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Purpose: Computed Tomography Angiography (CTA) is the first line of imaging in the diagnosis of Large Vessel Occlusion (LVO) strokes. We trained and independently validated end-to-end automated deep learning pipelines to predict 3-month outcomes after anterior circulation LVO thrombectomy based on admission CTAs. Methods: We split a dataset of 591 patients into training/cross-validation (n = 496) and independent test set (n = 95). We trained separate models for outcome prediction based on admission "CTA" images alone, "CTA + Treatment" (including time to thrombectomy and reperfusion success information), and "CTA + Treatment + Clinical" (including admission age, sex, and NIH stroke scale). A binary (favorable) outcome was defined based on a 3-month modified Rankin Scale ≤ 2. The model was trained on our dataset based on the pre-trained ResNet-50 3D Convolutional Neural Network ("MedicalNet") and included CTA preprocessing steps. Results: We generated an ensemble model from the 5-fold cross-validation, and tested it in the independent test cohort, with receiver operating characteristic area under the curve (AUC, 95% confidence interval) of 70 (0.59-0.81) for "CTA," 0.79 (0.70-0.89) for "CTA + Treatment," and 0.86 (0.79-0.94) for "CTA + Treatment + Clinical" input models. A "Treatment + Clinical" logistic regression model achieved an AUC of 0.86 (0.79-0.93). Conclusion: Our results show the feasibility of an end-to-end automated model to predict outcomes from admission and post-thrombectomy reperfusion success. Such a model can facilitate prognostication in telehealth transfer and when a thorough neurological exam is not feasible due to language barrier or pre-existing morbidities.
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PURPOSE: To create and validate an automated pipeline for detection of early signs of irreversible ischemic change from admission CTA in patients with large vessel occlusion (LVO) stroke. METHODS: We retrospectively included 368 patients for training and 143 for external validation. All patients had anterior circulation LVO stroke, endovascular therapy with successful reperfusion, and follow-up diffusion-weighted imaging (DWI). We devised a pipeline to automatically segment Alberta Stroke Program Early CT Score (ASPECTS) regions and extracted their relative Hounsfield unit (rHU) values. We determined the optimal rHU cut points for prediction of final infarction in each ASPECT region, performed 10-fold cross-validation in the training set, and measured the performance via external validation in patients from another institute. We compared the model with an expert neuroradiologist for prediction of final infarct volume and poor functional outcome. RESULTS: We achieved a mean area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity of 0.69±0.13, 0.69±0.09, 0.61±0.23, and 0.72±0.11 across all regions and folds in cross-validation. In the external validation cohort, we achieved a median [interquartile] AUC, accuracy, sensitivity, and specificity of 0.71 [0.68-0.72], 0.70 [0.68-0.73], 0.55 [0.50-0.63], and 0.74 [0.73-0.77], respectively. The rHU-based ASPECTS showed significant correlation with DWI-based ASPECTS (rS = 0.39, p<0.001) and final infarct volume (rS = -0.36, p<0.001). The AUC for predicting poor functional outcome was 0.66 (95%CI: 0.57-0.75). The predictive capabilities of rHU-based ASPECTS were not significantly different from the neuroradiologist's visual ASPECTS for either final infarct volume or functional outcome. CONCLUSIONS: Our study demonstrates the feasibility of an automated pipeline and predictive model based on relative HU attenuation of ASPECTS regions on baseline CTA and its non-inferior performance in predicting final infarction on post-stroke DWI compared to an expert human reader.
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Isquemia Encefálica , Humanos , Masculino , Femenino , Anciano , Estudios Retrospectivos , Persona de Mediana Edad , Isquemia Encefálica/diagnóstico por imagen , Imagen de Difusión por Resonancia Magnética/métodos , Accidente Cerebrovascular/diagnóstico por imagen , Angiografía por Tomografía Computarizada/métodos , Curva ROC , Anciano de 80 o más Años , Accidente Cerebrovascular Isquémico/diagnóstico por imagenRESUMEN
BACKGROUND: Central venous catheters (CVCs) play an indispensable role in clinical practice. Catheter malposition and tip migration can lead to severe complications. The authors present a case illustrating the endovascular management of inadvertent marginal sinus cannulation after an internal jugular vein (IJV) catheter tip migration. OBSERVATIONS: A triple-lumen CVC was inserted without complications into the right IJV of a patient undergoing a repeat sternotomy for aortic valve replacement. Two weeks postinsertion, it was discovered that the tip had migrated superiorly, terminating below the torcula in the posterior fossa. In the interventional suite, a three-dimensional venogram confirmed the inadvertent marginal sinus cannulation. The catheter was carefully retracted to the sigmoid sinus to preserve the option of catheter exchange if embolization became necessary. After a subsequent venogram, which displayed an absence of contrast extravasation, the entire catheter was safely removed. The patient tolerated the procedure well. LESSONS: Clinicians must be vigilant of catheter tip migration and malposition risks. Relying solely on postinsertion radiographs is insufficient. Once identified, prompt management of the malpositioned catheter is paramount in reducing morbidity and mortality and improving patient outcomes. Removing a malpositioned catheter constitutes a critical step, best performed by a specialized team under angiographic visualization.
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BACKGROUND AND OBJECTIVES: First pass effect (FPE) is a metric increasingly used to determine the success of mechanical thrombectomy (MT) procedures. However, few studies have investigated whether the duration of the procedure can modify the clinical benefit of FPE. We sought to determine whether FPE after MT for anterior circulation large vessel occlusion acute ischemic stroke is modified by procedural time (PT). METHODS: A multicenter, international data set was retrospectively analyzed for anterior circulation large vessel occlusion acute ischemic stroke treated by MT who achieved excellent reperfusion (thrombolysis in cerebral infarction 2c/3). The primary outcome was good functional outcome defined by 90-day modified Rankin scale scores of 0-2. The primary study exposure was first pass success (FPS, 1 pass vs ≥2 passes) and the secondary exposure was PT. We fit-adjusted logistic regression models and used marginal effects to assess the interaction between PT (≤30 vs >30 minutes) and FPS, adjusting for potential confounders including time from stroke presentation. RESULTS: A total of 1310 patients had excellent reperfusion. These patients were divided into 2 cohorts based on PT: ≤30 minutes (777 patients, 59.3%) and >30 minutes (533 patients, 40.7%). Good functional outcome was observed in 658 patients (50.2%). The interaction term between FPS and PT was significant ( P = .018). Individuals with FPS in ≤30 minutes had 11.5% higher adjusted predicted probability of good outcome compared with those who required ≥2 passes (58.2% vs 46.7%, P = .001). However, there was no significant difference in the adjusted predicted probability of good outcome in individuals with PT >30 minutes. This relationship appeared identical in models with PT treated as a continuous variable. CONCLUSION: FPE is modified by PT, with the added clinical benefit lost in longer procedures greater than 30 minutes. A comprehensive metric for MT procedures, namely, FPE 30 , may better represent the ideal of fast, complete reperfusion with a single pass of a thrombectomy device.
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BACKGROUND: A major driver of individual variation in long-term outcomes following a large vessel occlusion (LVO) stroke is the degree of collateral arterial circulation. We aimed to develop and evaluate machine-learning models that quantify LVO collateral status using admission computed tomography angiography (CTA) radiomics. METHODS: We extracted 1116 radiomic features from the anterior circulation territories from admission CTAs of 600 patients experiencing an acute LVO stroke. We trained and validated multiple machine-learning models for the prediction of collateral status based on consensus from two neuroradiologists as ground truth. Models were first trained to predict (1) good vs. intermediate or poor, or (2) good vs. intermediate or poor collateral status. Then, model predictions were combined to determine a three-tier collateral score (good, intermediate, or poor). We used the receiver operating characteristics area under the curve (AUC) to evaluate prediction accuracy. RESULTS: We included 499 patients in training and 101 in an independent test cohort. The best-performing models achieved an averaged cross-validation AUC of 0.80 ± 0.05 for poor vs. intermediate/good collateral and 0.69 ± 0.05 for good vs. intermediate/poor, and AUC = 0.77 (0.67-0.87) and AUC = 0.78 (0.70-0.90) in the independent test cohort, respectively. The collateral scores predicted by the radiomics model were correlated with (rho = 0.45, p = 0.002) and were independent predictors of 3-month clinical outcome (p = 0.018) in the independent test cohort. CONCLUSIONS: Automated tools for the assessment of collateral status from admission CTA-such as the radiomics models described here-can generate clinically relevant and reproducible collateral scores to facilitate a timely treatment triage in patients experiencing an acute LVO stroke.
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Importance: Intracerebral hemorrhage (ICH) is a serious complication of brain arteriovenous malformation (AVM). Apolipoprotein E (APOE) ε4 is a well-known genetic risk factor for ICH among persons without AVM, and cerebral amyloid angiopathy is a vasculopathy frequently observed in APOE ε4 carriers that may increase the risk of ICH. Objective: To assess whether APOE ε4 is associated with a higher risk of ICH in patients with a known AVM. Design, Setting, and Participants: This cross-sectional study including 412 participants was conducted in 2 stages (discovery and replication) using individual-level data from the UK Biobank (released March 2012 and last updated October 2023) and the All of Us Research Program (commenced on May 6, 2018, with its latest update provided in October 2023). The occurrence of AVM and ICH was ascertained at the time of enrollment using validated International Classification of Diseases, Ninth Revision and Tenth Revision, codes. Genotypic data on the APOE variants rs429358 and rs7412 were used to ascertain the ε status. Main Outcomes and Measures: For each study, the association between APOE ε4 variants and ICH risk was assessed among patients with a known AVM by using multivariable logistic regression. Results: The discovery phase included 253 UK Biobank participants with known AVM (mean [SD] age, 56.6 [8.0] years, 119 [47.0%] female), of whom 63 (24.9%) sustained an ICH. In the multivariable analysis of 240 participants of European ancestry, APOE ε4 was associated with a higher risk of ICH (odds ratio, 4.58; 95% CI, 2.13-10.34; P < .001). The replication phase included 159 participants with known AVM enrolled in All of Us (mean [SD] age, 57.1 [15.9] years; 106 [66.7%] female), of whom 29 (18.2%) sustained an ICH. In multivariable analysis of 101 participants of European ancestry, APOE ε4 was associated with higher risk of ICH (odds ratio, 4.52; 95% CI, 1.18-19.38; P = .03). Conclusions and Relevance: The results of this cross-sectional study of patients from the UK Biobank and All of Us suggest that information on APOE ε4 status may help identify patients with brain AVM who are at particularly high risk of ICH and that cerebral amyloid angiopathy should be evaluated as a possible mediating mechanism of the observed association.
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Apolipoproteína E4 , Hemorragia Cerebral , Malformaciones Arteriovenosas Intracraneales , Femenino , Humanos , Masculino , Persona de Mediana Edad , Apolipoproteína E4/genética , Encéfalo/irrigación sanguínea , Angiopatía Amiloide Cerebral/complicaciones , Hemorragia Cerebral/etiología , Hemorragia Cerebral/genética , Estudios Transversales , Malformaciones Arteriovenosas Intracraneales/complicacionesRESUMEN
BACKGROUND: Patients with ischemic stroke and concomitant COVID-19 infection have worse outcomes than those without this infection, but the impact of COVID-19 on hemorrhagic stroke remains unclear. We aimed to assess if COVID-19 worsens outcomes in intracerebral hemorrhage (ICH). METHODS AND RESULTS: We conducted an observational study of ICH outcomes using Get With The Guidelines Stroke data. We compared patients with ICH who were COVID-19 positive and negative during the pandemic (March 2020-February 2021) and prepandemic (March 2019-February 2020). Main outcomes were poor functional outcome (defined as a modified Rankin scale score of 4 to 6 at discharge), mortality, and discharge to a skilled nursing facility or hospice. The first stage included 60 091 patients with ICH who were COVID-19 negative and 1326 COVID-19 positive. In multivariable analyses, patients with ICH with versus without COVID-19 infection had 68% higher odds of poor outcome (odds ratio [OR], 1.68 [95% CI, 1.41-2.01]), 51% higher odds of mortality (OR, 1.51 [95% CI, 1.33-1.71]), and 66% higher odds of being discharged to a skilled nursing facility/hospice (OR, 1.66 [95% CI, 1.43-1.93]). The second stage included 62 743 prepandemic and 64 681 intrapandemic cases with ICH. In multivariable analyses, patients with ICH admitted during versus before the COVID-19 pandemic had 10% higher odds of poor outcomes (OR, 1.10 [95% CI, 1.07-1.14]), 5% higher mortality (OR, 1.05 [95% CI, 1.02-1.08]), and no significant difference in the risk of being discharged to a skilled nursing facility/hospice (OR, 0.93 [95% CI, 0.90-0.95]). CONCLUSIONS: The pathophysiology of the COVID-19 infection and changes in health care delivery during the pandemic played a role in worsening outcomes in the patient population with ICH.
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COVID-19 , Accidente Cerebrovascular , Humanos , Pandemias , COVID-19/epidemiología , Hemorragia Cerebral , PacientesRESUMEN
BACKGROUND: Frailty is a prevalent state associated with several aging-related traits and conditions. The relationship between frailty and stroke remains understudied. Here we aim to investigate whether the hospital frailty risk score (HFRS) is associated with the risk of stroke and determine whether a significant association between genetically determined frailty and stroke exists. DESIGN: Observational study using data from All of Us research program and Mendelian Randomization analyses. METHODS: Participants from All of Us with available electronic health records were selected for analysis. All of Us began national enrollment in 2018 and is expected to continue for at least 10 years. All of Us is recruiting members of groups that have traditionally been underrepresented in research. All participants provided informed consent at the time of enrollment, and the date of consent was recorded for each participant. Incident stroke was defined as stroke event happening on or after the date of consent to the All of Us study HFRS was measured with a 3-year look-back period before the date of consent for stroke risk. The HFRS was stratified into 4 categories: no-frailty (HFRS=0), low (HFRS ≥1 and <5), intermediate (≥5 and <15), and high (HFRS ≥15). Last, we implemented Mendelian Randomization analyses to evaluate whether genetically determined frailty is associated with stroke risk. RESULTS: Two hundred fifty-three thousand two hundred twenty-six participants were at risk of stroke. In multivariable analyses, frailty status was significantly associated with risk of any (ischemic or hemorrhagic) stroke following a dose-response way: not-frail versus low HFRS (HR, 4.9 [CI, 3.5-6.8]; P<0.001), not-frail versus intermediate HFRS (HR, 11.4 [CI, 8.3-15.7]; P<0.001) and not-frail versus high HFRS (HR, 42.8 [CI, 31.2-58.6]; P<0.001). We found similar associations when evaluating ischemic and hemorrhagic stroke separately (P value for all comparisons <0.05). Mendelian Randomization confirmed this association by indicating that genetically determined frailty was independently associated with risk of any stroke (OR, 1.45 [95% CI, 1.15-1.84]; P=0.002). CONCLUSIONS: Frailty, based on the HFRS was associated with higher risk of any stroke. Mendelian Randomization analyses confirmed this association providing evidence to support a causal relationship.
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Accidente Cerebrovascular Hemorrágico , Salud Poblacional , Accidente Cerebrovascular , Humanos , Accidente Cerebrovascular/epidemiología , Accidente Cerebrovascular/genética , Factores de Riesgo , Hospitales , Estudios RetrospectivosRESUMEN
BACKGROUND: Intratumoral aneurysms in highly vascular brain tumors can complicate resection depending on their location and feasibility of proximal control. Seemingly unrelated neurological symptoms may be from vascular steal that can help alert the need for additional vascular imaging and augmenting surgical strategies. OBSERVATIONS: A 29-year-old female presented with headaches and unilateral blurred vision, secondary to a large right frontal dural-based lesion with hypointense signal thought to represent calcifications. Given these latter findings and clinical suspicion for a vascular steal phenomenon to explain the blurred vision, computed tomography angiography was obtained, revealing a 4 × 2-mm intratumoral aneurysm. Diagnostic cerebral angiography confirmed this along with vascular steal by the tumor from the right ophthalmic artery. The patient underwent endovascular embolization of the intratumoral aneurysm, followed by open tumor resection in the same setting without complication, minimal blood loss, and improvement in her vision. LESSONS: Understanding the blood supply of any tumor, but highly vascular ones in particular, and the relationship with normal vasculature is undeniably important in avoiding potentially dangerous situations and optimizing maximal safe resection. Recognition of highly vascular tumors should prompt thorough understanding of the vascular supply and relationship of intracranial vasculature with consideration of endovascular adjuncts when appropriate.
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BACKGROUND: Andexanet alfa (AA), a factor Xa-inhibitor (FXi) reversal agent, is given as a bolus followed by a 2-hour infusion. This long administration time can delay EVD placement in intracerebral hemorrhage (ICH) patients. We sought to evaluate the safety of EVD placement immediately post-AA bolus compared to post-AA infusion. METHODS: We conducted a retrospective study that included adult patients admitted with FXi-associated ICH who received AA and underwent EVD placement The primary outcome was the occurrence of a new hemorrhage (tract, extra-axial, or intraventricular hemorrhage). Secondary outcomes included mortality, intensive care unit and hospital length of stay, and discharge modified Rankin Score. The primary safety outcome was documented thrombotic events. RESULTS: Twelve patients with FXi related ICH were included (EVD placement post-AA bolus, N = 8; EVD placement post-AA infusion, N = 4). Each arm included one patient with bilateral EVD placed. There was no difference in the incidence of new hemorrhages, with one post-AA bolus patient had small, focal, nonoperative extra-axial hemorrhage. Morbidity and mortality were higher in post-AA infusion patients (mRS, post-AA bolus, 4 [4-6] vs. post-AA infusion 6 [5,6], p = 0.24 and post-AA bolus, 3 (37.5 %) vs. post-AA infusion, 3 (75 %), p = 0.54, respectively). One patient in the post-AA bolus group had thrombotic event. There was no difference in hospital LOS (post-AA bolus, 19 days [12-26] vs. post-AA infusion, 14 days [9-22], p = 0.55) and ICU LOS (post-AA bolus, 10 days [6-13] vs. post-AA infusion, 11 days [5-21], p = 0.86). CONCLUSION: We report no differences in the incidence of tract hemorrhage, extra-axial hemorrhage, or intraventricular hemorrhage post-AA bolus versus post-AA infusion. Larger prospective studies to validate these results are warranted.
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Factor Xa , Trombosis , Adulto , Humanos , Inhibidores del Factor Xa , Estudios Retrospectivos , Estudios Prospectivos , Hemorragia Cerebral/cirugía , Fibrinolíticos , Drenaje/métodos , Proteínas RecombinantesAsunto(s)
Fragilidad , Hidrocéfalo Normotenso , Hidrocefalia , Humanos , Hidrocéfalo Normotenso/cirugía , Hidrocéfalo Normotenso/etiología , Derivación Ventriculoperitoneal/efectos adversos , Readmisión del Paciente , Fragilidad/cirugía , Hidrocefalia/cirugía , Hidrocefalia/etiología , Factores de RiesgoRESUMEN
OBJECTIVE: The aim of this study was to evaluate the impact of a Hospital Frailty Risk Score (HFRS) on unplanned readmission and health care resource utilization in normal pressure hydrocephalus (NPH) patients undergoing a ventriculoperitoneal (VP) shunt surgery. METHODS: A retrospective cohort study was performed using the 2016-2019 Nationwide Readmission Database. All NPH patients (≥60 years) undergoing a VP shunt surgery were identified using ICD-10-CM diagnostic and procedural codes. Patients were dichotomized into 2 cohorts as follows: Low HFRS (<5) and Intermediate-High HFRS (≥5). A multivariate logistic regression analysis was then used to identify independent predictors of adverse event (AE) and 30- and 90-day readmission. RESULTS: Of 13,262 patients, 4386 (33.1%) had an Intermediate-High HFRS score. A greater proportion of the Intermediate-High HFRS cohort experienced at least one AE (1.9 vs. 22.1, P < 0.001). The Intermediate-High HFRS cohort also had a longer length of stay (2.3 ± 2.4 days vs. 7.0 ± 7.7 days, P < 0.001), higher non-routine discharge rate (19.9% vs. 39.9%, P < 0.001), and greater admission cost ($14,634 ± 5703 vs. $21,749 ± 15,234, P < 0.001). The Intermediate-High HFRS cohort had higher rates of 30- (7.6% vs. 11.0%, P < 0.001) and 90-day (6.8% vs. 8.3%, P < 0.001) readmissions. On a multivariate regression analysis, Intermediate-High HFRS compared to Low HFRS was an independent predictor of any AE (odds ratio, 16.6; 95% confidence interval, [12.9-21.5]; P < 0.001) and 30-day readmission (odds ratio, 1.4; 95% confidence interval, [1.2-1.7]; P < 0.001). CONCLUSIONS: Our study suggests that frailty, as defined by HFRS, is associated with increased resource utilization in NPH patients undergoing VP shunt surgery. Furthermore, HFRS was an independent predictor of adverse events and 30-day hospital readmission.
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Fragilidad , Hidrocéfalo Normotenso , Humanos , Hidrocéfalo Normotenso/cirugía , Hidrocéfalo Normotenso/etiología , Derivación Ventriculoperitoneal/efectos adversos , Readmisión del Paciente , Estudios Retrospectivos , Fragilidad/diagnóstico , Fragilidad/epidemiología , Fragilidad/etiología , Factores de Riesgo , HospitalesRESUMEN
BACKGROUND: Intracranial aneurysms and pituitary adenomas are relatively common pathologies that, in rare instances, may concurrently present. Their management poses considerable clinical and technical challenges. OBSERVATIONS: The authors present a case of a 66-year-old female patient with a fusiform aneurysm of the left internal carotid artery associated with a symptomatic pituitary macroadenoma that had been causing visual deficits for the past several years. She underwent successful placement of flow diverter stents across her aneurysm, followed by routine dual antiplatelet therapy to maintain stent patency. She underwent frequent serial radiographic, endocrine, and ophthalmological evaluations during this time to ensure stability of her pituitary adenoma. Following confirmation of aneurysm obliteration and subsequent de-escalation of antiplatelet medications to aspirin monotherapy, her tumor was subsequently resected via an endoscopic endonasal approach in a delayed fashion. LESSONS: The authors review the literature regarding management of these concurrent pathologies and describe the aspects of the case that led them to their chosen treatment strategy. An algorithm is proposed regarding the management of parasellar aneurysms with a concurrent diagnosis of pituitary tumor pathology.
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With advances in high-throughput image processing technologies and increasing availability of medical mega-data, the growing field of radiomics opened the door for quantitative analysis of medical images for prediction of clinically relevant information. One clinical area in which radiomics have proven useful is stroke neuroimaging, where rapid treatment triage is vital for patient outcomes and automated decision assistance tools have potential for significant clinical impact. Recent research, for example, has applied radiomics features extracted from CT angiography (CTA) images and a machine learning framework to facilitate risk-stratification in acute stroke. We here provide methodological guidelines and radiomics data supporting the referenced article "CT angiographic radiomics signature for risk-stratification in anterior large vessel occlusion stroke." The data were extracted from the stroke center registry at Yale New Haven Hospital between 1/1/2014 and 10/31/2020; and Geisinger Medical Center between 1/1/2016 and 12/31/2019. It includes detailed radiomics features of the anterior circulation territories on admission CTA scans in stroke patients with large vessel occlusion stroke who underwent thrombectomy. We also provide the methodological details of the analysis framework utilized for training, optimization, validation and external testing of the machine learning and feature selection algorithms. With the goal of advancing the feasibility and quality of radiomics-based analyses to improve patient care within and beyond the field of stroke, the provided data and methodological support can serve as a baseline for future studies applying radiomics algorithms to machine-learning frameworks, and allow for analysis and utilization of radiomics features extracted in this study.
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INTRODUCTION: The purpose of this study was to report our initial experience of using a large-bore (0.096â³ inner diameter) access catheter in neurovascular interventions. METHODS: Data were retrospectively collected from 5 sites in the US for neurovascular procedures performed using a large-bore access catheter. The effectiveness outcome was technical success, defined as the access catheter's successfully reaching its target vessel without conversion to direct carotid puncture or to a smaller-bore access catheter and successfully completing the intended neurointervention. RESULTS: One hundred and thirteen procedures performed in 112 patients were included in this study. The mean age of the patients was 67.5 years (SD 16.2), and about half (49.1%) were female. The most common primary access sites were the femoral (64.6%) or radial (32.7%) artery. Challenging anatomic variations included severe vessel tortuosity (26/81, 32.1%), type II aortic arch (17/88, 19.3%), type III aortic arch (14/88, 15.9%), bovine arch (16/104, 15.4%), severe angle (<30°) between the subclavian and target vessel (11/74, 14.9%), and subclavian loop (7/79, 8.9%). The median access time to branch view was 18 min (IQR 11-28, N = 75). The technical success rate was 94.7%. Two dissections (1.8%) were related to the large-bore access catheter. Access site complications occurred in 2 patients (1.8%). Four additional symptomatic periprocedural complications not related to the large-bore access catheter occurred (7.1%). CONCLUSION: For neurovascular interventions, a 0.096â³ inner diameter access catheter could be used with both femoral and radial arterial approaches, had a high technical success rate, and had a low rate of periprocedural complications.
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Brain imaging is essential to the clinical care of patients with stroke, a leading cause of disability and death worldwide. Whereas advanced neuroimaging techniques offer opportunities for aiding acute stroke management, several factors, including time delays, inter-clinician variability, and lack of systemic conglomeration of clinical information, hinder their maximal utility. Recent advances in deep machine learning (DL) offer new strategies for harnessing computational medical image analysis to inform decision making in acute stroke. We examine the current state of the field for DL models in stroke triage. First, we provide a brief, clinical practice-focused primer on DL. Next, we examine real-world examples of DL applications in pixel-wise labeling, volumetric lesion segmentation, stroke detection, and prediction of tissue fate postintervention. We evaluate recent deployments of deep neural networks and their ability to automatically select relevant clinical features for acute decision making, reduce inter-rater variability, and boost reliability in rapid neuroimaging assessments, and integrate neuroimaging with electronic medical record (EMR) data in order to support clinicians in routine and triage stroke management. Ultimately, we aim to provide a framework for critically evaluating existing automated approaches, thus equipping clinicians with the ability to understand and potentially apply DL approaches in order to address challenges in clinical practice. ANN NEUROL 2022;92:574-587.
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Aprendizaje Profundo , Accidente Cerebrovascular , Humanos , Redes Neurales de la Computación , Neuroimagen/métodos , Reproducibilidad de los Resultados , Accidente Cerebrovascular/diagnóstico por imagen , Accidente Cerebrovascular/terapiaRESUMEN
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.
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Arteriopatías Oclusivas , Accidente Cerebrovascular , Humanos , Estudios Retrospectivos , Medición de Riesgo , Accidente Cerebrovascular/diagnóstico por imagen , Accidente Cerebrovascular/terapia , Trombectomía , Tomografía Computarizada por Rayos X , Resultado del TratamientoRESUMEN
OBJECTIVES: Improvements in acute stroke care have led to an increase in ischemic stroke survivors, who are at risk for development of post-ischemic stroke epilepsy (PISE). The impact of therapies such as thrombectomy and thrombolysis on risk of hospital revisits for PISE is unclear. We utilized administrative data to investigate the association between stroke treatment and PISE-related visits. MATERIALS AND METHODS: Using claims data from California, New York, and Florida, we performed a retrospective analysis of adult survivors of acute ischemic strokes. Patients with history of epilepsy, trauma, infections, or tumors were excluded. Included patients were followed for a primary outcome of revisits for seizures or epilepsy. Cox proportional hazards regression was used to identify covariates associated with PISE. RESULTS: In 595,545 included patients (median age 74 [IQR 21], 52% female), the 6-year cumulative rate of PISE-related revisit was 2.20% (95% CI 2.16-2.24). In multivariable models adjusting for demographics, comorbidities, and indicators of stroke severity, IV-tPA (HR 1.42, 95% CI 1.31-1.54, p<0.001) but not MT (HR 1.62, 95% CI 0.90-1.50, p=0.2) was associated with PISE-related revisit. Patients who underwent decompressive craniectomy experienced a 2-fold increase in odds for returning with PISE (HR 2.35, 95% CI 1.69-3.26, p<0.001). In-hospital seizures (HR 4.06, 95% CI 3.76-4.39, p<0.001) also elevated risk for PISE. SIGNIFICANCE: We demonstrate that ischemic stroke survivors who received IV-tPA, underwent decompressive craniectomy, or experienced acute seizures were at increased risk PISE-related revisit. Close attention should be paid to these patients with increased potential for long-term development of and re-hospitalization for PISE.
Asunto(s)
Epilepsia , Accidente Cerebrovascular Isquémico , Readmisión del Paciente , Anciano , Anciano de 80 o más Años , Epilepsia/etiología , Epilepsia/terapia , Femenino , Humanos , Accidente Cerebrovascular Isquémico/complicaciones , Accidente Cerebrovascular Isquémico/terapia , Masculino , Persona de Mediana Edad , Readmisión del Paciente/estadística & datos numéricos , Estudios RetrospectivosRESUMEN
We evaluated whether genetically elevated low-density lipoprotein cholesterol (LDL-C) levels are associated with lower risk of intracranial aneurysms and subarachnoid hemorrhage (IA/SAH). We conducted a 2-sample Mendelian randomization (MR) study. Our primary analysis used the inverse-variance weighted method. In secondary analyses, we implemented the MR-PRESSO method, restricted our analysis to LDL-C-specific instruments, and performed multivariate MR. A 1-mmol/l increase in genetically instrumented LDL-C levels was associated with a 17% lower risk of IA/SAH (odds ratio = 0.83, 95% confidence interval = 0.73-0.94, p = 0.004). Results remained consistent in secondary and multivariate analyses (all p < 0.05). Our results provide evidence for an inverse causal relationship between LDL-C levels and risk of IA/SAH. ANN NEUROL 2022;91:145-149.