Background and Purpose— As a reliable scoring system to detect the risk of symptomatic intracerebral hemorrhage after thrombectomy for ischemic stroke is not yet available, we developed a nomogram for predicting symptomatic intracerebral hemorrhage in patients with large vessel occlusion in the anterior circulation who received bridging of thrombectomy with intravenous thrombolysis (training set), and to validate the model by using a cohort of patients treated with direct thrombectomy (test set). Methods— We conducted a cohort study on prospectively collected data from 3714 patients enrolled in the IER (Italian Registry of Endovascular Stroke Treatment in Acute Stroke). Symptomatic intracerebral hemorrhage was defined as any type of intracerebral hemorrhage with increase of ≥4 National Institutes of Health Stroke Scale score points from baseline ≤24 hours or death. Based on multivariate logistic models, the nomogram was generated. We assessed the discriminative performance by using the area under the receiver operating characteristic curve. Results— National Institutes of Health Stroke Scale score, onset-to-end procedure time, age, unsuccessful recanalization, and Careggi collateral score composed the IER-SICH nomogram. After removing Careggi collateral score from the first model, a second model including Alberta Stroke Program Early CT Score was developed. The area under the receiver operating characteristic curve of the IER-SICH nomogram was 0.778 in the training set (n=492) and 0.709 in the test set (n=399). The area under the receiver operating characteristic curve of the second model was 0.733 in the training set (n=988) and 0.685 in the test set (n=779). Conclusions— The IER-SICH nomogram is the first model developed and validated for predicting symptomatic intracerebral hemorrhage after thrombectomy. It may provide indications on early identification of patients for more or less postprocedural intensive management.

The main focus of Coronavirus disease 2019 (COVID-19) infection is pulmonary complications through virus-related neurological manifestations, ranging from mild to severe, such as encephalitis, cerebral thrombosis, neurocognitive (dementia-like) syndrome, and delirium. The hospital screening procedures for quickly recognizing neurological manifestations of COVID-19 are often complicated by other coexisting symptoms and can be obscured by the deep sedation procedures required for critically ill patients. Here, we present two different case-reports of COVID-19 patients, describing neurological complications, diagnostic imaging such as olfactory bulb damage (a mild and unclear underestimated complication) and a severe and sudden thrombotic stroke complicated with hemorrhage with a low-level cytokine storm and respiratory symptom resolution. We discuss the possible mechanisms of virus entrance, together with the causes of COVID-19-related encephalitis, olfactory bulb damage, ischemic stroke, and intracranial hemorrhage.

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Purpose To compare the diagnostic accuracy (ACC) in the detection of acute posterior circulation strokes between qualitative evaluation of software-generated colour maps and automatic assessment of CT perfusion (CTP) parameters. Methods Were retrospectively collected 50 patients suspected of acute posterior circulation stroke who underwent to CTP (GE "Lightspeed", 64 slices) within 24 h after symptom onset between January 2016 and December 2018. The Posterior circulation-Acute Stroke Prognosis Early CT Score (pc-ASPECTS) was used for quantifying the extent of ischaemic areas on non-contrast (NC)CT and colour-coded maps generated by CTP4 (GE) and RAPID (iSchemia View) software. Final pc-ASPECTS was calculated on follow-up NCCT and/or MRI (Philips Intera 3.0 T or Philips Achieva Ingenia 1.5 T). RAPID software also elaborated automatic quantitative mismatch maps. Results By qualitative evaluation of colour-coded maps, MTT-CTP4D and Tmax-RAPID showed the highest sensitivity (SE) (88.6% and 90.9%, respectively) and ACC (84% and 88%, respectively) compared with the other perfusion parameters (CBV, CBF). Baseline NCCT and CBF provided by RAPID quantitative perfusion mismatch maps had the lowest SE (29.6% and 6.8%, respectively) and ACC (38% and 18%, respectively). CBF and Tmax assessment provided by quantitative RAPID perfusion mismatch maps showed significant lower SE and ACC than qualitative evaluation. No significant differences were found between the pc-ASPECTSs assessed on colour-coded MTT and Tmax maps neither between the scores assessed on colourcoded CBV-CTP4D and CBF-RAPID maps. Conclusion Qualitative analysis of colour-coded maps resulted more sensitive and accurate in the detection of ischaemic changes than automatic quantitative analysis.