Background and Purpose: Intracranial hemorrhage has been observed in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (COVID-19), but the clinical, imaging, and pathophysiological features of intracranial bleeding during COVID-19 infection remain poorly characterized. This study describes clinical and imaging characteristics of patients with COVID-19 infection who presented with intracranial bleeding in a European multicenter cohort. Methods: This is a multicenter retrospective, observational case series including 18 consecutive patients with COVID-19 infection and intracranial hemorrhage. Data were collected from February to May 2020 at five designated European special care centers for COVID-19. The diagnosis of COVID-19 was based on laboratory-confirmed diagnosis of SARS-CoV-2. Intracranial bleeding was diagnosed on computed tomography (CT) of the brain within one month of the date of COVID-19 diagnosis. The clinical, laboratory, radiologic, and pathologic findings, therapy and outcomes in COVID-19 patients presenting with intracranial bleeding were analyzed. Results: Eighteen patients had evidence of acute intracranial bleeding within 11 days (IQR 9–29) of admission. Six patients had parenchymal hemorrhage (33.3%), 11 had subarachnoid hemorrhage (SAH) (61.1%), and one patient had subdural hemorrhage (5.6%). Three patients presented with intraventricular hemorrhage (IVH) (16.7%). Conclusion: This study represents the largest case series of patients with intracranial hemorrhage diagnosed with COVID-19 based on key European countries with geospatial hotspots of SARS-CoV-2. Isolated SAH along the convexity may be a predominant bleeding manifestation and may occur in a late temporal course of severe COVID-19.

Our aim is to predict possible gross total and subtotal resections of skull meningiomas from pre-treatment T1 post contrast MR-images using radiomics and machine learning in a representative patient cohort. We analyse the accuracy of our model predictions depending on the tumor location within the skull and the postoperative tumor volume. In this retrospective, IRB-approved study, image segmentation of the contrast enhancing parts of the tumor was semi-automatically performed using the 3D Slicer open-source software platform. Imaging data were split into training data and independent test data at random. We extracted a total of 107 radiomic features by hand-delineated regions of interest on T1 post contrast MR images. Feature preselection and model construction were performed with eight different machine learning algorithms. Each model was estimated 100 times on new training data and then tested on a previously unknown, independent test data set to avoid possible overfitting. Our cohort included 138 patients. A gross total resection of the meningioma was performed in 107 cases and a subtotal resection in the remaining 31 cases. Using the training data, the mean area under the curve (AUC), mean accuracy, mean kappa, mean sensitivity and mean specificity were 0.901, 0.875, 0.629, 0.675 and 0.933 respectively. We obtained very similar results with the independent test data: mean AUC = 0.900, mean accuracy = 0.881, mean kappa = 0.644, mean sensitivity = 0.692 and mean specificity = 0.936. Thus, our model exposes good and stable predictive performance with both training and test data. Our radiomics approach shows that with machine learning algorithms and comparatively few explanatory factors such as the location of the tumor within the skull as well as its shape, it is possible to make accurate predictions about whether a meningioma can be completely resected by surgery. Complete resections and resections with larger postoperative tumor volumes can be predicted with very high accuracy. However, cases with very small postoperative tumor volumes are comparatively difficult to predict correctly.

Objective: In rare cases, Lyme neuroborreliosis (LNB) can induce cerebral vasculitis leading to severe stenosis of the cerebral vasculature and consecutive ischemia. Therapy is based on anti-biotic treatment of the tick-borne disease, whereas interventional therapeutic options have not been assessed yet. Material and Methods: We report on a patient with LNB and concomitant stenoses and progressive and fatal vasculitis of the cerebral vessels despite all therapeutic efforts by the departments of neurology and interventional neuroradiology. In this context, we also conducted a literature review on endovascular treatment of LNB-associated cerebral ischemia. Results: A 52-year-old female presented with transient neglect and psychomotor slowdown (initial NIHSS = 0). MRI and serology led to the diagnosis of basal meningitis due to LNB with vasculitis of cerebral arteries. Despite immediate treatment with antibiotics and steroids, neurologic deterioration (NIHSS 8) led to an emergency angiography on day 2 after admission. Hemodynamically relevant stenoses of the MCA were treated via spasmolysis and PTA, leading to almost complete neurological recovery. Despite intensified medical treatment, the vasculitis progressed and could only be transiently ameliorated via repetitive spasmolysis. On day 19, she again presented with significant neurologic deterioration (NIHSS 9), and PTA and stenting of the nearly occluded MCA were performed with a patent vessel, initially without hemorrhagic complications. Despite all therapeutic efforts and preserved stent perfusion, vasculitis worsened and the concurrent occurrence of subdural hemorrhage led to the death of the patient. Conclusion: Neuroradiological interventions, i.e., spasmolysis, PTA, and, if necessary, stenting, can and should be considered in cases of LNB-induced vasculitis and stroke that are refractory to best medical treatment alone. Key point: Neuroradiological interventions can be considered in patients with vascular complications of Lyme neuroborreliosis as an additional extension of the primary drug therapy.

For patients with symptomatic acute occlusions of the internal carotid artery below the circle of Willis, endovascular and best medical treatment were both effective and safe therapeutic options.

The aim of this study was to develop a magnetic resonance imaging (MRI) based radiomics model to predict mitosis cycles in intracranial meningioma grading prior to surgery. Preoperative contrast-enhanced T1-weighted (T1CE) cerebral MRI data of 167 meningioma patients between 2015 and 2020 were obtained, preprocessed and segmented using the 3D Slicer software and the PyRadiomics plugin. In total 145 radiomics features of the T1CE MRI images were computed. The criterion on the basis of which the feature selection was made is whether the number of mitoses per 10 high power field (HPF) is greater than or equal to zero. Our analyses show that machine learning algorithms can be used to make accurate predictions about whether the number of mitoses per 10 HPF is greater than or equal to zero. We obtained our best model using Ridge regression for feature pre-selection, followed by stepwise logistic regression for final model construction. Using independent test data, this model resulted in an AUC (Area under the Curve) of 0.8523, an accuracy of 0.7941, a sensitivity of 0.8182, a specificity of 0.7500 and a Cohen’s Kappa of 0.5576. We analyzed the performance of this model as a function of the number of mitoses per 10 HPF. The model performs well for cases with zero mitoses as well as for cases with more than one mitosis per 10 HPF. The worst model performance (accuracy = 0.6250) is obtained for cases with one mitosis per 10 HPF. Our results show that MRI-based radiomics may be a promising approach to predict the mitosis cycles in intracranial meningioma prior to surgery. Specifically, our approach may offer a non-invasive means of detecting the early stages of a malignant process in meningiomas prior to the onset of clinical symptoms.

Objective: Mechanical thrombectomy (MT) has become the standard treatment for acute ischemic stroke (AIS) with large vessel occlusion (LVO). First-pass (FP) reperfusion of the occluded vessel and fewer passes with stent retrievers show improvement in functional outcomes in stroke patients, while higher numbers of passes are associated with higher complication rates and worse outcomes. Studies indicate that a larger size of the stent-retriever is associated with a higher rate of first-pass reperfusion and improved clinical outcomes. In this retrospective study, we investigated the clinical performance of a recently developed and one of the largest stent-retrievers available in the treatment of LVO (pRESET 6-50, phenox GmbH, Bochum).Materials and methods: All consecutive patients with ischemic stroke due to proximal large vessel occlusion treated with MT using the pRESET 6-50 stent-retriever in two tertiary stroke centers between 09/2021 and 07/2022 were included in this study. The reperfusion rate after MT was quantified by the modified thrombolysis in cerebral infarction (mTICI) score, and functional neurological outcome was evaluated with the National Institutes of Health Stroke Scale (NIHSS) score and the major early neurological recovery (mENR) rate after 24 h. Successful FP reperfusion was defined as mTICI ≥ 2b. Successful and complete reperfusion were defined as mTICI ≥ 2b and mTICI ≥ 2c, respectively.Results: In total, 98 patients (52 men and 46 women) with a median age of 75 (range 25–95 years) were included. A total of 70 (72%) patients presented with an occlusion of the middle cerebral artery (MCA) in the M1 segment, 6 (6%) patients with an occlusion of the M2 segment, 17 (17%) patients with an occlusion of the internal carotid artery (ICA), and 5 (5%) patients with an occlusion of the obstructed basilar artery (BA). Successful FP reperfusion was achieved in 58 patients (62%). Successful and complete reperfusion were achieved in 95 (97%) and 82 (83%) patients, respectively. The median National Institutes of Health Stroke Scale (NIHSS) in all treated patients improved from 17 to 7.5. Major early neurological recovery (mENR) was observed in 34 patients (35.1%).Conclusion: MT with the pRESET 6-50 stent-retriever achieves high successful first-pass and final reperfusion rates in patients with AIS and LVO. The results of this study support the thesis to use large-format stent-retriever in proximal vessel occlusion MT whenever feasible in order to improve high FP and final reperfusion rate, which are known predictors of good clinical outcome.