Roadmap Guided Direct Percutaneous Vertebral Artery Puncture for Mechanical Thrombectomy of Acute Basilar Artery Occlusion: A Technical Case Report and Review of the Literature

Access techniques for mechanical thrombectomy normally include percutaneous puncture of the common femoral or, more recently, the radial artery. Although target vessel catheterization may frequently not be devoid of difficulties via both routes, the vast majority of mechanical thrombectomy (MT) cases can be successfully managed. However, in a significant minority of cases, a stable target vessel access cannot be reached resulting in futile recanalization procedures and detrimental outcomes for the patients. As such, in analogy to direct carotid puncture for anterior circulation MT, direct vertebral artery (VA) puncture (DVP) is a direct cervical approach, which can constitute the only feasible access to the posterior circulation in highly selected cases. So far, due to the rarity of DVP, only anecdotal evidence from isolated case reports is available and this approach raises concerns with regard to safety issues, feasibility, and technical realization. We present a case in which bail-out access to the posterior circulation was successfully obtained through a roadmap-guided lateral direct puncture of the V2 segment of the cervical VA and give an overview of technical nuances of published DVP approaches for posterior circulation MT

Volumetric accuracy of different imaging modalities in acute intracerebral hemorrhage

Background: Follow-up imaging in intracerebral hemorrhage is not standardized and radiologists rely on different imaging modalities to determine hematoma growth. This study assesses the volumetric accuracy of different imaging modalities (MRI, CT angiography, postcontrast CT) to measure hematoma size. Methods: 28 patients with acute spontaneous intracerebral hemorrhage referred to a tertiary stroke center were retrospectively included between 2018 and 2019. Inclusion criteria were (1) spontaneous intracerebral hemorrhage (supra- or infratentorial), (2) noncontrast CT imaging performed on admission, (3) follow-up imaging (CT angiography, postcontrast CT, MRI), and (4) absence of hematoma expansion confirmed by a third cranial image within 6 days. Two independent raters manually measured hematoma volume by drawing a region of interest on axial slices of admission noncontrast CT scans as well as on follow-up imaging (CT angiography, postcontrast CT, MRI) using a semi-automated segmentation tool (Visage image viewer; version 7.1.10). Results were compared using Bland-Altman plots. Results: Mean admission hematoma volume was 18.79 +/- 19.86 cc. All interrater and intrarater intraclass correlation coefficients were excellent (1; IQR 0.98-1.00). In comparison to hematoma volume on admission noncontrast CT volumetric measurements were most accurate in patients who received postcontrast CT (bias of - 2.47%, SD 4.67: n = 10), while CT angiography often underestimated hemorrhage volumes (bias of 31.91%, SD 45.54; n = 20). In MRI sequences intracerebral hemorrhage volumes were overestimated in T2* (bias of - 64.37%, SD 21.65; n = 10). FLAIR (bias of 6.05%, SD 35.45; n = 13) and DWI (bias of-14.6%, SD 31.93; n = 12) over- and underestimated hemorrhagic volumes. Conclusions: Volumetric measurements were most accurate in postcontrast CT while CT angiography and MRI sequences often substantially over- or underestimated hemorrhage volumes

Cerebrovascular Events in Suspected Sepsis: Retrospective Prevalence Study in Critically Ill Patients Undergoing Full-Body Computed Tomography

Purpose: This study aimed at retrospectively evaluating full-body computed tomography (CT) examinations for the prevalence of cerebrovascular events in patients with suspected sepsis treated in the intensive care unit (ICU). Methods: All full-body CT examinations, i.e., both cranial CT (cCT) and body CT including chest, abdomen and pelvis, for focus search in septic patients over a 12-months period were identified from three ICUs, using full-text search. From this retrospective cohort, we fully analyzed 278 cCT examinations for the occurrence of acute cerebral findings. All acute cerebrovascular events were independently reviewed by two blinded readers. Clinical and laboratory findings were extracted. The data were statistically analyzed using contingency tests. Results: In our population of patients with suspected sepsis, 10.8% (n = 30/278) were identified to have major cerebral events, including 7.2% (n = 20/278) major cerebrovascular events and 4.3% (n = 12/278) generalized parenchymal damage. 13.4% (n = 22/163) of patients with a severe coma as compared with non-severe coma, 4.4% (n = 3/68), showed a major cerebral event (p = 0.04). Patients referred from the cardiology/nephrology ICU ward showed major cerebral events in 16.3% (n = 22/135), as compared with 4.9% (n = 3/61) in patients from pulmonary ICU and 6.1% (n = 5/82) major cerebral events with surgical referral (p = 0.02). Conclusion: Our study provides further evidence that septic patients may suffer from cerebral events with relevance to their prognosis. Severe coma and the referring ward were associated with acute cerebral conditions. Full-body CT has the advantage of both detecting of septic foci and possibly identifying ischemic or hemorrhagic stroke in this vulnerable patient population

Clinical and Imaging Characteristics in Patients with SARS-CoV-2 Infection and Acute Intracranial Hemorrhage

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

Qualitative and quantitative markers of computed tomography for the prediction of clinical outcome in acute ischemic and hemorrhagic stroke

Patienten mit einem akuten, ischämischen Schlaganfall haben durch den Durchbruch und Paradigmenwechsel hin zur endovaskulären Therapie eine deutliche Verringerung von Morbidität und Mortalität entwickelt. Dennoch unterliegen viele Patienten, trotz erfolgreicher Rekanalisation durch eine MT, einer hohen interindividuellen Variabilität im klinischen outcome. Ziel ist es daher weitere Subgruppen zu identifizieren, um die Therapieeffekte einer MT einer möglichst großen Patientenpopulation zugänglich zu machen. Mit der Einführung des Biomarkers NWU gelang erstmals eine zuverlässige Messung des ischämischen Hirnödems durch eine Quantifizierung des prozentualen Wassereinstromes in das Infarktgewebe. Ziel der Originalarbeit 1 und 2 war es daher NWU als potentiellen Prädiktionsmarker für klinische Endpunkte des ischämischen Schlaganfalls, in einer Subgruppe von Patienten mit erfolgreicher MT, näher zu evaluieren. Neben klinischen Parametern, wurden neben NWU ebenfalls weitere qualitative und quantitative, etablierte Bildgebungsmarker erhoben (z.B. ASPECTS, Kollateralstatus). Für das frühe NWU in der initialen Bildgebung wurde in uni- und multivariaten Modellen gezeigt, dass es sowohl etablierten Marker der CT Bildgebung (ASPECTS) als auch der Klinik (NIHSS) in der diagnostischen Aussagekraft für ein schlechtes outcome überlegen ist. Zudem könnte der frühe Nettoeinstrom von zytotoxischem Ödem die hohe Intervariabilität des klinischen outcome, trotz ähnlicher Infarktausdehnung und -volumina sowie Zeitfenster, erklären (accelerated ‘‘tissue clock’’ desynchronized with the real ‘‘time clock’’). Trotz der kontinuierlichen Erfolge des Therapieeffektes der MT aus der HERMES, sowie zuletzt der DAWN und DEFUSE-3 Studie, bleibt die ICH die gefürchtetste Komplikation jeder MT und bleibt ein wichtiger Endpunkt großer RCTs. So haben die Ergebnisse der Originalarbeit 3 eine überlegene prognostische Aussagekraft von NWU gegenüber etablierten Bildgebungsmarkern (ASPECTS und Kollateralstatus) sowie klinischen Markern (NIHSS) gezeigt. Die Klassifikation der Blutungsereignisse nach den jüngsten, internationalen Konsensusempfehlungen der Heidelberger Blutungsklassifikation, weisen zusätzlich auf die methodische Stärke der vorliegenden Originalarbeit 3 und 4 hin. Im direkten Vergleich mit vorherigen Klassifikationen (z.B. ECASS III) zeigte die Heidelberger Blutungsklassifikation eine höhere Sensitivität für die Bestimmung einer sICH. Der genaue prognostische Wert der aICH auf das klinische outcome bleibt dennoch aktuell unzureichend geklärt. Die Ergebnisse in Originalarbeit 4 stellen zudem eindeutig die Langzeitauswirkungen einer aICH nach erfolgreicher MT auf das funktionelle outcome dar und untersucht deren Risikofaktoren. Ferner wurden anhand der Ergebnisse klinisch-anwendbare, prognostische Modelle etabliert und evaluiert. Denn insbesondere beim ischämischen Schlaganfall gilt es den therapierelevanten Nutzen von prognostischen Modellen durch eine stetige Verbesserung von Behandlungsstandards und Fortentwicklung therapeutischer Interventionen voranzutreiben. Beim hämorrhagischen Schlaganfall hat sich, anders als beim ischämischen Schlaganfall, bisher kein therapeutischer Durchbruch ergeben, weshalb dieses Patientenkollektiv weiterhin hohe Mortalitäten und Morbiditäten aufweist. Neben der Erforschung neuer medikamentöser und therapeutischer Angriffspunkte der sekundären Hirnschädigung nach einer ICH, liegt unverändert der wissenschaftliche Fokus auf einer frühen Detektion der potentiell therapeutisch-reversiblen Expansion einer ICH. Hierbei haben insbesondere Marker der multimodalen CT an Bedeutung in der Detektion der HE gewonnen. So wird das Spot Sign der CTA bereits in großen prospektiven RCTs zur Patientenstratifizierung eingesetzt. Angesichts der breiten Verfügbarkeit von NCCT Markern erscheint dennoch die Stratifizierung des Expansionsrisikos mit NCCT-Markern als eine vielversprechende, alternative Strategie. Ziel der Habilitationsschrift war es daher den prognostischen Nutzen und den Grad der Interaktion der Marker näher zu untersuchen, um zukünftig auch akkurate und universell gültige Modelle erstellen und deren Einsetzbarkeit in künftigen RCTs bahnen zu können. Hierfür wurden in einem großen multizentrischen Studiendesign (Originalarbeit 5) fünf etablierte NCCT Marker und das Spot Sign für ihre Verteilung (1) in der Gesamtkohorte, (2) in Abhängigkeit von einem guten bzw. schlechten outcome, (3) in Abhängigkeit vom Auftreten mehrerer Zeichen, sowie (4) für ihre Inter- und Intraraterreliabilität untersucht. Die Originalarbeit 6 hat erstmals die Verteilung der Marker bei einem gemeinsamen Auftreten und deren jeweiligen individuellen Einfluss auf das klinische outcome beschrieben. Die klinische Relevanz dieser Ergebnisse zeigt der Einzug der Ergebnisse in die internationalen Konsensusempfehlungen von Morotti et al. Die pathophysiologischen Mechanismen, die den NCCT Markern zugrunde liegen, bleiben unzureichend geklärt. Dennoch gilt es weitgehend gesichert, dass ein Großteil der dichtemorphologischen Charakteristika der NCCT Marker auf verschiedenen Stadien der Koagulation des Blutes beruhen. Doch Unterschiede in der Distribution der NCCT Marker und deren potentiell unterschiedlichen Einfluss auf das klinische outcome, sind bei Patienten unter oraler Antikoagulation erstmals in der Originalarbeit 7 untersucht worden. Prognostische Modelle der Schlaganfalltherapie werden auch zukünftig unverändert eine hohe Relevanz behalten. Die vorgestellten Originalarbeiten dieser Habilitationsschrift evaluieren hierfür quantitative und qualitative Prädiktoren für das klinische outcome nach akutem ischämischem und hämorrhagischem Schlaganfall während der Hospitalisierungs- und Verlaufsphase. Sie definieren somit Studien-Subpopulationen und potentielle, neue Therapieziele, die anschließend prospektiv untersucht werden können

Improved multi-parametric prediction of tissue outcome in acute ischemic stroke patients using spatial features.

INTRODUCTION:In recent years, numerous methods have been proposed to predict tissue outcome in acute stroke patients using machine learning methods incorporating multiparametric imaging data. Most methods include diffusion and perfusion parameters as image-based parameters but do not include any spatial information although these parameters are spatially dependent, e.g. different perfusion properties in white and gray brain matter. This study aims to investigate if including spatial features improves the accuracy of multi-parametric tissue outcome prediction. MATERIALS AND METHODS:Acute and follow-up multi-center MRI datasets of 99 patients were available for this study. Logistic regression, random forest, and XGBoost machine learning models were trained and tested using acute MR diffusion and perfusion features and known follow-up lesions. Different combinations of atlas coordinates and lesion probability maps were included as spatial information. The stroke lesion predictions were compared to the true tissue outcomes using the area under the receiver operating characteristic curve (ROC AUC) and the Dice metric. RESULTS:The statistical analysis revealed that including spatial features significantly improves the tissue outcome prediction. Overall, the XGBoost and random forest models performed best in every setting and achieved state-of-the-art results regarding both metrics with similar improvements achieved including Montreal Neurological Institute (MNI) reference space coordinates or voxel-wise lesion probabilities. CONCLUSION:Spatial features should be integrated to improve lesion outcome prediction using machine learning models

Correction: Improved multi-parametric prediction of tissue outcome in acute ischemic stroke patients using spatial features.

[This corrects the article DOI: 10.1371/journal.pone.0228113.]

Localized prediction of tissue outcome in acute ischemic stroke patients using diffusion- and perfusion-weighted MRI datasets.

BackgroundAn accurate prediction of tissue outcome in acute ischemic stroke patients is of high interest for treatment decision making. To date, various machine learning models have been proposed that combine multi-parametric imaging data for this purpose. However, most of these machine learning models were trained using voxel information extracted from the whole brain, without taking differences in susceptibility to ischemia into account that exist between brain regions. The aim of this study was to develop and evaluate a local tissue outcome prediction approach, which makes predictions using locally trained machine learning models and thus accounts for regional differences.Material and methodsMulti-parametric MRI data from 99 acute ischemic stroke patients were used for the development and evaluation of the local tissue outcome prediction approach. Diffusion (ADC) and perfusion parameter maps (CBF, CBV, MTT, Tmax) and corresponding follow-up lesion masks for each patient were registered to the MNI brain atlas. Logistic regression (LR) and random forest (RF) models were trained employing a local approach, which makes predictions using models individually trained for each specific voxel position using the corresponding local data. A global approach, which uses a single model trained using all voxels of the brain, was used for comparison. Tissue outcome predictions resulting from the global and local RF and LR models, as well as a combined (hybrid) approach were quantitatively evaluated and compared using the area under the receiver operating characteristic curve (ROC AUC), the Dice coefficient, and the sensitivity and specificity metrics.ResultsStatistical analysis revealed the highest ROC AUC and Dice values for the hybrid approach. With 0.872 (ROC AUC; LR) and 0.353 (Dice; RF), these values were significantly higher (p ConclusionThe results of this study suggest that using locally trained machine learning models can lead to better lesion outcome prediction results compared to a single global machine learning model trained using all voxel information independent of the location in the brain

Multilesion Segmentations in Patients with Intracerebral Hemorrhage: Reliability of ICH, IVH and PHE Masks

Background and Purpose: Fully automated methods for segmentation and volume quantification of intraparenchymal hemorrhage (ICH), intraventricular hemorrhage extension (IVH), and perihematomal edema (PHE) are gaining increasing interest. Yet, reliabilities demonstrate considerable variances amongst each other. Our aim was therefore to evaluate both the intra- and interrater reliability of ICH, IVH and PHE on ground-truth segmentation masks. Methods: Patients with primary spontaneous ICH were retrospectively included from a German tertiary stroke center (Charité Berlin; January 2016–June 2020). Baseline and follow-up non-contrast Computed Tomography (NCCT) scans were analyzed for ICH, IVH, and PHE volume quantification by two radiology residents. Raters were blinded to all demographic and outcome data. Inter- and intrarater agreements were determined by calculating the Intraclass Correlation Coefficient (ICC) for a randomly selected set of patients with ICH, IVH, and PHE. Results: 100 out of 670 patients were included in the analysis. Interrater agreements ranged from an ICC of 0.998 for ICH (95% CI [0.993; 0.997]), to an ICC of 0.979 for IVH (95% CI [0.984; 0.993]), and an ICC of 0.886 for PHE (95% CI [0.760; 0.938]), all p-values < 0.001. Intrarater agreements ranged from an ICC of 0.997 for ICH (95% CI [0.996; 0.998]), to an ICC of 0.995 for IVH (95% CI [0.992; 0.996]), and an ICC of 0.980 for PHE (95% CI [0.971; 0.987]), all p-values < 0.001. Conclusion Manual segmentations of ICH, IVH, and PHE demonstrate good-to-excellent inter- and intrarater reliabilities, with the highest agreement for ICH and IVH and lowest for PHE. Therefore, the degree of variances reported in fully automated quantification methods might be related amongst others to variances in ground-truth masks