Ischemic Strokes Due to Large-Vessel Occlusions Contribute Disproportionately to Stroke-Related Dependence and Death: A Review

The Application of Data Envelopment Analysis to Emergency Departments and Management of Emergency Conditions: A Narrative Review

The healthcare industry is one application for data envelopment analysis (DEA) that can have significant benefits for standardizing health service delivery. This narrative review focuses on the application of DEA in emergency departments (EDs) and the management of emergency conditions such as acute ischemic stroke and acute myocardial infarction (AMI). This includes benchmarking the proportion of patients that receive treatment for these emergency conditions. The most frequent primary areas of study motivating work in DEA, EDs and management of emergency conditions including acute management of stroke are sorted into five distinct clusters in this study: (1) using basic DEA models for efficiency analysis in EDs, i.e., applying variable return to scale (VRS), or constant return to scale (CRS) to ED operations; (2) combining advanced and basic DEA approaches in EDs, i.e., applying super-efficiency with basic DEA or advanced DEA approaches such as additive model (ADD) and slack-based measurement (SBM) to clarify the dynamic aspects of ED efficiency throughout the duration of a first-aid program for AMI or heart attack; (3) applying DEA time series models in EDs like the early use of thrombolysis and percutaneous coronary intervention (PCI) in AMI treatment, and endovascular thrombectomy (EVT) in acute ischemic stroke treatment, i.e., using window analysis and Malmquist productivity index (MPI) to benchmark the performance of EDs over time; (4) integrating other approaches with DEA in EDs, i.e., combining simulations, machine learning (ML), multi-criteria decision analysis (MCDM) by DEA to reduce patient waiting times, and futile transfers; and (5) applying various DEA models for the management of acute ischemic stroke, i.e., using DEA to increase the number of eligible acute ischemic stroke patients receiving EVT and other medical ischemic stroke treatment in the form of thrombolysis (alteplase and now Tenecteplase). We thoroughly assess the methodological basis of the papers, offering detailed explanations regarding the applied models, selected inputs and outputs, and all relevant methodologies. In conclusion, we explore several ways to enhance DEA's status, transforming it from a mere technical application into a strong methodology that can be utilized by healthcare managers and decision-makers.

Role of artificial intelligence and machine learning in the diagnosis of cerebrovascular disease

Introduction

Cerebrovascular diseases are known to cause significant morbidity and mortality to the general population. In patients with cerebrovascular disease, prompt clinical evaluation and radiographic interpretation are both essential in optimizing clinical management and in triaging patients for critical and potentially life-saving neurosurgical interventions. With recent advancements in the domains of artificial intelligence (AI) and machine learning (ML), many AI and ML algorithms have been developed to further optimize the diagnosis and subsequent management of cerebrovascular disease. Despite such advances, further studies are needed to substantively evaluate both the diagnostic accuracy and feasibility of these techniques for their application in clinical practice. This review aims to analyze the current use of AI and MI algorithms in the diagnosis of, and clinical decision making for cerebrovascular disease, and to discuss both the feasibility and future applications of utilizing such algorithms.

Methods

We review the use of AI and ML algorithms to assist clinicians in the diagnosis and management of ischemic stroke, hemorrhagic stroke, intracranial aneurysms, and arteriovenous malformations (AVMs). After identifying the most widely used algorithms, we provide a detailed analysis of the accuracy and effectiveness of these algorithms in practice.

Results

The incorporation of AI and ML algorithms for cerebrovascular patients has demonstrated improvements in time to detection of intracranial pathologies such as intracerebral hemorrhage (ICH) and infarcts. For ischemic and hemorrhagic strokes, commercial AI software platforms such as RapidAI and Viz.AI have bene implemented into routine clinical practice at many stroke centers to expedite the detection of infarcts and ICH, respectively. Such algorithms and neural networks have also been analyzed for use in prognostication for such cerebrovascular pathologies. These include predicting outcomes for ischemic stroke patients, hematoma expansion, risk of aneurysm rupture, bleeding of AVMs, and in predicting outcomes following interventions such as risk of occlusion for various endovascular devices. Preliminary analyses have yielded promising sensitivities when AI and ML are used in concert with imaging modalities and a multidisciplinary team of health care providers.

Conclusion

The implementation of AI and ML algorithms to supplement clinical practice has conferred a high degree of accuracy, efficiency, and expedited detection in the clinical and radiographic evaluation and management of ischemic and hemorrhagic strokes, AVMs, and aneurysms. Such algorithms have been explored for further purposes of prognostication for these conditions, with promising preliminary results. Further studies should evaluate the longitudinal implementation of such techniques into hospital networks and residency programs to supplement clinical practice, and the extent to which these techniques improve patient care and clinical outcomes in the long-term.

Virtual reality simulation training in stroke thrombectomy centers with limited patient volume-Simulator performance and patient outcome

BACKGROUND

Virtual reality simulation training may improve the technical skills of interventional radiologists when establishing endovascular thrombectomy at limited-volume stroke centers. The aim of this study was to investigate whether the technical thrombectomy performance of interventional radiologists improved after a defined virtual reality simulator training period. As part of the quality surveillance of clinical practice, we also assessed patient outcomes and thrombectomy quality indicators at the participating centers.

METHODS

Interventional radiologists and radiology residents from three thrombectomy-capable stroke centers participated in a five months thrombectomy skill-training curriculum on a virtual reality simulator. The simulator automatically registered procedure time, the number of predefined steps that were correctly executed, handling errors, contrast volume, fluoroscopy time, and radiation dose exposure. The design was a before-after study. Two simulated thrombectomy cases were used as pretest and posttest cases, while seven other cases were used for training. Utilizing the Norwegian Stroke Register, we investigated clinical results in thrombectomy during the study period.

RESULTS

Nineteen interventional radiologists and radiology residents participated in the study. The improvement between pretest and posttest cases was statistically significant for all outcome measures in both simulated cases, except for the contrast volume used in one case. Clinical patient outcomes in all three centers were well within the recommendations from multi-society consensus guidelines.

CONCLUSION

Performance on the virtual reality simulator improved after training. Virtual reality simulation may improve the learning curve for interventional radiologists in limited-volume thrombectomy centers. No correlation alleged, the clinical data indicates that the centers studied performed thrombectomy in accordance with guideline-recommended standards.

Global, Regional, and National Economic Consequences of Stroke

BACKGROUND

An understanding of global, regional, and national macroeconomic losses caused by stroke is important for allocation of clinical and research resources. The authors investigated the macroeconomic consequences of stroke disease burden in the year 2019 in 173 countries.

METHODS

Disability-adjusted life year data for overall stroke and its subtypes (ischemic stroke, intracerebral hemorrhage, and subarachnoid hemorrhage) were collected from the GBD study (Global Burden of Disease) 2019 database. Gross domestic product (GDP, adjusted for purchasing power parity [PPP]) data were collected from the World Bank; GDP and disability-adjusted life year data were combined to estimate macroeconomic losses using a value of lost welfare (VLW) approach. All results are presented in 2017 international US dollars adjusted for PPP.

RESULTS

Globally, in 2019, VLW due to stroke was $2059.67 billion or 1.66% of the global GDP. Global VLW/GDP for stroke subtypes was 0.78% (VLW=$964.51 billion) for ischemic stroke, 0.71% (VLW=$882.81 billion) for intracerebral hemorrhage, and 0.17% (VLW=$212.36 billion) for subarachnoid hemorrhage. The Central European, Eastern European, and Central Asian GBD super-region reported the highest VLW/GDP for stroke overall (3.01%), ischemic stroke (1.86%), and for subarachnoid hemorrhage (0.26%). The Southeast Asian, East Asian, and Oceanian GBD super-region reported the highest VLW/GDP for intracerebral hemorrhage (1.48%).

CONCLUSIONS

The global macroeconomic consequences related to stroke are vast even when considering stroke subtypes. The present quantification may be leveraged to help justify increased spending of finite resources on stroke in an effort to improve outcomes for patients with stroke globally.

Management of intracranial arterial stenosis during mechanical thrombectomy: Survey of neuro-interventionalists

BACKGROUND

The optimal management of emergent large vessel occlusion due to underlying intracranial stenosis (intracranial stenosis related large vessel occlusion) remains unknown. The primary aim of this survey analysis was to measure variation in the clinical management of intracranial stenosis related large vessel occlusion during mechanical thrombectomy.

METHODS

A survey was designed using a web-based survey-building platform and distributed via the Society of NeuroInterventional Surgery (SNIS) and the Society of Vascular and Interventional Neurology (SVIN) websites for a response. Predictors of respondents' level of comfortability stenting were estimated using a binomial logistic regression model.

RESULTS

We received 105 responses to the survey. Most respondents (54.3%) practiced at an academic Stroke Center. Nearly half of the respondents (49%) had been practicing for 5 or more years independently after fellowship. An average of 54 mechanical thrombectomies were performed by each respondent annually. There was variation in the definition of intracranial stenosis related large vessel occlusion, number of passes performed before pursuing rescue stenting, as well as intra and post-procedural antiplatelet management. Of respondents, 58% felt rescue stenting was very risky, and 55.7% agreed that there was equipoise regarding emergent angioplasty and/or stenting versus medical therapy for intracranial stenosis related large vessel occlusion. Respondents who encountered intracranial stenosis related large vessel occlusion more frequently thought that rescue stenting was less risky.

CONCLUSION

There is notable variability in the diagnosis and management of intracranial stenosis related large vessel occlusion during mechanical thrombectomy. While most respondents felt rescue stenting was risky, the majority believed the benefit could outweigh the risk. The majority of respondents agreed that equipoise exists regarding the management of intracranial stenosis related large vessel occlusion, highlighting the need for clinical trials in this rare patient population.

World Federation for Interventional Stroke Treatment (WIST) Multispecialty Training Guidelines for Endovascular Stroke Intervention

INTRODUCTION

Today, endovascular treatment (EVT) is the therapy of choice for strokes due to acute large vessel occlusion, irrespective of prior thrombolysis. This necessitates fast, coordinated multi-specialty collaboration. Currently, in most countries, the number of physicians and centres with expertise in EVT is limited. Thus, only a small proportion of eligible patients receive this potentially life-saving therapy, often after significant delays. Hence, there is an unmet need to train a sufficient number of physicians and centres in acute stroke intervention in order to allow widespread and timely access to EVT.

AIM

To provide multi-specialty training guidelines for competency, accreditation and certification of centres and physicians in EVT for acute large vessel occlusion strokes.

MATERIAL AND METHODS

The World Federation for Interventional Stroke Treatment (WIST) consists of experts in the field of endovascular stroke treatment. This interdisciplinary working group developed competency - rather than time-based - guidelines for operator training, taking into consideration trainees' previous skillsets and experience. Existing training concepts from mostly single specialty organizations were analysed and incorporated.

RESULTS

The WIST establishes an individualized approach to acquiring clinical knowledge and procedural skills to meet the competency requirements for certification of interventionalists of various disciplines and stroke centres in EVT. WIST guidelines encourage acquisition of skills using innovative training methods such as structured supervised high-fidelity simulation and procedural performance on human perfused cadaveric models.

CONCLUSIONS

WIST multispecialty guidelines outline competency and quality standards for physicians and centres to perform safe and effective EVT. The role of quality control and quality assurance is highlighted.

SUMMARY

The World Federation for Interventional Stroke Treatment (WIST) establishes an individualized approach to acquiring clinical knowledge and procedural skills to meet the competency requirements for certification of interventionalists of various disciplines and stroke centres in endovascular treatment (EVT). WIST guidelines encourage acquisition of skills using innovative training methods such as structured supervised high-fidelity simulation and procedural performance on human perfused cadaveric models. WIST multispecialty guidelines outline competency and quality standards for physicians and centers to perform safe and effective EVT. The role of quality control and quality assurance is highlighted.

SIMULTANEOUS PUBLICATION

The WIST 2023 Guidelines are published simultaneously in Europe (Adv Interv Cardiol 2023).

Performance of Thrombectomy-Capable, Comprehensive, and Primary Stroke Centers in Reperfusion Therapies for Acute Ischemic Stroke: Report from the Get With The Guidelines Stroke Registry: Stroke Outcomes Per Hospital Certification Status

Background

The thrombectomy-capable stroke center (TSC) is a recently introduced intermediate tier of accreditation for hospitals caring for patients with acute ischemic stroke (AIS). The comparative quality and clinical outcomes of reperfusion therapies at TSCs, primary stroke centers (PSCs), and comprehensive stroke centers (CSCs) has not been well delineated.

Methods

We conducted a retrospective, observational, cohort study from 2018-2020 that included patients with AIS who received endovascular (EVT) and/or intravenous (IVT) reperfusion therapies at CSC, TSC, or PSC. Participants were recruited from Get With The Guidelines-Stroke registry. Study endpoints included timeliness of IVT and EVT, successful reperfusion, discharge destination, discharge mortality, and functional independence at discharge.

Results

Among 84,903 included patients, 48,682 received EVT, of whom 73% were treated at CSCs, 22% at PSCs, and 4% at TSCs. The median annual EVT volume was 76 for CSCs, 55 for TSCs, and 32 for PSCs. Patient differences by center status included higher NIHSS, longer onset-to-arrival time, and higher transfer-in rates for CSC/TSC/PSC, respectively. In adjusted analyses, the likelihood of achieving the goal door-to-needle time was higher in CSCs compared to PSCs (OR 1.39; 95% CI 1.17-1.66) and in TSCs compared to PSCs (OR 1.45; 95% CI 1.08-1.96). Similarly, the odds of achieving the goal door-to-puncture time were higher in CSCs compared to PSCs (OR 1.58; 95% CI 1.13-2.21). CSCs and TSCs also demonstrated better clinical efficacy outcomes compared to PSCs. The odds of discharge to home or rehabilitation were higher in CSCs compared to PSCs (OR 1.18; 95% CI 1.06-1.31), while the odds of in-hospital mortality/discharge to hospice were lower in both CSCs compared to PSCs (OR 0.87; 95% CI 0.81-0.94) and TSCs compared to PSCs (OR 0.86; 95% CI 0.75-0.98). There were no significant differences in any of the quality-of-care metrics and clinical outcomes between TSCs and CSCs.

Conclusions

In this study representing national US practice, CSCs and TSCs exceeded PSCs in key quality-of-care reperfusion metrics and outcomes, whereas TSCs and CSCs demonstrated similar performance. Considering that over one-fifth of all EVT procedures during the study period were conducted at PSCs, it may be desirable to explore national initiatives aimed at facilitating the elevation of eligible PSCs to a higher certification status.

Neuroimaging Spectrum in COVID-19 Infection: A Single-Center Experience

Background and Purpose  The ongoing coronavirus disease 2019 (COVID-19) pandemic is a multisystemic disease and involvement of the nervous system is well established. The neurological and neuroimaging features of the disease have been extensively evaluated. Our study aimed to elucidate the neuroradiological findings in COVID-19 infected patients admitted to our institute during the first and second waves of the pandemic in India. Methods  This was a single-center retrospective study of all COVID-19 positive patients who underwent neuroimaging between March 2020 and May 2021. The presenting neurological complaints, the imaging findings in computed tomography (CT) imaging, and/or magnetic resonance imaging (MRI) were recorded. They recorded the findings in the subheadings of ischemic stroke, hemorrhagic stroke, parainfectious demyelination, acute encephalitis syndrome, and changes of global hypoxic changes. Patients with age-related, chronic, and incidental findings were excluded. Results  The study comprised of 180 COVID-19 positive patients who underwent neuroimaging. CT scan was performed for 169 patients, MRI for 28, and a combination of both CT and MRI was performed for 17 patients. Seventy percent of patients were males, and median age was 61.5 years (interquartile range: 48.25-70.75). Out of the 180 patients, 66 patients had nonspecific findings that could not be attributed to COVID-19 infection. In the remaining 114 patients, 77 (42.7%) had ischemic findings, while 22 (12.2%) had hemorrhagic stroke. Hypoxic ischemic changes were noted in five patients. The rest of the patients had a spectrum of changes including, cerebellitis (3), tumefactive demyelination (1), COVID-19-associated encephalitis (1), hemorrhagic acute demyelinating encephalomyelitis (1), transverse myelitis (1), cytotoxic lesions of corpus callosum (1), Guillain-Barre syndrome (1), and COVID-19-associated microhemorrhages (1). Conclusion  Neurological manifestations of COVID-19 infection are not uncommon, and our understanding of this topic is expanding. A complex interplay of neurotropism and direct central nervous system invasion, immune activation and cytokine storm, vasculitis, and parainfectious processes are implicated in the pathophysiology. While the most common imaging finding was ischemic stroke, followed by hemorrhagic stroke, a diverse range of parainfectious findings was also noted in our study.

Lipidomics, Acute Ischemic Stroke, Symptoms, and Outcomes: Observational Study Protocol

BACKGROUND

Acute ischemic stroke is one of the leading causes of death and disability globally. Recent advances in omics methodology enable lipidomic profiling, which may provide knowledge of the underlying pathology of acute ischemic stroke and its associated outcomes.

OBJECTIVE

This study aims to examine the longer-term relationships between symptoms and outcomes following acute ischemic stroke and the underlying lipidomic signatures over 6 months during recovery between acute ischemic stroke patients who received reperfusion therapies and those who did not.

METHODS

This prospective cohort study will enroll 104 participants post-acute ischemic stroke in two groups based on their receipt of reperfusion therapy (Group 1) or not (Group 2; n = 52/group). Peripheral plasma samples will be collected from both groups for lipidomic analysis over 6 months. Arterial blood samples will be collected during the procedure for those receiving reperfusion. Self-reported symptoms and outcome data will be collected from both groups.

DISCUSSION

We will compare and examine the associations among plasma lipidomic biomarkers and symptoms and cognitive, functional, and health-related quality of life outcomes over 6 months between acute ischemic stroke patients who did and did not receive reperfusion intervention.

Inflammatory-associated proteomic predictors of cognitive outcome in subjects with ELVO treated by mechanical thrombectomy

BACKGROUND

Emergent Large Vessel Occlusion (ELVO) stroke causes devastating vascular events which can lead to significant cognitive decline and dementia. In the subset of ELVO subjects treated with mechanical thrombectomy (MT) at our institution, we aimed to identify systemic and intracranial proteins predictive of cognitive function at time of discharge and at 90-days. These proteomic biomarkers may serve as prognostic indicators of recovery, as well as potential targets for novel/existing therapeutics to be delivered during the subacute stage of stroke recovery.

METHODS

At the University of Kentucky Center for Advanced Translational Stroke Sciences, the BACTRAC tissue registry (clinicaltrials.gov; NCT03153683) of human biospecimens acquired during ELVO stroke by MT is utilized for research. Clinical data are collected on each enrolled subject who meets inclusion criteria. Blood samples obtained during thrombectomy were sent to Olink Proteomics for proteomic expression values. Montreal Cognitive Assessments (MoCA) were evaluated with categorical variables using ANOVA and t-tests, and continuous variables using Pearson correlations.

RESULTS

There were n = 52 subjects with discharge MoCA scores and n = 28 subjects with 90-day MoCA scores. Several systemic and intracranial proteins were identified as having significant correlations to discharge MoCA scores as well as 90-day MoCA scores. Highlighted proteins included s-DPP4, CCL11, IGFBP3, DNER, NRP1, MCP1, and COMP.

CONCLUSION

We set out to identify proteomic predictors and potential therapeutic targets related to cognitive outcomes in ELVO subjects undergoing MT. Here, we identify several proteins which predicted MoCA after MT, which may serve as therapeutic targets to lessen post-stroke cognitive decline.

The diagnostic performance of artificial intelligence algorithms for identifying M2 segment middle cerebral artery occlusions: A systematic review and meta-analysis

BACKGROUND

Artificial intelligence (AI)-based algorithms have been developed to facilitate rapid and accurate computed tomography angiography (CTA) assessment in proximal large vessel occlusion (LVO) acute ischemic stroke, including internal carotid artery and M1 occlusions. In clinical practice, however, the detection of medium vessel occlusion (MeVO) represents an ongoing diagnostic challenge in which the added value of AI remains unclear.

PURPOSE

To assess the diagnostic performance of AI platforms for detecting M2 occlusions.

METHODS

Studies that report the diagnostic performance of AI-based detection of M2 occlusions were screened, and sensitivity and specificity data were extracted using the semi-automated AutoLit software (Nested Knowledge, MN) platform. STATA (version 16 IC; Stata Corporation, College Station, Texas, USA) was used to conduct all analyses.

RESULTS

Eight studies with a low risk of bias and significant heterogeneity were included in the quantitative and qualitative synthesis. The pooled estimates of sensitivity and specificity of AI platforms for M2 occlusion detection were 64% (95% CI, 53 to 74%) and 97% (95% CI, 84 to 100%), respectively. The area under the curve (AUC) in the SROC curve was 0.79 (95% CI, 0.74 to 0.83).

CONCLUSION

The current performance of the AI-based algorithm makes it more suitable as an adjunctive confirmatory tool rather than as an independent one for M2 occlusions. With the rapid development of such algorithms, it is anticipated that newer generations will likely perform much better.

Assessing the Relationship between LAMS and CT Perfusion Parameters in Acute Ischemic Stroke Secondary to Large Vessel Occlusion

BACKGROUND

The Los Angeles Motor Scale (LAMS) is a rapid pre-hospital scale used to predict stroke severity which has also been shown to accurately predict large vessel occlusions (LVOs). However, to date there is no study exploring whether LAMS correlates with the computed tomography perfusion (CTP) parameters in LVOs.

METHODS

Patients with LVO between September 2019 and October 2021 were retrospectively reviewed and included if the CTP data and admission neurologic exams were available. The LAMS was documented based on emergency personnel exams or scored retrospectively using an admission neurologic exam. The CTP data was processed by RAPID (IschemaView, Menlo Park, CA, USA) with an ischemic core volume (relative cerebral blood flow [rCBF] < 30%), time-to-maximum (Tmax) volume (Tmax > 6 s delay), hypoperfusion index (HI), and cerebral blood volume (CBV) index. Spearman's correlations were performed between the LAMS and CTP parameters.

RESULTS

A total of 85 patients were included, of which there were 9 intracranial internal carotid artery (ICA), 53 proximal M1 branch middle cerebral artery M1, and 23 proximal M2 branch occlusions. Overall, 26 patients had LAMS 0-3, and 59 had LAMS 4-5. In total, LAMS positively correlated with CBF < 30% (Correlation Coefficient (CC): 0.32, p < 0.01), Tmax > 6 s (CC:0.23, p < 0.04), HI (CC:0.27, p < 0.01), and negatively correlated with the CBV index (CC:-0.24, p < 0.05). The relationships between LAMS and CBF were < 30% and the HI was more pronounced in M1 occlusions (CC:0.42, p < 0.01; 0.34, p < 0.01 respectively) and proximal M2 occlusions (CC:0.53, p < 0.01; 0.48, p < 0.03 respectively). The LAMS also correlated with a Tmax > 6 s in M1 occlusions (CC:0.42, p < 0.01), and negatively correlated with the CBV index in M2 occlusions (CC:-0.69, p < 0.01). There were no significant correlations between the LAMS and intracranial ICA occlusions.

CONCLUSIONS

The results of our preliminary study indicate that the LAMS is positively correlated with the estimated ischemic core, perfusion deficit, and HI, and negatively correlated with the CBV index in patients with anterior circulation LVO, with stronger relationships in the M1 and M2 occlusions. This is the first study showing that the LAMS may be correlated with the collateral status and estimated ischemic core in patients with LVO.

Diagnostic accuracy of a decision-support software for the detection of intracranial large-vessel occlusion in CT angiography

AIM

To investigate the real-world clinical performance of the decision-support software "e-CTA" (e-Stroke Suite, Brainomix Limited, Oxford UK) for the detection of acute intracranial large-vessel occlusion (LVO) on computed tomography (CT) angiography at a UK district general hospital.

MATERIALS AND METHODS

The retrospective study included 300 consecutive CT angiograms of the head and neck performed between 8 March 2021 and 20 May 2021. e-CTA findings were recorded and compared with the radiologist report. Cases in which there was disagreement between e-CTA and the radiologist were reviewed by a sub-specialist vascular radiologist as the reference standard.

RESULTS

The incidence of intracranial LVO was 7%. e-CTA correctly identified 18 of 21 intracranial proximal LVOs (86%). There were 34 false positives. The sensitivity was 0.86 (95% confidence interval [CI], 0.64-0.97), with specificity of 0.88 (95% CI, 0.83-0.91). The positive predictive value was 0.35 (95% CI, 0.27-0.43). The negative predictive value was 0.99 (95% CI, 0.96-1.00).

CONCLUSION

Sensitivity, specificity, and negative predictive values were similar to those reported in the literature (Seker et al., Int J Stroke. 2021; 17:77-82); however, the positive predictive value for e-CTA was significantly lower. In practice, this meant that over half of all reported occlusions by the software were false positives. Radiologists should be aware of these metrics in order to assign appropriate weight to software findings when formulating a report. Differences in population demographics, scanners, CT protocols, and incidence are all factors potentially influencing software accuracy. Local validation testing may help provide accuracy metrics more relevant to individual institutions.

Anticoagulation under-utilization in atrial fibrillation patients is responsible for a large proportion of strokes requiring endovascular therapy

OBJECTIVES

Atrial fibrillation (AF) is responsible for 30-50% of large strokes requiring endovascular thrombectomy (EVT). Anticoagulation (AC) underutilization is a common source of AF-related stroke. We compared antithrombotic medications among stroke patients with AF that did or did not undergo EVT to determine if AC underutilization disproportionately results in strokes requiring EVT, while quantifying the proportion of likely preventable thrombectomies.

METHODS

This retrospective single-center cohort included consecutive patients admitted with acute ischemic stroke between 2016 and 2021. Patients were categorized based on the presence of AF, and pre-admission antithrombotic medications were compared between those who underwent EVT and those who didn't. The reason for not being on AC was abstracted from the medical record, and patients were categorized as either AC eligible or AC contraindicated.

RESULTS

Of 3092 acute ischemic stroke patients, 644 had a history of AF, 213 of whom underwent EVT. Patients who required EVT were more likely to not be taking any antithrombotics prior to admission (34% vs 24%, p=0.007) or have subtherapeutic INR on admission if taking warfarin (83% vs 63%; p = 0.046). Among the AF-EVT patients, 44% were taking AC, and only 31% were adequately anticoagulated. Only 8% of AF-EVT patients who were not on pre-admission AC had a clear contraindication, and 94% were ultimately discharged on AC.

CONCLUSIONS

Lack of antithrombotic therapy in AF patients disproportionately contributes to strokes requiring EVT. A small minority of AF patients have contraindications to AC, so adequate anticoagulation can prevent a remarkable number of strokes requiring EVT.

Factors associated with the time from the first call to emergency medical services to puncture for mechanical thrombectomy for ischaemic stroke patients in Gironde, France, in 2017 and 2018

BACKGROUND AND PURPOSE

When an ischaemic stroke due to a large vessel occlusion occurs, the sooner Mechanical Thrombectomy (MT) is performed, the better the functional prognosis. However, the organisation of care does not systematically allow rapid access to MT. The aim of our study was to determine the clinical and organisational factors associated with the time to access to MT.

METHODS

We conducted a cohort study in Gironde County, France. Patients admitted for MT and regulated by the Gironde Emergency Medical Services (EMS) between 01/01/2017 and 31/12/2018 were included. The time to access to MT was the difference between the first call to EMS and groin puncture for MT. The main explanatory variables were: type of pathway (mothership (MS), drip and ship (DS) with cerebral imaging performed in the local hospital centre (LHC), and DS without imaging in the LHC); NIHSS score; driving distance to MT; time of stroke onset (weekend or holiday, school holidays, other); age and sex. Linear regression models were used to explain time to access to MT. Missing data were handled using a multiple imputation procedure (Full conditional specification, Mice R-Package) carried out in our multivariable linear regression model. A quantitative bias analysis was performed by weighing the imputed time to access to MT and identifying the weight changing the conclusions of our analysis.

RESULTS

Among the 314 included patients, 152 were women (48.4%), and the mean NIHSS score was 16.4. Two hundred and two (64.3%) patients were managed through the MS pathway. The average time from onset to femoral puncture was 251 minutes. In the multivariate analysis, the time to MT was longer when patients were managed DS with imaging in the LHC pathway (+106 min, p = 0.03), and even longer in the DS without imaging in the LHC pathway (+197 min, p = 0.002), compared with MS. Time from onset to MT decreased with increasing NIHSS score (-6 min per NIHSS point, p <.0001). In our quantitative bias analysis, we multiplied the imputed time in access to MT in the DS pathways only (with or without imaging in the LHC) by weights varying from 0.9 to 0.2 (imputed delays reduced from 10% to 80%). With reduction of 40% or more, there was no longer any difference in time to access to MT between the three studied pathways.

CONCLUSIONS

The DS pathway can be shortened by generalizing access to cerebral imaging in LHCs. Optimizing pre-admission orientation toward MT is a major issue in LVOS management.

Predictors of functional dependence at one year in acute ischemic stroke with large vessel occlusion

BACKGROUND

In China, the current status of clinical treatment of eLVO and the factors affecting its long-term prognosis are unclear.

OBJECTIVE

This study aims to explore the predictive factors of functional outcomes at one year in patients of acute ischemic stroke with emergent large vessel occlusion (eLVO).

METHODS

We retrospectively collected 536 patients who underwent treatments for eLVO. Primary outcomes included one-year functional outcomes and delayed functional independence (DFI). The logistic regression was performed to predict the primary outcome.

RESULTS

431 (85%) survivors participated in the one-year follow-up. In the multivariate logistic analysis adjusted for baseline characteristics, the following factors were found to be significant predictors of functional dependence at one year: old age (aOR = 1.042, 95% CI=1.01-1.076, p = 0.011), low Alberta stroke program early CT score (ASPECTS) (aOR = 0.791, 95% CI=0.671-0.933, p = 0.005), unsuccessful reperfusion (aOR = 0.168, 95% CI=0.048-0.586, p = 0.005), poor medication compliance (aOR = 0.022, 95% CI=0.007-0.072, p < 0.001), and complicated with stroke-associated pneumonia (SAP) (aOR = 2.269, 95% CI=1.103-4.670, p = 0.026). We also found that men (aOR = 3.947, 95% CI=1.15-13.549, p = 0.029) had better medication adherence (aOR = 14.077, 95% CI=1.736-114.157, p = 0.013), and going to rehabilitation centers (aOR = 5.197, 95% CI=1.474-18.327, p = 0.010) were independent predictors of DFI.

CONCLUSION

The significant predictors of functional dependence at one year were: old age, low ASPECTS, unsuccessful reperfusion, poor medication adherence, and combination with SAP. Men, good medication adherence, and going to rehabilitation centers contributed to getting delayed functional independence.

Direct Mechanical Thrombectomy Versus Prior Bridging Intravenous Thrombolysis in Acute Ischemic Stroke: A Systematic Review and Meta-Analysis

BACKGROUND

The current guideline recommends using an intravenous tissue-type plasminogen activator (IV tPA) prior to mechanical thrombectomy (MT) in eligible acute ischemic stroke (AIS) with emergent large vessel occlusion (ELVO). Some recent studies found no significant differences in the long-term functional outcomes between bridging therapy (BT, i.e., IV tPA prior to MT) and direct MT (dMT).

METHODS

We conducted a systematic review and meta-analysis to compare the safety and functional outcomes between BT and dMT in AIS patients with ELVO who were eligible for IV tPA administration. Based on the ELVO location, patients were categorized as the anterior group (occlusion of the anterior circulation), or the combined group (occlusion of the anterior and/or posterior circulation). A subgroup analysis was performed based on the study type, i.e., RCT and non-RCT.

RESULTS

Thirteen studies (3985 patients) matched the eligibility criteria. Comparing the BT and dMT groups, no significant differences in terms of mortality and good functional outcome were observed at 90 days. Symptomatic intracranial hemorrhagic (sICH) events were more frequent in BT patients in the combined group (OR = 0.73, p = 0.02); this result remained significant only in the non-RCT subgroup (OR = 0.67, p = 0.03). The RCT subgroup had a significantly higher rate of successful revascularization in BT patients (OR = 0.73, p = 0.02).

CONCLUSIONS

Our meta-analysis uncovered no significant differences in functional outcome and mortality rate at 90 days between dMT and BT in patients with AIS who had ELVO. Although BT performed better in terms of successful recanalization rate, there is a risk of increased sICH rate in this group.

Automated detection of intracranial large vessel occlusions using Viz.ai software: Experience in a large, integrated stroke network

BACKGROUND AND PURPOSE

Endovascular thrombectomy is an evidence-based treatment for large vessel occlusion (LVO) stroke. Commercially available artificial intelligence has been designed to detect the presence of an LVO on computed tomography angiogram (CTA). We compared Viz.ai-LVO (San Francisco, CA, USA) to CTA interpretation by board-certified neuroradiologists (NRs) in a large, integrated stroke network.

METHODS

From January 2021 to December 2021, we compared Viz.ai detection of an internal carotid artery (ICA) or middle cerebral artery first segment (MCA-M1) occlusion to the gold standard of CTA interpretation by board-certified NRs for all code stroke CTAs. On a monthly basis, sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Trend analyses were conducted to evaluate for any improvement of LVO detection by the software over time.

RESULTS

3851 patients met study inclusion criteria, of whom 220 (5.7%) had an ICA or MCA-M1 occlusion per NR. Sensitivity and specificity were 78.2% (95% CI 72%-83%) and 97% (95% CI 96%-98%), respectively. PPV was 61% (95% CI 55%-67%), NPV 99% (95% CI 98%-99%), and accuracy was 95.9% (95% CI 95.3%-96.5%). Neither specificity or sensitivity improved over time in the trend analysis.

CONCLUSIONS

Viz.ai-LVO has high specificity and moderately high sensitivity to detect an ICA or proximal MCA occlusion. The software has the potential to streamline code stroke workflows and may be particularly impactful when emergency access to NRs or vascular neurologists is limited.

Intra-arterial verapamil improves functional outcomes of thrombectomy in a preclinical model of extended hyperglycemic stroke

The abrupt hyperglycemic reperfusion following thrombectomy has been shown to harm the efficacy of the intervention in stroke patients with large vessel occlusion. Studies of ours and others have shown thioredoxin-interacting protein (TXNIP) is critically involved in hyperglycemic stroke injury. We recently found verapamil ameliorates cerebrovascular toxicity of tissue plasminogen activators in hyperglycemic stroke. The present study aims to answer if verapamil exerts direct neuroprotective effects and alleviates glucose toxicity following thrombectomy in a preclinical model of hyperglycemic stroke. Primary cortical neural (PCN) cultures were exposed to hyperglycemic reperfusion following oxygen-glucose deprivation (OGD), with or without verapamil treatment. In a mouse model of intraluminal stroke, animals were subjected to 4 h middle cerebral artery occlusion (MCAO) and intravenous glucose infusion. Glucose infusion lasted one more hour at reperfusion, along with intra-arterial (i.a.) verapamil infusion. Animals were subjected to sensorimotor function tests and histological analysis of microglial phenotype at 72 h post-stroke. According to our findings, glucose concentrations (2.5-20 mM) directly correlated with TXNIP expression in OGD-exposed PCN cultures. Verapamil (100 nM) effectively improved PCN cell neurite growth and reduced TXNIP expression as well as interaction with NOD-like receptor pyrin domain-containing-3 (NLRP3) inflammasome, as determined by immunoblotting and immunoprecipitation. In our mouse model of extended hyperglycemic MCAO, i.a. verapamil (0.5 mg/kg) could attenuate neurological deficits induced by hyperglycemic stroke. This was associated with reduced microglial pro-inflammatory transition. This finding encourages pertinent studies in hyperglycemic patients undergoing thrombectomy where the robust reperfusion may exacerbate glucose toxicity.

Developing and predicting of early mortality after endovascular thrombectomy in patients with acute ischemic stroke

BACKGROUND

Stroke is one of the leading causes of mortality across the world. However, there is a paucity of information regarding mortality rates and associated risk factors in patients with acute ischemic stroke (AIS) undergoing endovascular thrombectomy (EVT). In this study, we aimed to clarify these issues and analyzed previous publications related to mortality in patients treated with EVT.

METHODS

We analyzed the survival of 245 consecutive patients treated with mechanical thrombectomy for AIS for which mortality information was obtained. Early mortality was defined as death occurring during hospitalization after EVT or within 7 days following hospital discharge from the stroke event.

RESULTS

Early mortality occurred in 22.8% of cases in this cohort. Recanalization status (modified thrombolysis in cerebral infarction, mTICI) (p = 0.002), National Institute of Health Stroke Scale Score (NIHSS) score 24-h after EVT (p < 0.001) and symptomatic intracerebral hemorrhage (sICH) (p < 0.001) were independently associated with early mortality. Age, sex, cardiovascular risk factors, NIHSS score pre-treatment, Alberta Stroke Program Early CT Score (ASPECTS), stroke subtype, site of arterial occlusion and timing form onset to recanalization did not have an independent influence on survival. Non-survivors had a shorter hospitalization (p < 0.001) but higher costs related to their hospitalization and outpatient care.

CONCLUSION

The recanalization status, NIHSS score 24-h after EVT and sICH were predictors of early mortality in AIS patients treated with EVT.

Effect of blood pressure on the prognosis of acute ischemic stroke patients caused by anterior circulation large vessel occlusion without recanalization

PURPOSE

To explore the effect of blood pressure on the prognosis of acute ischemic stroke patients caused by anterior circulation large vessel occlusion without recanalization.

METHODS

Acute ischemic stroke patients caused by anterior circulation large vessel occlusion without recanalization were retrospectively collected. All patients were divided into the functional independent group and non-functional independent group, death group and non-death group based on the 90-day mRS score. Logistic regression was applied to analyze the relationship between the highest systolic blood pressure, the average systolic blood pressure, the lowest systolic blood pressure, the highest diastolic blood pressure, the average diastolic blood pressure, the lowest diastolic blood pressure in the first 24 h after admission and the functional prognosis as well as the complications after 90 days. The independent impact factors selected from regression analysis were used to investigate the blood pressure with prognostic value by receiver operating characteristic curve (ROC).

RESULTS

A total of 70 patients were recruited in this study. Among them, 39 cases (55.71%) were male and 31 cases (44.29%) were female, with a mean age of 61.83 ± 15.24 years old. 15 cases (21.43%) had a favorable 90-day outcome, and the other 55 cases (78.57%) had a higher mRS Score. After a 90-day follow-up, univariate analysis showed that hypertension and hyperlipidemia, highest systolic blood pressure, mean systolic blood pressure and NIHSS score were statistically significant in two groups with or without functional independence, while the NIHSS score at admission, systolic blood pressure at admission, average systolic blood pressure, highest systolic blood pressure and diastolic blood pressure were statistically significant in patients with death outcomes (P < 0.05). Multivariate regression analysis suggested that the highest systolic blood pressure was statistically significant (P < 0.05), the further ROC curve results showed the cut-off value of the highest systolic blood pressure was 180.5 mmHg, with a sensitivity of 82.35% and a specificity of 81.13%. The highest Youden's index was 0.6348.

CONCLUSION

For acute ischemic stroke patients caused by anterior circulation large vessel occlusion without recanalization, the appropriate reduction of blood pressure within 24 h after admission may have a positive effect on the clinical prognosis. The 90-day mortality of acute ischemic stroke patients without revascularization was independently related to the highest systolic blood pressure. The risk of death was increased when the highest systolic blood pressure was greater than 180.5 mmHg.

Dose-Dependent Von Willebrand Factor Inhibition by Aptamer BB-031 Correlates with Thrombolysis in a Microfluidic Model of Arterial Occlusion

Von Willebrand Factor (VWF) plays a critical role in thrombus formation, stabilization, and propagation. Previous studies have demonstrated that targeted inhibition of VWF induces thrombolysis when administered in vivo in animal models of ischemic stroke. The study objective was to quantify dose-dependent inhibition of VWF-platelet function and its relationship with thrombolysis using BB-031, an aptamer that binds VWF and inhibits its function. VWF:Ac, VWF:RCo, T-TAS, and ristocetin-induced impedance aggregometry were used to assess BB-031-mediated inhibition of VWF. Reductions in original thrombus surface area and new deposition during administration of treatment were measured in a microfluidic model of arterial thrombolysis. Rotational thromboelastometry was used to assess changes in hemostasis. BB-031 induced maximal inhibition at the highest dose (3384 nM) in VWF:Ac, and demonstrated dose-dependent responses in all other assays. BB-031, but not vehicle, induced recanalization in the microfluidic model. Maximal lytic efficacy in the microfluidic model was seen at 1692 nM and not 3384 nM BB-031 when assessed by surface area. Minor changes in ROTEM parameters were seen at 3384 nM BB-031. Targeted VWF inhibition by BB-031 results in clinically measurable impairment of VWF function, and specifically VWF-GPIb function as measured by VWF:Ac. BB-031 also induced thrombolysis as measured in a microfluidic model of occlusion and reperfusion. Moderate correlation between inhibition and lysis was observed. Additional studies are required to further examine off-target effects of BB-031 at high doses, however, these are expected to be above the range of clinical targeted dosing.

Deep Learning in Ischemic Stroke Imaging Analysis: A Comprehensive Review

Ischemic stroke is a cerebrovascular disease with a high morbidity and mortality rate, which poses a serious challenge to human health and life. Meanwhile, the management of ischemic stroke remains highly dependent on manual visual analysis of noncontrast computed tomography (CT) or magnetic resonance imaging (MRI). However, artifacts and noise of the equipment as well as the radiologist experience play a significant role on diagnostic accuracy. To overcome these defects, the number of computer-aided diagnostic (CAD) methods for ischemic stroke is increasing substantially during the past decade. Particularly, deep learning models with massive data learning capabilities are recognized as powerful auxiliary tools for the acute intervention and guiding prognosis of ischemic stroke. To select appropriate interventions, facilitate clinical practice, and improve the clinical outcomes of patients, this review firstly surveys the current state-of-the-art deep learning technology. Then, we summarized the major applications in acute ischemic stroke imaging, particularly in exploring the potential function of stroke diagnosis and multimodal prognostication. Finally, we sketched out the current problems and prospects.

Thrombectomy in large vessel occlusion stroke-Does age matter?

OBJECTIVES

Endovascular treatment (EVT) is the gold standard treatment for emergent large vessel occlusion (LVO). The benefit of EVT for emergent LVO in elderly patients (>80 years old) is still debated as they have been under-represented in randomized controlled trials. Elderly patients with an emergent LVO are a growing population warranting further study.

MATERIALS & METHODS

We included 225 consecutive patients treated with EVT for LVO either in the anterior or posterior circulation. The clinical outcome was assessed using the National Institute of Health Stroke Scale (NIHSS). Long-term functional outcome was assessed using 90-day modified ranking scale (mRS).

RESULTS

Neurological improvement: A five-year higher age predicted a 0.43 higher mean NIHSS score after EVT (p = .027). After adjusting for confounders (influencing variables), the association between age and post-interventional NIHSS was reduced and non-significant (p = .17). At discharge, a five-year higher age predicted a 0.74 higher mean NIHSS (p = .003). After adjusting for confounders this association was reduced and non-significant (p = .06). Long-term functional outcome: A five-year higher age predicted a 0.20 higher mRS at three months (p < .001). When adjusting for confounders this number was reduced to 0.16, yet still highly significant (p < .001).

CONCLUSIONS

Age seems to have a minor role in predicting neurological improvement after EVT but has an impact on long-term functional outcome. The decision to perform or withhold EVT should therefore not solely be based on age.

Image level detection of large vessel occlusion on 4D-CTA perfusion data using deep learning in acute stroke

OBJECTIVES

Automated image-level detection of large vessel occlusions (LVO) could expedite patient triage for mechanical thrombectomy. A few studies have previously attempted LVO detection using artificial intelligence (AI) on CT angiography (CTA) images. To our knowledge this is the first study to detect LVO existence and location on raw 4D-CTA/ CT perfusion (CTP) images using neural network (NN) models.

MATERIALS AND METHODS

Retrospective study using data from a level-I stroke center was performed. A total of 306 (187 with LVO, and 119 without) patients were evaluated. Image pre-processing included co-registration, normalization and skull stripping. Five consecutive time-points for each patient were selected to provide variable contrast density in data. Additional data augmentation included rotation and horizonal image flipping. Our model architecture consisted of two neural networks, first for classification (based on hemispheric asymmetry), followed by second model for exact site of LVO detection. Only cases deemed positive by the classification model were routed to the detection model, thereby reducing false positives and improving specificity. The results were compared with expert annotated LVO detection.

RESULTS

Using a 80:20 split for training and validation, the combination of both classification and detection model achieved a sensitivity of 86.5%, a specificity of 89.5%, and an accuracy of 87.5%. A 5-fold cross-validation using the entire data achieved a mean sensitivity of 82.7%, a specificity of 89.8%, and an accuracy of 85.5% and a mean AUC of 0.89 (95% CI: 0.85-0.93).

CONCLUSION

Our findings suggest that accurate image-level LVO detection is feasible on CTP raw images.

eICAB: A novel deep learning pipeline for Circle of Willis multiclass segmentation and analysis

BACKGROUND

The accurate segmentation, labeling and quantification of cerebral blood vessels on MR imaging is important for basic and clinical research, yet results are not generalizable, and often require user intervention. New methods are needed to automate this process.

PURPOSE

To automatically segment, label and quantify Circle of Willis (CW) arteries on Magnetic Resonance Angiography images using deep convolutional neural networks.

MATERIALS AND METHODS

MRA images were pooled from three public and private databases. A total of 116 subjects (mean age 56 years ± 21 [standard deviation]; 72 women) were used to make up the training set (N=101) and the testing set (N=15). In each image, fourteen arterial segments making up or surrounding the CW were manually annotated and validated by a clinical expert. Convolutional neural network (CNN) models were trained on a training set to be finally combined in an ensemble to develop eICAB. Model performances were evaluated using (1) quantitative analysis (dice score on test set) and (2) qualitative analysis (external datasets, N=121). The reliability was assessed using multiple MRAs of healthy participants (ICC of vessel diameters and volumes on test-retest).

RESULTS

Qualitative analysis showed that eICAB correctly predicted the large, medium and small arteries in 99±0.4%, 97±1% and 88±7% of all images, respectively. For quantitative assessment, the average dice score coefficients for the large (ICAs, BA), medium (ACAs, MCAs, PCAs-P2), and small (AComm, PComm, PCAs-P1) vessels were 0.76±0.07, 0.76±0.08 and 0.41±0.27, respectively. These results were similar and, in some cases, statistically better (p<0.05) than inter-expert annotation variability and robust to image SNR. Finally, test-retest analysis showed that the model yielded high diameter and volume reliability (ICC=0.99).

CONCLUSION

We have developed a quick and reliable open-source CNN-based method capable of accurately segmenting and labeling the CW in MRA images. This method is largely independent of image quality. In the future, we foresee this approach as a critical step towards fully automated analysis of MRA databases in basic and clinical research.

A novel integrated angioscope-laser system for atherosclerotic carotid artery occlusion: Feasibility and techniques

Introduction

Atherosclerotic extracranial carotid artery stenosis accounts for about 20%-30% of all strokes, which is one of the leading causes of adult morbidity and mortality. Although carotid endarterectomy (CEA) is still the mainly operational manner for atherosclerotic carotid artery stenosis/occlusion (ACAS/ACAO), and carotid angioplasty and stenting (CAS) have been used as an alternative, both CEA and CAS have limitations of their own, such as extensive invasiveness and in-stent restenosis.

Methods

In this study we established a novel interventional system in vitro to take advantage of both CEA and CAS. Twenty consecutive carotid atherosclerotic plaques were harvested from the patients who underwent CEA. The plaques were randomized into two groups and inserted into the pruned and sutured descending aortas of the swine in vitro. The ZebraScope™ was modified with a protective device on its flexible tip, so that the plaque could be dissected from the wall of parent carotid artery and ablated completely without damage to the carotid artery. The holmium:YAG (Ho:YAG) and thulium fiber laser (TFL) generators were alternately used when needed.

Results

All the carotid atherosclerotic plaques were completely ablated by Ho:YAG laser and/or TFL. The Ho:YAG laser was more effective for the atherosclerotic plaques with severe calcification, while the TFL was more suitable for those with moderate calcification. There were still some thermal injury spots on the inner wall of the parent carotid artery caused by the laser in the non-protected group B. In the protected group A, on the contrary, there was no even a thermal injury spot was found on the relevant location except for one sample. The difference of ablating duration was statistically significant between group A (36.5 ± 4.79 min) and group B (63.4 ± 6.55 min) (P < 0.01).

Conclusion

According to our knowledge, this is the first attempt to ablate carotid atherosclerotic plaques assisted by the ZebraScope™ in vitro. The protective and dissecting device on the tip of the angioscope makes it safe and visible when the ablation is performed to carotid atherosclerotic plaques. The Ho:YAG laser and TFL are effective and safe for ablating the plaque in vitro.

Head-to-head comparison of commercial artificial intelligence solutions for detection of large vessel occlusion at a comprehensive stroke center

Purpose

Despite the availability of commercial artificial intelligence (AI) tools for large vessel occlusion (LVO) detection, there is paucity of data comparing traditional machine learning and deep learning solutions in a real-world setting. The purpose of this study is to compare and validate the performance of two AI-based tools (RAPID LVO and CINA LVO) for LVO detection.

Materials and methods

This was a retrospective, single center study performed at a comprehensive stroke center from December 2020 to June 2021. CT angiography (n = 263) for suspected stroke were evaluated for LVO. RAPID LVO is a traditional machine learning model which primarily relies on vessel density threshold assessment, while CINA LVO is an end-to-end deep learning tool implemented with multiple neural networks for detection and localization tasks. Reasons for errors were also recorded.

Results

There were 29 positive and 224 negative LVO cases by ground truth assessment. RAPID LVO demonstrated an accuracy of 0.86, sensitivity of 0.90, specificity of 0.86, positive predictive value of 0.45, and negative predictive value of 0.98, while CINA demonstrated an accuracy of 0.96, sensitivity of 0.76, specificity of 0.98, positive predictive value of 0.85, and negative predictive value of 0.97.

Conclusion

Both tools successfully detected most anterior circulation occlusions. RAPID LVO had higher sensitivity while CINA LVO had higher accuracy and specificity. Interestingly, both tools were able to detect some, but not all M2 MCA occlusions. This is the first study to compare traditional and deep learning LVO tools in the clinical setting.

End-to-end artificial intelligence platform for the management of large vessel occlusions: A preliminary study

OBJECTIVES

In this study, we developed a deep learning pipeline that detects large vessel occlusion (LVO) and predicts functional outcome based on computed tomography angiography (CTA) images to improve the management of the LVO patients.

METHODS

A series identifier picked out 8650 LVO-protocoled studies from 2015 to 2019 at Rhode Island Hospital with an identified thin axial series that served as the data pool. Data were annotated into 2 classes: 1021 LVOs and 7629 normal. The Inception-V1 I3D architecture was applied for LVO detection. For outcome prediction, 323 patients undergoing thrombectomy were selected. A 3D convolution neural network (CNN) was used for outcome prediction (30-day mRS) with CTA volumes and embedded pre-treatment variables as inputs.

RESULT

For LVO-detection model, CTAs from 8,650 patients (median age 68 years, interquartile range (IQR): 58-81; 3934 females) were analyzed. The cross-validated AUC for LVO vs. not was 0.74 (95% CI: 0.72-0.75). For the mRS classification model, CTAs from 323 patients (median age 75 years, IQR: 63-84; 164 females) were analyzed. The algorithm achieved a test AUC of 0.82 (95% CI: 0.79-0.84), sensitivity of 89%, and specificity 66%. The two models were then integrated with hospital infrastructure where CTA was collected in real-time and processed by the model. If LVO was detected, interventionists were notified and provided with predicted clinical outcome information.

CONCLUSION

3D CNNs based on CTA were effective in selecting LVO and predicting LVO mechanical thrombectomy short-term prognosis. End-to-end AI platform allows users to receive immediate prognosis prediction and facilitates clinical workflow.

Pre-thrombectomy prognostic prediction of large-vessel ischemic stroke using machine learning: A systematic review and meta-analysis

Introduction

Machine learning (ML) methods are being increasingly applied to prognostic prediction for stroke patients with large vessel occlusion (LVO) treated with endovascular thrombectomy. This systematic review aims to summarize ML-based pre-thrombectomy prognostic models for LVO stroke and identify key research gaps.

Methods

Literature searches were performed in Embase, PubMed, Web of Science, and Scopus. Meta-analyses of the area under the receiver operating characteristic curves (AUCs) of ML models were conducted to synthesize model performance.

Results

Sixteen studies describing 19 models were eligible. The predicted outcomes include functional outcome at 90 days, successful reperfusion, and hemorrhagic transformation. Functional outcome was analyzed by 10 conventional ML models (pooled AUC=0.81, 95% confidence interval [CI]: 0.77-0.85, AUC range: 0.68-0.93) and four deep learning (DL) models (pooled AUC=0.75, 95% CI: 0.70-0.81, AUC range: 0.71-0.81). Successful reperfusion was analyzed by three conventional ML models (pooled AUC=0.72, 95% CI: 0.56-0.88, AUC range: 0.55-0.88) and one DL model (AUC=0.65, 95% CI: 0.62-0.68).

Conclusions

Conventional ML and DL models have shown variable performance in predicting post-treatment outcomes of LVO without generally demonstrating superiority compared to existing prognostic scores. Most models were developed using small datasets, lacked solid external validation, and at high risk of potential bias. There is considerable scope to improve study design and model performance. The application of ML and DL methods to improve the prediction of prognosis in LVO stroke, while promising, remains nascent.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021266524, identifier CRD42021266524.

Evaluation of the Rapid Arterial oCclusion Evaluation (RACE) scale in Upstate South Carolina, USA

OBJECTIVES

Several stroke assessments have been designed for Emergency Medical Services to identify stroke patients with large vessel occlusion in the prehospital setting. The Rapid Arterial oCclusion Evaluation scale was developed in Spain, yet only few United States-based studies have confirmed findings from Spain. This study was designed to determine if the Rapid Arterial oCclusion Evaluation scale is a valid prehospital stroke assessment for identifying large vessel occlusion patients in South Carolina, USA.

MATERIALS AND METHODS

The performance of the Rapid Arterial oCclusion Evaluation scale was determined by calculating the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy at each score. The discriminative power of the Rapid Arterial oCclusion Evaluation score was evaluated using receiver operator characteristics. Comparison of the Rapid Arterial oCclusion Evaluation Scale to the National Institute of Health Stroke Scale was assessed using the Spearman's coefficient.

RESULTS

The Rapid Arterial oCclusion Evaluation scale had an acceptable discriminative power (c = 0.71). A score of ≥5 had a sensitivity of 0.71, specificity of 0.65, positive predictive value of 0.24, negative predictive value of 0.93, and accuracy of 0.66. There was a significant correlation between the Rapid Arterial Cclusion Evaluation score and the National Institute of Health Stroke Scale (rho = 0.60).

CONCLUSION

The Rapid Arterial oCclusion Evaluation scale performed comparably to the National Institute of Health Stroke Scale in South Carolina; however, performed lower than Spain. Future studies should investigate patient demographics and emergency medical services training to determine if these variables contribute to the results found in this study.

Diagnostic Errors in Cerebrovascular Pathology: Retrospective Analysis of a Neuroradiology Database at a Large Tertiary Academic Medical Center

BACKGROUND AND PURPOSE

Diagnostic errors affect 2%-8% of neuroradiology studies, resulting in significant potential morbidity and mortality. This retrospective analysis of a large database at a single tertiary academic institution focuses on diagnostic misses in cerebrovascular pathology and suggests error-reduction strategies.

MATERIALS AND METHODS

CT and MR imaging reports from a consecutive database spanning 2015-2020 were searched for errors of attending physicians in cerebrovascular pathology. Data were collected on missed findings, study types, and interpretation settings. Errors were categorized as ischemic, arterial, venous, hemorrhagic, and "other."

RESULTS

A total of 245,762 CT and MR imaging neuroradiology examinations were interpreted during the study period. Vascular diagnostic errors were present in 165 reports, with a mean of 49.6 (SD, 23.3) studies on the shifts when an error was made, compared with 34.9 (SD, 19.2) on shifts without detected errors (P < .0001). Seventy percent of examinations occurred in the hospital setting; 93.3% of errors were perceptual; 6.7% were interpretive; and 93.9% (n = 155) were clinically significant (RADPEER 2B or 3B). The distribution of errors was arterial and ischemic each with 33.3%, hemorrhagic with 21.8%, and venous with 7.5%. Most errors involved brain MR imaging (30.3%) followed by head CTA (27.9%) and noncontrast head CT (26.1%). The most common misses were acute/subacute infarcts (25.1%), followed by aneurysms (13.7%) and subdural hematomas (9.7%).

CONCLUSIONS

Most cerebrovascular diagnostic errors were perceptual and clinically significant, occurred in the emergency/inpatient setting, and were associated with higher-volume shifts. Diagnostic errors could be minimized by adjusting search patterns to ensure vigilance on the sites of the frequently missed pathologies.

Characterizing reasons for stroke thrombectomy ineligibility among potential candidates transferred in a hub-and-spoke network

Background

Access to endovascular thrombectomy (EVT) is relatively limited. Hub-and-spoke networks seek to transfer appropriate large vessel occlusion (LVO) candidates to EVT-capable hubs. However, some patients are ineligible upon hub arrival, and factors that drive transfer inefficiencies are not well described. We sought to quantify EVT transfer efficiency and identify reasons for EVT ineligibility.

Methods

Consecutive EVT candidates presenting to 25 spokes from 2018-2020 with pre-transfer CTA-defined LVO and ASPECTS ≥6 were identified from a prospectively maintained database. Outcomes of interest included hub EVT, reasons for EVT ineligibility, and 90-day modified Rankin Scale (mRS) ≤2.

Results

Among 258 patients, the median age was 70 years (IQR 60-81); 50% were female. 56% were ineligible for EVT after hub arrival. Cited reasons were large established infarct (49%), mild symptoms (33%), recanalization (6%), distal occlusion (5%), sub-occlusive lesion (3%), and goals of care (3%). Late window patients [last known well (LKW) >6 hours] were more likely to be ineligible (67% vs 43%, P<0.0001). EVT ineligible patients were older (73 vs 68 years, p=0.04), had lower NIHSS (10 vs 16, p<0.0001), longer LKW-hub arrival time (8.4 vs 4.6 hours, p<0.0001), longer spoke Telestroke consult-hub arrival time (2.8 vs 2.2 hours, p<0.0001), and received less intravenous thrombolysis (32% vs 45%, p=0.04) compared to eligible patients. EVT ineligibility independently reduced the odds of 90-day mRS≤2 (aOR=0.26, 95%CI=0.12,0.56; p=0.001) when controlling for age, NIHSS, and LKW-hub arrival time.

Conclusions

Among patients transferred for EVT, there are multiple reasons for ineligibility upon hub arrival, with most excluded for infarct growth and mild symptoms. Understanding factors that drive transfer inefficiencies is important to improve EVT access and outcomes.

Tenecteplase or Alteplase Better in Patients with Acute Ischemic Stroke Due to Large Vessel Occlusion: A Single Center Observational Study

Background and Objectives: The study aimed to investigate the efficacy of intravenous thrombolysis with Tenecteplase before thrombectomy for acute ischemic stroke (AIS) patients compared with previous results using Alteplase. Previous trials for Tenecteplase have indicated an increased incidence of vascular reperfusion. In April 2021, we started to primarily give Tenecteplase to patients eligible to undergo thrombectomy. Materials and Methods: In this retrospective observational single-center non-randomized study, we analyzed directly admitted patients with AIS who had occlusion of the internal carotid, middle cerebral, or basilar artery and who underwent thrombectomy, as well as the recanalization rate for these patients at the first angiographic assessment (mTICI score 2b–3), and complications. Results: We included 184 patients (demographic characteristics did not differ between Tenecteplase and Alteplase groups (mean age 68.4 vs. 73.0 years; female sex 53.3% vs. 51.1%, NIHSS 14 (IQR 4–26) vs. 15 (2–31). Forty-five patients received Tenecteplase and 139 Alteplase before endovascular treatment (EVT). Pre-EVT (endovascular treatment) recanalization was more likely to occur with Tenecteplase rather than Alteplase (22.2% vs. 8.6%, p = 0.02). Successful reperfusion (mTICI 2b–3) after EVT was achieved in 155 patients (42 (93.4%) vs. 113 (81.3), p = 0.07). Hemorrhagic imbibition occurred in 15 (33.3%) Tenecteplase-treated patients compared with 39 (28.1%) Alteplase-treated patients (p = 0.5). Patients treated with Tenecteplase had higher odds of excellent functional outcome than Alteplase-treated patients (Tenecteplase 48.6% vs. Alteplase 26.1%; OR 0.37 (95% CI 0.17–0.81), p = 0.01). Conclusions: Tenecteplase (25 mg/kg) could have superior clinical efficacy over Alteplase for AIS patients with large-vessel occlusion (LVO), administered before EVT. The improvement in reperfusion rate and the better excellent functional outcome could come without an increased safety concern.

Cortical symptoms described in emergency calls for patients with suspected large vessel occlusion: a descriptive analysis of 157 emergency calls

Background

Emergency medical dispatchers typically use the dispatch code for suspected stroke when the caller brings up one or more symptoms from the face-arm-speech triad. Paramedics and emergency department physicians are trained to suspect large vessel occlusion stroke when the stroke patient presents with hemiparesis and cortical symptoms: neglect, aphasia, and conjugate eye deviation (CED). We hypothesized that these symptoms could be evident in the emergency call.

In this study, we aimed to describe common symptoms mentioned in the emergency calls for paramedic-suspected thrombectomy candidates. Secondly, we wanted to explore how the question about CED arises in the Finnish suspected stroke dispatch protocol. Our third aim was to find out if the symptoms brought up in suspected stroke and non-stroke dispatches differed from each other.

Methods

This was a retrospective study with a descriptive analysis of emergency calls for patients with paramedic-suspected large vessel occlusion stroke. We listened to the emergency calls for 157 patients transported to Tampere University Hospital, a Finnish comprehensive stroke centre. Two researchers listened for symptoms brought up in these calls and filled out a pre-planned case report form.

Results

Speech disturbance was the most common symptom brought up in 125 (80%) calls. This was typically described as an inability to speak any words (n = 65, 52% of calls with speech disturbance). Other common symptoms were falling down (n = 63, 40%) and facial asymmetry (n = 41, 26%). Suspicion of stroke was mentioned by 44 (28%) callers. When the caller mentioned unconsciousness the emergency dispatcher tended to use a non-stroke dispatch code. The dispatchers adhered poorly to the protocol and asked about CED in only 57% of suspected stroke dispatches. We found CED in 12 emergency calls and ten of these patients were diagnosed with large vessel occlusion.

Conclusion

In cases where paramedics suspected large vessel occlusion stroke, typical stroke symptoms were described during the emergency call. Speech disturbance was typically described as inability to say anything. It is possible to further develop suspected stroke dispatch protocols to recognize thrombectomy candidates from ischemic cortical signs such as global aphasia and CED.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12873-022-00706-5.

Development and validation of a prognostic nomogram based on objective nutritional indexes in ischemic stroke patients with large vessel occlusion undergoing endovascular thrombectomy

BACKGROUND AND AIMS

Preserved nutritional status in acute ischemic stroke patients with large vessel occlusion (LVO) undergoing endovascular thrombectomy (EVT) is important but lacks an effective evaluation method. We aimed to investigate the prognostic value of objective nutritional indexes (ONIs) in LVO patients after EVT that were validated by studies in patients with other vascular diseases receiving intervention therapy and to develop a functional prediction nomogram for better stroke management.

METHODS AND RESULTS

LVO patients undergoing EVT from 2016 to 2020 were retrospectively enrolled and randomly classified into training and validation cohorts at a ratio of 7:3. The ONIs, including the Controlling Nutritional Status (CONUT) score, Nutritional Risk Index (NRI), and Prognostic Nutritional Index (PNI), were calculated. A stepwise logistic regression model for 3-month poor functional outcome based on the smallest Akaike information criterion was employed to develop the nomogram, and the nomogram's determination and clinical use were tested by area under the curve (AUC), calibration plots, and decision curve analysis and compared with three earlier prognostic models. A total of 418 patients were enrolled. The CONUT independently related and increased the risk of 3-month poor functional outcome with an OR of 1.387 (95% CI: 1.133-1.698, p = 0.002). A nomogram including CONUT and other seven factors (AIC = 274.568) was developed. The AUC of the nomogram was 0.847 (95% CI: 0.799-0.894) and 0.836 (95% CI: 0.755-0.916) in the training and validation cohort, respectively, with better predictive performance and clinical utility than previous models.

CONCLUSION

The CONUT independently related to the poor functional outcome, and the newly established nomogram reliably predicted the functional outcome in LVO patients after EVT.

Baseline Characteristics Associated with Good Collateral Status Using Hypoperfusion Index as an Outcome

Up to 30% of ischemic stroke cases are due to large vessel occlusion (LVO), causing significant morbidity. Studies have shown that the collateral circulation of patients with acute ischemic stroke (AIS) secondary to LVO can predict their clinical and radiological outcomes. The aim of this study is to identify baseline patient characteristics that can help predict the collateral status of these patients for improved triage. In this IRB approved retrospective study, consecutive patients presenting with AIS secondary to anterior circulation LVO were identified between September 2019 and August 2021. The baseline patient characteristics, laboratory values, imaging features and outcomes were collected using a manual chart review. From the 181 consecutive patients initially reviewed, 54 were confirmed with a clinical diagnosis of AIS and anterior circulation LVO. In patients with poor collateral status, the body mass index (BMI) was found to be significantly lower compared to those with good collateral status (26.4 ± 5.6 vs. 31.7 ± 12.3; p = 0.045). BMI of >35 kg/m2 was found to predict the presence of good collateral status. Age was found to be significantly higher (70.5 ± 9.6 vs. 58.9 ± 15.6; p = 0.034) in patients with poor collateral status and M1 strokes associated with older age and BMI.

Ischemic Stroke at a Tertiary Academic Hospital in Tanzania: A Prospective Cohort Study With a Focus on Presumed Large Vessel Occlusion

Background

Large vessel ischemic strokes account for more than one-third of all strokes associated with substantial morbidity and mortality without early intervention. The incidence of large vessel occlusion (LVO) is not known in sub-Saharan Africa (SSA). Definitive vessel imaging is not routinely available in resource-limited settings.

Aims

We aimed to investigate the burden and outcomes of presumed LVO among patients with ischemic stroke admitted to a large tertiary academic hospital in Tanzania.

Methods

This cohort study recruited all consenting first-ever ischemic stroke participants admitted at a tertiary hospital in Tanzania. Demographic data were recorded, and participants were followed up to 1 year using the modified Rankin Scale (mRS). A diagnosis of presumed LVO was made by a diagnostic neuroradiologist and interventional neurologist based on contiguous ischemic changes in a pattern consistent with proximal LVO on a non-contrast computed tomography head. We examined factors associated with presumed LVO using logistic regression analysis. Inter-observer Kappa was calculated.

Results

We enrolled 158 first-ever ischemic strokes over 8 months with a mean age of 59.7 years. Presumed LVO accounted for 39.2% [95% confidence interval (CI) 31.6–47.3%] and an overall meantime from the onset of stroke symptoms to hospital arrival was 1.74 days. Participants with presumed LVO were more likely to involve the middle cerebral artery (MCA) territory (70.9%), p < 0.0001. Independent factors on multivariate analysis associated with presumed LVO were hypertension [adjusted odds ratio (aOR) 5.74 (95% CI: 1.74–18.9)] and increased waist-hip ratio [aOR 7.20 (95% CI: 1.83–28.2)]. One-year mortality in presumed LVO was 80% when compared with 73.1% in participants without presumed LVO. The Cohen's Kappa inter-observer reliability between the diagnostic neuroradiologist and interventional neurologist was 0.847.

Conclusion

There is a high burden of presumed LVO associated with high rates of 1-year morbidity and mortality at a tertiary academic hospital in Tanzania. Efforts are needed to confirm these findings with definitive vessel imaging, promoting cost-effective preventive strategies to reduce the burden of non-communicable diseases (NCDs), and a call for adopting endovascular therapies to reduce morbidity and mortality.

Implications of COVID-19 to Stroke Medicine: An Epidemiological and Pathophysiological Perspective

The neurological complications of Coronavirus 2019 (COVID-19) including stroke have been documented in the recent literature. COVID-19-related inflammation is suggested to contribute to both a hypercoagulable state and haemorrhagic transformation, including in younger individuals. COVID-19 is associated with a heightened risk of ischaemic stroke. Haemorrhagic stroke in COVID-19 patients is associated with increased morbidity and mortality. Cerebral venous sinus thrombosis (CVST) accounts for <1% of stroke cases in the general population but has come to heightened public attention due to the increased risk associated with adenoviral COVID-19 vaccines. However, recent evidence suggests the prevalence of stroke is less in vaccinated individuals than in unvaccinated COVID-19 patients. This review evaluates the current evidence of COVID-19-related ischaemic and haemorrhagic stroke, with a focus on current epidemiology and inflammatory-linked pathophysiology in the field of vascular neurology and stroke medicine.

High Prevalence of Atrial Fibrillation in a Lithuanian Stroke Patient Cohort

Background and Objectives: Atrial fibrillation (AF) is the most common cardiac arrhythmia and is associated with a five-fold increased risk for acute ischemic stroke (AIS). We aimed to estimate the prevalence of AF in a Lithuanian cohort of stroke patients, and its impact on patients regarding case fatality, functional outcome, and health-related quality of life (HRQoL) at 90 days. Materials and Methods: A single-center prospective study was carried out for four non-consecutive months between December 2018 and July 2019 in one of the two comprehensive stroke centers in Eastern Lithuania. A telephone-based follow-up was conveyed at 90 days using the modified Rankin Scale (mRS) and EuroQoL five-dimensional three-level descriptive system (EQ-5D-3L) with a self-rated visual analog scale (EQ-VAS). One-year case fatality was investigated. Results: We included 238 AIS patients with a mean age of 71.4 ± 11.9 years of whom 45.0% were female. A striking 97 (40.8%) AIS patients had a concomitant AF, in 68 (70.1%) of whom the AF was pre-existing. The AIS patients with AF were at a significantly higher risk for a large vessel occlusion (LVO; odds ratio 2.72 [95% CI 1.38−5.49], p = 0.004), and had a more severe neurological impairment at presentation (median NIHSS score (interquartile range): 9 (6−16) vs. 6 (3−9), p < 0.001). The LVO status was only detected in those who had received computed tomography angiography. Fifty-five (80.9%) patients with pre-existing AF received insufficient anticoagulation at stroke onset. All patients received a 12-lead ECG, however, in-hospital 24-h Holter monitoring was only performed in 3.4% of AIS patients without pre-existing AF. Although multivariate analyses found no statistically significant difference in one-year stroke patient survival and favorable functional status (mRS 0−2) at 90 days, when adjusted for age, gender, reperfusion treatment, baseline functional status, and baseline NIHSS, stroke patients with AF had a significantly poorer self-perceived HRQoL, indicated by a lower EQ-VAS score (regression coefficient ± standard error: β = −11.776 ± 4.850, p = 0.017). Conclusions: In our single-center prospective observational study in Lithuania, we found that 40.8% of AIS patients had a concomitant AF, were at a higher risk for an LVO, and had a significantly poorer self-perceived HRQoL at 90 days. Despite the high AF prevalence, diagnostic tools for subclinical AF were greatly underutilized.

Validation of a machine learning software tool for automated large vessel occlusion detection in patients with suspected acute stroke

PURPOSE

CT angiography (CTA) is the imaging standard for large vessel occlusion (LVO) detection in patients with acute ischemic stroke. StrokeSENS LVO is an automated tool that utilizes a machine learning algorithm to identify anterior large vessel occlusions (LVO) on CTA. The aim of this study was to test the algorithm's performance in LVO detection in an independent dataset.

METHODS

A total of 400 studies (217 LVO, 183 other/no occlusion) read by expert consensus were used for retrospective analysis. The LVO was defined as intracranial internal carotid artery (ICA) occlusion and M1 middle cerebral artery (MCA) occlusion. Software performance in detecting anterior LVO was evaluated using receiver operator characteristics (ROC) analysis, reporting area under the curve (AUC), sensitivity, and specificity. Subgroup analyses were performed to evaluate if performance in detecting LVO differed by subgroups, namely M1 MCA and ICA occlusion sites, and in data stratified by patient age, sex, and CTA acquisition characteristics (slice thickness, kilovoltage tube peak, and scanner manufacturer).

RESULTS

AUC, sensitivity, and specificity overall were as follows: 0.939, 0.894, and 0.874, respectively, in the full cohort; 0.927, 0.857, and 0.874, respectively, in the ICA occlusion cohort; 0.945, 0.914, and 0.874, respectively, in the M1 MCA occlusion cohort. Performance did not differ significantly by patient age, sex, or CTA acquisition characteristics.

CONCLUSION

The StrokeSENS LVO machine learning algorithm detects anterior LVO with high accuracy from a range of scans in a large dataset.

Patient and procedure selection for mechanical thrombectomy: Toward personalized medicine and the role of artificial intelligence

Mechanical thrombectomy (MT) for ischemic stroke due to large vessel occlusion is standard of care. Evidence-based guidelines on eligibility for MT have been outlined and evidence to extend the treatment benefit to more patients, particularly those at the extreme ends of a stroke clinical severity spectrum, is currently awaited. As patient selection continues to be explored, there is growing focus on procedure selection including the tools and techniques of thrombectomy and associated outcomes. Artificial intelligence (AI) has been instrumental in the area of patient selection for MT with a role in diagnosis and delivery of acute stroke care. Machine learning algorithms have been developed to detect cerebral ischemia and early infarct core, presence of large vessel occlusion, and perfusion deficit in acute ischemic stroke. Several available deep learning AI applications provide ready visualization and interpretation of cervical and cerebral arteries. Further enhancement of AI techniques to potentially include automated vessel probe tools in suspected large vessel occlusions is proposed. Value of AI may be extended to assist in procedure selection including both the tools and technique of thrombectomy. Delivering personalized medicine is the wave of the future and tailoring the MT treatment to a stroke patient is in line with this trend.

Internal Carotid Artery Occlusion: Management

PURPOSE OF REVIEW

Acute internal carotid artery occlusion (ICAO) is associated with high rates of morbidity and mortality, whereas chronic ICAO can present insidiously with recurrent strokes. In this review, we discuss the medical and surgical management approaches among patients with acute, subacute, and chronic ICAO.

RECENT FINDINGS

We reviewed the recent literature regarding clinical presentation of acute and chronic cases of ICAO, and discuss the current data, accepted guidelines, and prospects. Surgical, endovascular, or a combination (hybrid) revascularization has been shown to be effective in recanalization with improved functional outcomes in patients with ICAO in comparison to systemic thrombolysis or medical therapy alone. Future prospective or randomized clinical trials are warranted to elucidate the procedural superiority for revascularization of patients with ICAO.

CT angiographic radiomics signature for risk stratification in anterior large vessel occlusion stroke

BACKGROUND AND PURPOSE

As "time is brain" in acute stroke triage, the need for automated prognostication tools continues to increase, particularly in rapidly expanding tele-stroke settings. We aimed to create an automated prognostication tool for anterior circulation large vessel occlusion (LVO) stroke based on admission CTA radiomics.

METHODS

We automatically extracted 1116 radiomics features from the anterior circulation territory on admission CTAs of 829 acute LVO stroke patients who underwent mechanical thrombectomy in two academic centers. We trained, optimized, validated, and compared different machine-learning models to predict favorable outcome (modified Rankin Scale ≤ 2) at discharge and 3-month follow-up using four different input sets: "Radiomics", "Radiomics + Treatment" (radiomics, post-thrombectomy reperfusion grade, and intravenous thrombolysis), "Clinical + Treatment" (baseline clinical variables and treatment), and "Combined" (radiomics, treatment, and baseline clinical variables).

RESULTS

For discharge outcome prediction, models were optimized/trained on n = 494 and tested on an independent cohort of n = 100 patients from Yale. Receiver operating characteristic analysis of the independent cohort showed no significant difference between best-performing Combined input models (area under the curve, AUC = 0.77) versus Radiomics + Treatment (AUC = 0.78, p = 0.78), Radiomics (AUC = 0.78, p = 0.55), or Clinical + Treatment (AUC = 0.77, p = 0.87) models. For 3-month outcome prediction, models were optimized/trained on n = 373 and tested on an independent cohort from Yale (n = 72), and an external cohort from Geisinger Medical Center (n = 232). In the independent cohort, there was no significant difference between Combined input models (AUC = 0.76) versus Radiomics + Treatment (AUC = 0.72, p = 0.39), Radiomics (AUC = 0.72, p = 0.39), or Clinical + Treatment (AUC = 76, p = 0.90) models; however, in the external cohort, the Combined model (AUC = 0.74) outperformed Radiomics + Treatment (AUC = 0.66, p < 0.001) and Radiomics (AUC = 0.68, p = 0.005) models for 3-month prediction.

CONCLUSION

Machine-learning signatures of admission CTA radiomics can provide prognostic information in acute LVO stroke candidates for mechanical thrombectomy. Such objective and time-sensitive risk stratification can guide treatment decisions and facilitate tele-stroke assessment of patients. Particularly in the absence of reliable clinical information at the time of admission, models solely using radiomics features can provide a useful prognostication tool.

Impedance-based sensors discriminate among different types of blood thrombi with very high specificity and sensitivity

BACKGROUND

Intracranial occlusion recanalization fails in 20% of endovascular thrombectomy procedures, and thrombus composition is likely to be an important factor. In this study, we demonstrate that the combination of electrical impedance spectroscopy (EIS) and machine learning constitutes a novel and highly accurate method for the identification of different human thrombus types.

METHODS

134 samples, subdivided into four categories, were analyzed by EIS: 29 'White', 26 'Mixed', 12 'Red' thrombi, and 67 liquid 'Blood' samples. Thrombi were generated in vitro using citrated human blood from five healthy volunteers. Histological analysis was performed to validate the thrombus categorization based on red blood cell content. A machine learning prediction model was trained on impedance data to differentiate blood samples from any type of thrombus and in between the four sample categories.

RESULTS

Histological analysis confirmed the similarity between the composition of in vitro generated thrombi and retrieved human thrombi. The prediction model yielded a sensitivity/specificity of 90%/99% for distinguishing blood samples from thrombi and a global accuracy of 88% for differentiating among the four sample categories.

CONCLUSIONS

Combining EIS measurements with machine learning provides a highly effective approach for discriminating among different thrombus types and liquid blood. These findings raise the possibility of developing a probe-like device (eg, a neurovascular guidewire) integrating an impedance-based sensor. This sensor, placed in the distal part of the smart device, would allow the characterization of the probed thrombus on contact. The information could help physicians identify optimal thrombectomy strategies to improve outcomes for stroke patients.

Performance of the vision, aphasia, neglect (VAN) assessment within a single large EMS system

BACKGROUND

There is limited evidence on the performance of emergent large-vessel occlusion (LVO) stroke screening tools when used by emergency medical services (EMS) and emergency department (ED) providers. We assessed the validity and predictive value of the vision, aphasia, neglect (VAN) assessment when completed by EMS and in the ED among suspected stroke patients.

METHODS

We conducted a retrospective study of VAN performed by EMS providers and VAN inferred from the National Institutes of Health Stroke Scale performed by ED nurses at a single hospital. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of VAN by EMS and in the ED for LVO and a combined LVO and intracerebral hemorrhage (ICH) outcome.

RESULTS

From January 2018 to June 2020, 1,547 eligible patients were identified. Sensitivity and specificity of ED VAN were similar for LVO (72% and 74%, respectively), whereas EMS VAN was more sensitive (84%) than specific (68%). PPVs were low for both EMS VAN (26%) and ED VAN (21%) to detect LVO. Due to several VAN-positive ICHs, PPVs were substantially higher for both EMS VAN (44%) and ED VAN (39%) to detect LVO or ICH. EMS and ED VAN had high NPVs (97% and 96%, respectively).

CONCLUSIONS

Among suspected stroke patients, we found modest sensitivity and specificity of VAN to detect LVO for both EMS and ED providers. Moreover, the low PPV in our study suggests a significant number of patients with non-LVO ischemic stroke or ICH could be over-triaged with VAN.

A systematic review of cost-effectiveness analyses on endovascular thrombectomy in ischemic stroke patients

OBJECTIVE

The objective of this study was to examine the published cost-effectiveness analyses (CEAs) on endovascular thrombectomy (EVT) in acute stroke patients, with a particular focus on the practice of accounting for costs and utilities.

METHODS

We conducted a systematic review of published CEAs on EVT in acute stroke patients from 1/1/2009 to 10/1/2019. Published CEAs were searched in Ovid Embase, Ovid MEDLINE, and Web of Science. Cost or comparative effectiveness analyses were excluded. Risk of bias and quality assessment was based on the Consolidated Health Economic Evaluation Reporting Standard checklist.

RESULTS

Twenty-one studies were included in the final analysis, from the USA, Canada, Europe, Asia, and Australia. They all concluded EVT to be cost-effective, but with significant variations in methodology. Fifteen studies employed a long-term horizon (> 20 years), while only 11 incorporated risk of recurrent strokes. The willingness-to-pay (WTP) threshold varied from $10,000/quality-adjusted life year (QALY) to $120,000/QALY, with $50,000/QALY and $100,000/QALY being the most commonly used. Five studies undertook a societal perspective, but only one accounted for indirect costs. Seventeen studies based outcomes on 90-day modified Rankin Scale (mRS) scores, and 9 of these 17 studies grouped outcomes by mRS 0-2 and 3-5. Among these 9 studies, the range of QALY score reported for mRS 0-2 was 0.71-0.85 QALY, and that of mRS 3-5 was 0.21-0.40.

CONCLUSIONS

Our study reveals significant heterogeneity in previously published thrombectomy CEAs, highlighting need for better standardization in future CEAs.

KEY POINTS

• All included studies concluded thrombectomy to be cost-effective, from both long- and short-term perspectives. • Only 5 out of 22 studies undertook a societal perspective, and only 1 accounted for indirect costs. • The range of value for mRS 0-2 was 0.71-0.85 quality-adjusted life year (QALY) and 0.21-0.40 QALY for mRS 3-5.

A novel emergency medical services protocol to improve treatment time for large vessel occlusion strokes

In many systems, patients with large vessel occlusion (LVO) strokes experience delays in transport to thrombectomy-capable centers. This pilot study examined use of a novel emergency medical services (EMS) protocol to expedite transfer of patients with LVOs to a comprehensive stroke center (CSC). From October 1, 2020 to February 22, 2021, Indianapolis EMS piloted a protocol, in which paramedics, after transporting a patient with a possible stroke remained at the patient's bedside until released by the emergency department or neurology physician. In patients with possible LVO, EMS providers remained at the bedside until the clinical assessment and CT angiography (CTA) were complete. If indicated, the paramedics at bedside transferred the patient, via the same ambulance, to a nearby thrombectomy-capable CSC with which an automatic transfer agreement had been arranged. This five-month mixed methods study included case-control assessment of use of the protocol, number of transfers, safety during transport, and time saved in transfer compared to emergent transfers via conventional interfacility transfer agencies. In qualitative analysis EMS providers, and ED physicians and neurologists at both sending and receiving institutions, completed e-mail surveys on the process, and offered suggestions for process improvement. Responses were coded with an inductive content analysis approach. The protocol was used 42 times during the study period; four patients were found to have LVOs and were transferred to the CSC. There were no adverse events. Median time from decision-to-transfer to arrival at the CSC was 27.5 minutes (IQR 24.5-29.0), compared to 314.5 minutes (IQR 204.0-459.3) for acute non-stroke transfers during the same period. Major themes of provider impressions included: incomplete awareness of the protocol, smooth process, challenges when a stroke alert was activated after EMS left the hospital, greater involvement of EMS in patient care, and comments on communication and efficiency. This pilot study demonstrated the feasibility, safety, and efficiency of a novel approach to expedite endovascular therapy for patients with LVOs.

Stroke Core Volume Weighs More Than Recanalization Time for Predicting Outcome in Large Vessel Occlusion Recanalized Within 6 h of Symptoms Onset

Introduction

Current guidelines suggest that perfusion imaging should only be performed > 6 h after symptom onset. Pathophysiologically, brain perfusion should matter whatever the elapsed time. We aimed to compare relative contribution of recanalization time and stroke core volume in predicting functional outcome in patients treated by endovascular thrombectomy within 6-h of stroke-onset.

Methods

Consecutive patients presenting between January 2015 and June 2021 with (i) an acute ischaemic stroke due to an anterior proximal occlusion, (ii) a successful thrombectomy (TICI >2a) within 6-h of symptom-onset and (iii) CT perfusion imaging were included. Core stroke volume was automatically computed using RAPID software. Two linear regression models were built that included in the null hypothesis the pre-treatment NIHSS score and the hypoperfusion volume (Tmax > 6 s) as confounding variables and 24 h post-recanalization NIHSS and 90 days mRS as outcome variables. Time to recanalization was used as covariate in one model and stroke core volume as covariate in the other.

Results

From a total of 377 thrombectomies, 94 matched selection criteria. The Model null hypothesis explained 37% of the variability for 24 h post-recanalization NIHSS and 42% of the variability for 90 days MRS. The core volume as covariate increased outcome variability prediction to 57 and 56%, respectively. Time to recanalization as covariate marginally increased outcome variability prediction from 37 and 34% to 40 and 42.6%, respectively.

Conclusion

Core stroke volume better explains outcome variability in comparison to the time to recanalization in anterior large vessel occlusion stroke with successful thrombectomy done within 6 h of symptoms onset. Still, a large part of outcome variability prediction fails to be explained by the usual predictors.