue-map in standad MNI-152 space was obtained from 600 normal MRI scans from two large population studies (published previously). Robust registration of the WM-tissue-map to individual CT space was accomplished by affine linear registration with non-linear refinement (FSL4.1). The tissue- specific density (Hounsfield Unit, HU) within WM-space of the CT image was determined by the mean of all voxel densities weighted by WM content: Σ (HUxyz × Pxyz (WM))/ Σ (Pxyz (WM) ; (HUxyz = density of voxelxyz ; Pxyz = partial WM content at voxelxyz). The reduction of HU over WM-space in 40 CT images with visible WM disease was correlated with gold standard MR-based WM lesion volume measurements. Results: Automated WM-specific segmentation of brain CT was reliable in 40 cases with varying occurrence of WM-disease. Microangiopathic reduction of density within WM-space showed high correlation with MRI FLAIR-based WM-lesion volume (Pearson correlation coefficient 0.87). Conclusion: Automated quantification of density reduction within WM-space in CT images is feasible and may be used as a surrogate for gold standard MR based WM lesion load. The presented method needs further validation with larger datasets and different CT scanner protocols.