Comprehensive Venous Outflow Predicts Functional Outcomes in Patients with Acute Ischemic Stroke Treated by Thrombectomy.

BACKGROUND AND PURPOSE: Cortical venous outflow has emerged as a robust measure of collateral blood flow in acute ischemic stroke. The addition of deep venous drainage to this assessment may provide valuable information to further guide the treatment of these patients. MATERIALS AND METHODS: We performed a multicenter retrospective cohort study of patients with acute ischemic stroke treated by thrombectomy between January 2013 and January 2021. The internal cerebral veins were scored on a scale of 0-2. This metric was combined with existing cortical vein opacification scores to create a comprehensive venous outflow score from 0 to 8 and stratify patients as having favorable-versus-unfavorable comprehensive venous outflow. Outcome analyses were primarily conducted using the Mann-Whitney U and χ2 tests. RESULTS: Six hundred seventy-eight patients met the inclusion criteria. Three hundred fifteen were stratified as having favorable comprehensive venous outflow (mean age, 73 years; range, 62-81 years; 170 men), and 363, as having unfavorable comprehensive venous outflow (mean age, 77 years; range, 67-85 years; 154 men). There were significantly higher rates of functional independence (mRS 0-2; 194/296 versus 37/352, 66% versus 11%, P < .001) and excellent reperfusion (TICI 2c/3; 166/313 versus 142/358, 53% versus 40%, P < .001) in patients with favorable comprehensive venous outflow. There was a significant increase in the association of mRS with the comprehensive venous outflow score compared with the cortical vein opacification score (-0.74 versus -0.67, P = .006). CONCLUSIONS: A favorable comprehensive venous profile is strongly associated with functional independence and excellent postthrombectomy reperfusion. Future studies should focus on patients with venous outflow status that is discrepant with the eventual outcome.

Detection of Early Ischemic Changes with Virtual Noncontrast Dual-Energy CT in Acute Ischemic Stroke: A Noninferiority Analysis.

BACKGROUND AND PURPOSE: Dual-energy virtual NCCT has the potential to replace conventional NCCT to detect early ischemic changes in acute ischemic stroke. In this study, we evaluated whether virtual NCCT is noninferior compared with standard linearly blended NCCT, a surrogate of conventional NCCT, regarding the detection of early ischemic changes with ASPECTS. MATERIALS AND METHODS: Adult patients who presented with suspected acute ischemic stroke and who underwent dual-energy NCCT and CTA and brain MR imaging within 48 hours were included. Standard linearly blended images were reconstructed to match a conventional NCCT. Virtual NCCT images were reconstructed from CTA. ASPECTS was evaluated on conventional NCCT, virtual NCCT, and DWI, which served as the reference standard. Agreement between CT assessments and the reference standard was evaluated with the Lin concordance correlation coefficient. Noninferiority was assessed with bootstrapped estimates of the differences in ASPECTS between conventional and virtual NCCT with 95% CIs. RESULTS: Of the 193 included patients, 100 patients (52%) had ischemia on DWI. Compared with the reference standard, the ASPECTS concordance correlation coefficient for conventional and virtual NCCT was 0.23 (95% CI, 0.15-0.32) and 0.44 (95% CI, 0.33-0.53), respectively. The difference in the concordance correlation coefficient between virtual and conventional NCCT was 0.20 (95% CI, 0.01-0.39) and did not cross the prespecified noninferiority margin of -0.10. CONCLUSIONS: Dual-energy virtual NCCT is noninferior compared with conventional NCCT for the detection of early ischemic changes with ASPECTS.

Prediction of Clinical Outcome in Patients with Large-Vessel Acute Ischemic Stroke: Performance of Machine Learning versus SPAN-100.

BACKGROUND AND PURPOSE: Traditional statistical models and pretreatment scoring systems have been used to predict the outcome for acute ischemic stroke patients (AIS). Our aim was to select the most relevant features in terms of outcome prediction on the basis of machine learning algorithms for patients with acute ischemic stroke and to compare the performance between multiple models and the Stroke Prognostication Using Age and National Institutes of Health Stroke Scale (SPAN-100) index model. MATERIALS AND METHODS: A retrospective multicenter cohort of 1431 patients with acute ischemic stroke was subdivided into recanalized and nonrecanalized patients. Extreme Gradient Boosting machine learning models were built to predict the mRS score at 90 days using clinical, imaging, combined, and best-performing features. Feature selection was performed using the relative weight and frequency of occurrence in the models. The model with the best performance was compared with the SPAN-100 index model using area under the receiver operating curve analysis. RESULTS: In 3 groups of patients, the baseline NIHSS was the most significant predictor of outcome among all the parameters, with relative weights of 0.36∼0.69; ischemic core volume on CTP ranked as the most important imaging biomarker with relative weights of 0.29∼0.47. The model with the best-performing features had a better performance than the other machine learning models. The area under the curve of the model with the best-performing features was higher than SPAN-100 model and reached statistical significance for the total (P < .05) and the nonrecanalized patients (P < .001). CONCLUSIONS: Machine learning-based feature selection can identify parameters with higher performance in outcome prediction. Machine learning models with the best-performing features, especially advanced CTP data, had superior performance of the recovery outcome prediction for patients with stroke at admission in comparison with SPAN-100.

Automated Cerebral Hemorrhage Detection Using RAPID.

BACKGROUND AND PURPOSE: Intracranial hemorrhage (ICH) is an important event that is diagnosed on head NCCT. Increased NCCT utilization in busy hospitals may limit timely identification of ICH. RAPID ICH is an automated hybrid 2D-3D convolutional neural network application designed to detect ICH that may allow for expedited ICH diagnosis. We determined the accuracy of RAPID ICH for ICH detection and ICH volumetric quantification on NCCT. MATERIALS AND METHODS: NCCT scans were evaluated for ICH by RAPID ICH. Consensus detection of ICH by 3 neuroradiology experts was used as the criterion standard for RAPID ICH comparison. ICH volume was also automatically determined by RAPID ICH in patients with intraparenchymal or intraventricular hemorrhage and compared with manually segmented ICH volumes by a single neuroradiology expert. ICH detection accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and positive and negative likelihood ratios by RAPID ICH were determined. RESULTS: We included 308 studies. RAPID ICH correctly identified 151/158 ICH cases and 143/150 ICH-negative cases, which resulted in high sensitivity (0.956, CI: 0.911-0.978), specificity (0.953, CI: 0.907-0.977), positive predictive value (0.956, CI: 0.911-0.978), and negative predictive value (0.953, CI: 0.907-0.977) for ICH detection. The positive likelihood ratio (20.479, CI 9.928-42.245) and negative likelihood ratio (0.046, CI 0.023-0.096) for ICH detection were similarly favorable. RAPID ICH volumetric quantification for intraparenchymal and intraventricular hemorrhages strongly correlated with expert manual segmentation (correlation coefficient r = 0.983); the median absolute error was 3 mL. CONCLUSIONS: RAPID ICH is highly accurate in the detection of ICH and in the volumetric quantification of intraparenchymal and intraventricular hemorrhages.

Hypoperfusion intensity ratio correlates with angiographic collaterals in acute ischaemic stroke with M1 occlusion.

BACKGROUND AND PURPOSE: Among patients with an acute ischaemic stroke secondary to large-vessel occlusion, the hypoperfusion intensity ratio (HIR) [time to maximum (TMax) > 10 volume/TMax > 6 volume] is a strong predictor of infarct growth. We studied the correlation between HIR and collaterals assessed with digital subtraction angiography (DSA) before thrombectomy. METHODS: Between January 2014 and March 2018, consecutive patients with an acute ischaemic stroke and an M1 middle cerebral artery (MCA) occlusion who underwent perfusion imaging and endovascular treatment at our center were screened. Ischaemic core (mL), HIR and perfusion mismatch (TMax > 6 s minus core volume) were assessed through magnetic resonance imaging or computed tomography perfusion. Collaterals were assessed on pre-intervention DSA using the American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology (ASITN/SIR) scale. Baseline clinical and perfusion characteristics were compared between patients with good (ASITN/SIR score 3-4) and those with poor (ASITN/SIR score 0-2) DSA collaterals. Correlation between HIR and ASITN/SIR scores was evaluated using Pearson's correlation. Receiver operating characteristic analysis was performed to determine the optimal HIR threshold for the prediction of good DSA collaterals. RESULTS: A total of 98 patients were included; 49% (48/98) had good DSA collaterals and these patients had significantly smaller hypoperfusion volumes (TMax > 6 s, 89 vs. 125 mL; P = 0.007) and perfusion mismatch volumes (72 vs. 89 mL; P = 0.016). HIR was significantly correlated with DSA collaterals (-0.327; 95% confidence interval, -0.494 to -0.138; P = 0.01). An HIR cut-off of <0.4 best predicted good DSA collaterals with an odds ratio of 4.3 (95% confidence interval, 1.8-10.1) (sensitivity, 0.792; specificity, 0.560; area under curve, 0.708). CONCLUSION: The HIR is a robust indicator of angiographic collaterals and might be used as a surrogate of collateral assessment in patients undergoing magnetic resonance imaging. HIR <0.4 best predicted good DSA collaterals.

Patient Outcomes and Cerebral Infarction after Ruptured Anterior Communicating Artery Aneurysm Treatment.

BACKGROUND AND PURPOSE: Anterior communicating artery aneurysm rupture and treatment is associated with high rates of dependency, which are more severe after clipping compared with coiling. To determine whether ischemic injury might account for these differences, we characterized cerebral infarction burden, infarction patterns, and patient outcomes after surgical or endovascular treatment of ruptured anterior communicating artery aneurysms. MATERIALS AND METHODS: We performed a retrospective cohort study of consecutive patients with ruptured anterior communicating artery aneurysms. Patient data and neuroimaging studies were reviewed. A propensity score for outcome measures was calculated to account for the nonrandom assignment to treatment. Primary outcome was the frequency of frontal lobe and striatum ischemic injury. Secondary outcomes were patient mortality and clinical outcome at discharge and at 3 months. RESULTS: Coiled patients were older (median, 55 versus 50 years; P = .03), presented with a worse clinical status (60% with Hunt and Hess Score >2 versus 34% in clipped patients; P = .02), had a higher modified Fisher grade (P = .01), and were more likely to present with intraventricular hemorrhage (78% versus 56%; P = .03). Ischemic frontal lobe infarction (OR, 2.9; 95% CI, 1.1-8.4; P = .03) and recurrent artery of Heubner infarction (OR, 20.9; 95% CI, 3.5-403.7; P < .001) were more common in clipped patients. Clipped patients were more likely to be functionally dependent at discharge (OR, 3.2; P = .05) compared with coiled patients. Mortality and clinical outcome at 3 months were similar between coiled and clipped patients. CONCLUSIONS: Frontal lobe and recurrent artery of Heubner infarctions are more common after surgical clipping of ruptured anterior communicating artery aneurysms, and are associated with poorer clinical outcomes at discharge.

Cerebral Angiography for Evaluation of Patients with CT Angiogram-Negative Subarachnoid Hemorrhage: An 11-Year Experience.

BACKGROUND AND PURPOSE: CT angiography is increasingly used to evaluate patients with nontraumatic subarachnoid hemorrhage given its high sensitivity for aneurysms. We investigated the yield of digital subtraction angiography among patients with SAH or intraventricular hemorrhage and a negative CTA. MATERIALS AND METHODS: An 11-year, single-center retrospective review of all consecutive patients with CTA-negative SAH was performed. Noncontrast head CT, CTA, DSA, and MR imaging studies were reviewed by 2 experienced interventional neuroradiologists and 1 neuroradiologist. RESULTS: Two hundred thirty patients (mean age, 54 years; 51% male) with CTA-negative SAH were identified. The pattern of SAH was diffuse (40%), perimesencephalic (31%), sulcal (31%), isolated IVH (6%), or identified by xanthochromia (7%). Initial DSA yield was 13%, including vasculitis/vasculopathy (7%), aneurysm (5%), arteriovenous malformation (0.5%), and dural arteriovenous fistula (0.5%). An additional 6 aneurysms/pseudoaneurysms (4%) were identified by follow-up DSA, and a single cavernous malformation (0.4%) was identified by MRI. No cause of hemorrhage was identified in any patient presenting with isolated intraventricular hemorrhage or xanthochromia. Diffuse SAH was due to aneurysm rupture (17%); perimesencephalic SAH was due to aneurysm rupture (3%) or vasculitis/vasculopathy (1.5%); and sulcal SAH was due to vasculitis/vasculopathy (32%), arteriovenous malformation (3%), or dural arteriovenous fistula (3%). CONCLUSIONS: DSA identifies vascular pathology in 13% of patients with CTA-negative SAH. Aneurysms or pseudoaneurysms are identified in an additional 4% of patients by repeat DSA following an initially negative DSA. All patients with CT-negative SAH should be considered for DSA. The pattern of SAH may suggest the cause of hemorrhage, and aneurysms should specifically be sought with diffuse or perimesencephalic SAH.