No abstract

Objective Aging is a major risk factor for numerous neurological disorders, and the mechanisms underlying brain aging remain elusive. Recent animal studies demonstrated a tight relationship between impairment of the glymphatic pathway, meningeal lymphatic vessels, and aging. However, the relationship in the human brain remains uncertain. Methods In this observational cohort study, patients underwent magnetic resonance imaging before and at multiple time points after intrathecal administration of a contrast agent. Head T1‐weighted imaging was performed to assess the function of the glymphatic pathway and head high‐resolution T2–fluid attenuated inversion recovery imaging to visualize putative meningeal lymphatic vessels (pMLVs). We measured the signal unit ratio (SUR) of 6 locations in the glymphatic pathway and pMLVs, defined the percentage change in SUR from baseline to 39 hours as the clearance of the glymphatic pathway and pMLVs, and then analyzed their relationships with aging. Results In all patients (N = 35), the SUR of the glymphatic pathway and pMLVs changed significantly after intrathecal injection of the contrast agent. The clearance of both the glymphatic pathway and pMLVs was related to aging (all p < 0.05). The clearance of pMLVs was significantly related to the clearance of the glymphatic pathway (all p < 0.05), and the clearance of the glymphatic pathway was significantly faster in patients with early filling of pMLVs than those with late filling (all p < 0.05). Interpretation We revealed that both the glymphatic pathway and pMLVs might be impaired in the aging human brain through the novel, clinically available method to simultaneously visualize their clearance. Our findings also support that in humans, pMLVs are the downstream of the glymphatic pathway. Ann Neurol 2020;87:357–369

To develop a quantitative assessment of collateral perfusion at CT and to investigate its value in the prediction of outcome in patients with acute ischemic stroke (AIS). Materials and Methods:This retrospective study reviewed data from consecutive patients with AIS and an occluded M1 segment of the middle cerebral artery who underwent pretreatment perfusion CT between May 2009 and August 2017. The maximum cerebral blood flow (CBF) of collateral vessels (cCBF max ) within the Sylvian fissure was calculated for each patient. Good outcome was defined as a 90-day modified Rankin scale score of 0-2. Multivariable logistic regression analysis was used to determine the relationship between cCBF max and (a) hemorrhagic transformation and (b) clinical outcome. Results:The final analysis included 204 patients (median age, 73 years; interquartile range, 62-80 years; 82 [40.2%] women). Multivariable logistic regression analysis showed that higher cCBF max was an independent predictor for (a) a lower risk of hemorrhagic transformation (odds ratio [OR], 0.99; 95% confidence interval [CI]: 0.98, 1.00; P = .009) after adjusting for baseline National Institutes of Health Stroke Scale (NIHSS), endovascular thrombectomy, baseline infarct core volume, and recanalization and (b) better outcome (OR, 1.02; 95% CI: 1.01, 1.03; P = .001) after adjusting for age, baseline NIHSS score, endovascular thrombectomy, hypertension, baseline infarct core volume, and recanalization, respectively. Conclusion:The measurement of maximum cerebral blood flow of collateral vessels within the Sylvian fissure is a feasible quantitative collateral assessment at perfusion CT. Maximum cerebral blood flow of collateral vessels was associated with clinical outcome in patients with acute ischemic stroke.

BACKGROUND AND PURPOSE: Parenchymal hemorrhage is a severe complication following mechanical recanalization in patients with acute ischemic stroke with large-vessel occlusion. This study aimed to assess whether the metallic hyperdensity sign on noncontrast CT performed immediately after mechanical thrombectomy can predict parenchymal hemorrhage at 24 hours. MATERIALS AND METHODS: We included consecutive patients with acute ischemic stroke with large-vessel occlusion who underwent noncontrast CT immediately after mechanical thrombectomy between January 2014 and September 2018. The metallic hyperdensity sign was defined as a nonpetechial intracerebral hyperdense lesion (diameter, Ն1 cm) in the basal ganglia and a maximum CT density of Ͼ90 HU. The sensitivity, specificity, and positive and negative predictive values of the metallic hyperdensity sign in predicting parenchymal hemorrhage were calculated. RESULTS: A total of 198 patients were included. The metallic hyperdensity sign was found in 59 (29.7%) patients, and 51 (25.7%) patients had parenchymal hemorrhage at 24 hours. Patients with the metallic hyperdensity sign are more likely to have parenchymal hemorrhage than those without it (76.3% versus 4.3%, P Ͻ .001). The sensitivity, specificity, positive predictive value, and negative predictive value of the metallic hyperdensity sign in predicting parenchymal hemorrhage were 88.2%, 90.5%, 76.3%, and 95.7%, respectively. CONCLUSIONS: The presence of the metallic hyperdensity sign on noncontrast CT performed immediately after mechanical thrombectomy in patients with large-vessel occlusion could predict the occurrence of parenchymal hemorrhage at 24 hours, which might be helpful in postinterventional management within 24 hours after mechanical thrombectomy.

Background: Large core is associated with poor outcome in acute ischemic stroke (AIS) patients. It is unclear whether endovascular treatment (EVT) could bring benefits to patients with core volume ≥70 ml before treatment. We aimed to compare the impact of EVT with intravenous thrombolysis (IVT) on the outcome in patients with core volume ≥70 ml.Methods: We included consecutive anterior circulation AIS patients who underwent MR or CT perfusion within 6 h post stroke onset, which revealed a core ≥70 ml before reperfusion therapy. Good outcome was defined by modified Rankin Scale of 0 to 2 at 90-day. Reperfusion was defined as a reduction in hypoperfusion volume of ≥70% between baseline and 24 h.Results: One hundred four patients were included. Among them, 76 received IVT only, and 28 received EVT. After adjusting for age, NIHSS score, baseline core volume and onset to imaging time, patients in EVT group were more likely to achieve good outcome compared to IVT patients (OR, 3.875; 95% Cl 1.068–14.055, p = 0.039). More patients in EVT group achieved recanalization (84.0 vs. 58.5%, p = 0.027) and reperfusion (66.7 vs. 33.3%, p = 0.010) than in IVT group. Reperfusion also independently predicted good outcome (OR, 7.718; 95% Cl 1.713-34.772, p = 0.008). All patients with good outcome achieved recanalization at 24 h.Conclusions: Our data indicated that patients with core volume ≥70 ml might still benefit from EVT, which was related to its high reperfusion rate.

Thrombus permeability assessed on dynamic CTA could be a better predictor of outcome after reperfusion therapy than that assessed on conventional single-phase CTA.

Background: Identifying large vessel occlusion (LVO) patients in the prehospital triage stage to avoid unnecessary and costly delays is important but still challenging. We aim to develop an artificial neural network (ANN) algorithm to predict LVO using prehospital accessible data including demographics, National Institutes of Health Stroke Scale (NIHSS) items and vascular risk factors.Methods: Consecutive acute ischemic stroke patients who underwent CT angiography (CTA) or time of flight MR angiography (TOF-MRA) and received reperfusion therapy within 8 h from symptom onset were included. The diagnosis of LVO was defined as occlusion of the intracranial internal carotid artery (ICA), M1 and M2 segments of the middle cerebral artery (MCA) and basilar artery on CTA or TOF-MRA before treatment. Patients with and without LVO were randomly selected at a 1:1 ratio. The ANN model was developed using backpropagation algorithm, and 10-fold cross-validation was used to validate the model. The comparison of diagnostic parameters between the ANN model and previously established prehospital prediction scales were performed.Results: Finally, 300 LVO and 300 non-LVO patients were randomly selected for the training and validation of the ANN model. The mean Youden index, sensitivity, specificity and accuracy of the ANN model based on the 10-fold cross-validation analysis were 0.640, 0.807, 0.833 and 0.820, respectively. The area under the curve (AUC), Youden index and accuracy of the ANN model were all higher than other prehospital prediction scales.Conclusions: The ANN can be an effective tool for the recognition of LVO in the prehospital triage stage.

Four dimensional-computed tomography angiography is a useful noninvasive technique to identify ICA-PO. Patients with ICA-PO are prone to undergo poor outcome from reperfusion therapy, especially when reperfusion is not achieved.