Clinical-Radiological Parameters Improve the Prediction of the Thrombolysis Time Window by Both MRI Signal Intensities and DWI-FLAIR Mismatch

Background: With regard to acute stroke, patients with unknown time from stroke onset are not eligible for thrombolysis. Quantitative diffusion weighted imaging (DWI) and fluid attenuated inversion recovery (FLAIR) MRI relative signal intensity (rSI) biomarkers have been introduced to predict eligibility for thrombolysis, but have shown heterogeneous results in the past. In the present work, we investigated whether the inclusion of easily obtainable clinical-radiological parameters would improve the prediction of the thrombolysis time window by rSIs and compared their performance to the visual DWI-FLAIR mismatch. Methods: In a retrospective study, patients from 2 centers with proven stroke with onset <12 h were included. The DWI lesion was segmented and overlaid on ADC and FLAIR images. rSI mean and SD, were calculated as follows: (mean ROI value/mean value of the unaffected hemisphere). Additionally, the visual DWI-FLAIR mismatch was evaluated. Prediction of the thrombolysis time window was evaluated by the area-under-the-curve (AUC) derived from receiver operating characteristic (ROC) curve analysis. Factors such as the association of age, National Institutes of Health Stroke Scale, MRI field strength, lesion size, vessel occlusion and Wahlund-Score with rSI were investigated and the models were adjusted and stratified accordingly. Results: In 82 patients, the unadjusted rSI measures DWI-mean and -SD showed the highest AUCs (AUC 0.86-0.87). Adjustment for clinical-radiological covariates significantly improved the performance of FLAIR-mean (0.91) and DWI-SD (0.91). The best prediction results based on the AUC were found for the final stratified and adjusted models of DWI-SD (0.94) and FLAIR-mean (0.96) and a multivariable DWI-FLAIR model (0.95). The adjusted visual DWI-FLAIR mismatch did not perform in a significantly worse manner (0.89). ADC-rSIs showed fair performance in all models. Conclusions: Quantitative DWI and FLAIR MRI biomarkers as well as the visual DWI-FLAIR mismatch provide excellent prediction of eligibility for thrombolysis in acute stroke, when easily obtainable clinical-radiological parameters are included in the prediction models.

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Abstract WP50: MRI Biomarkers in Acute Stroke: Addition of Clinical Parameters Improves the Identification of Patients Eligible for Thrombolysis

Stroke ◽

10.1161/str.47.suppl_1.wp50 ◽

2016 ◽

Vol 47 (suppl_1) ◽

Author(s):

Vince I Madai ◽

Carla N Wood ◽

Ivana Galinovic ◽

Ulrike Grittner ◽

Sophie K Piper ◽

...

Keyword(s):

Acute Stroke ◽

Time Window ◽

Area Under The Curve ◽

Lesion Size ◽

Mean Value ◽

Quantitative Mri ◽

Stroke Onset ◽

Clinical Parameters ◽

Roc Curve Analysis ◽

Vessel Occlusion

Introduction: Patients with unknown time from stroke onset, e.g. in wake-up stroke, are not eligible for thrombolyic treatment. Relative signal intensities (rSI) of DWI and FLAIR MRI are biomarkers for eligibility for thrombolysis, but have shown heterogeneous results to date. We investigated if the addition of available clinical parameters improves the prediction of the thrombolysis time window in patients with acute stroke. Hypothesis: Inclusion of clinical parameters improves the prediction of the thrombolysis time window by quantitative MRI biomarkers Methods: Patients from two centers with proven stroke and stroke-onset <12 hours were included in a retrospective design. The DWI lesion was segmented and overlaid on ADC and FLAIR maps. rSI mean and standard deviation (std) were calculated: mean VOI value/mean value of the unaffected hemisphere. Prediction of the thrombolysis time window was evaluated by the area-under-the-curve (AUC) of receiver-operating-characteristic (ROC) curve analysis. Age, NIHSS, MRI field strength, lesion size, vessel occlusion and Wahlund-Score were included in adjusted and stratified regression models. Results: 82 patients were included. In the unadjusted analysis, DWI-mean and -std (AUC: 0.86, 0.87) performed best. Adjustment for clinical parameters significantly improved the performance of FLAIR-mean (0.87) and DWI-std (0.91). The best performance was found for the final stratified and adjusted models of DWI-std (0.94) and FLAIR-mean (0.96). ADC-rSIs showed no clinically acceptable performance in all models. Conclusion: rSIs of DWI and FLAIR MRI predict eligibility for thrombolysis in acute stroke with high precision, when easily available clinical parameters are included in the prediction.

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Pomona Large Vessel Occlusion Screening Tool for Prehospital and Emergency Room Settings

Interventional Neurology ◽

10.1159/000486515 ◽

2018 ◽

Vol 7 (3-4) ◽

pp. 196-203 ◽

Cited By ~ 2

Author(s):

Kessarin Panichpisal ◽

Kenneth Nugent ◽

Maharaj Singh ◽

Richard Rovin ◽

Reji Babygirija ◽

...

Keyword(s):

Los Angeles ◽

Acute Stroke ◽

Predictive Value ◽

Area Under The Curve ◽

Predictive Performance ◽

Large Vessel ◽

Stroke Severity ◽

Vessel Occlusion ◽

Comparable Accuracy ◽

Score Model

Background: Early identification of patients with acute ischemic strokes due to large vessel occlusions (LVO) is critical. We propose a simple risk score model to predict LVO. Method: The proposed scale (Pomona Scale) ranges from 0 to 3 and includes 3 items: gaze deviation, expressive aphasia, and neglect. We reviewed a cohort of all acute stroke activation patients between February 2014 and January 2016. The predictive performance of the Pomona Scale was determined and compared with several National Institutes of Health Stroke Scale (NIHSS) cutoffs (≥4, ≥6, ≥8, and ≥10), the Los Angeles Motor Scale (LAMS), the Cincinnati Prehospital Stroke Severity (CPSS) scale, the Vision Aphasia and Neglect Scale (VAN), and the Prehospital Acute Stroke Severity Scale (PASS). Results: LVO was detected in 94 of 776 acute stroke activations (12%). A Pomona Scale ≥2 had comparable accuracy to predict LVO as the VAN and CPSS scales and higher accuracy than Pomona Scale ≥1, LAMS, PASS, and NIHSS. A Pomona Scale ≥2 had an accuracy (area under the curve) of 0.79, a sensitivity of 0.86, a specificity of 0.70, a positive predictive value of 0.71, and a negative predictive value of 0.97 for the detection of LVO. We also found that the presence of either neglect or gaze deviation alone had comparable accuracy of 0.79 as Pomona Scale ≥2 to detect LVO. Conclusion: The Pomona Scale is a simple and accurate scale to predict LVO. In addition, the presence of either gaze deviation or neglect also suggests the possibility of LVO.

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Acute Stroke Management in the First 24 Hours

10.1093/med/9780190856519.001.0001 ◽

2018 ◽

Cited By ~ 1

Keyword(s):

Emergency Department ◽

Ischemic Stroke ◽

Acute Stroke ◽

Time Window ◽

Systems Of Care ◽

Treatment Decision ◽

Team Work ◽

Hospital Organization ◽

Vessel Occlusion ◽

Clinical Scenarios

Diagnosis and treatment of acute stroke has advanced considerably in the past 2 decades. Most notably, in cases of ischemic stroke, intravenous alteplase has become the standard of medical treatment despite its multiple contraindications and limited time window. More recently, trials have proven that endovascular thrombectomy is superior to medical therapy alone, advancing the standard of care for patients who present with acute ischemic stroke from a large vessel occlusion and salvageable brain tissue. The treatment of hemorrhagic stroke now involves the use of novel pharmacological agents and advanced minimally invasive technology. Important changes have also occurred at the levels of hospital organization and treatment decision-making. Such changes in organization and designation of hospitals with distinct levels of stroke care and the variety of stroke protocols now requires team work of emergency medical services (EMS), Emergency Department, stroke neurologists, neurosurgeons, and neurointerventionalists. This book provides an overview of the modern medical and surgical options for the treatment of patients with acute ischemic and hemorrhagic strokes. The pivotal role of EMS in prehospital evaluation and triage of a stroke patient and the levels of stroke systems of care are discussed. In addition, the current guidelines on the management of acute stroke, with the focus on early care of acute stroke patients at the Emergency Department and the first 24 hours of hospital admission, are reviewed. Each chapter contains a discussion of common clinical scenarios including initial management steps, practical points, and common pitfalls.

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Electroencephalography Might Improve Diagnosis of Acute Stroke and Large Vessel Occlusion

Stroke ◽

10.1161/strokeaha.120.030150 ◽

2020 ◽

Vol 51 (11) ◽

pp. 3361-3365 ◽

Cited By ~ 1

Author(s):

Fareshte Erani ◽

Nadezhda Zolotova ◽

Benjamin Vanderschelden ◽

Nima Khoshab ◽

Hagop Sarian ◽

...

Keyword(s):

Neural Network ◽

Emergency Department ◽

Deep Learning ◽

Acute Stroke ◽

Clinical Data ◽

Area Under The Curve ◽

Large Vessel ◽

Large Vessel Occlusion ◽

Vessel Occlusion ◽

Deep Learning Neural Network

Background and Purpose: Clinical methods have incomplete diagnostic value for early diagnosis of acute stroke and large vessel occlusion (LVO). Electroencephalography is rapidly sensitive to brain ischemia. This study examined the diagnostic utility of electroencephalography for acute stroke/transient ischemic attack (TIA) and for LVO. Methods: Patients (n=100) with suspected acute stroke in an emergency department underwent clinical exam then electroencephalography using a dry-electrode system. Four models classified patients, first as acute stroke/TIA or not, then as acute stroke with LVO or not: (1) clinical data, (2) electroencephalography data, (3) clinical+electroencephalography data using logistic regression, and (4) clinical+electroencephalography data using a deep learning neural network. Each model used a training set of 60 randomly selected patients, then was validated in an independent cohort of 40 new patients. Results: Of 100 patients, 63 had a stroke (43 ischemic/7 hemorrhagic) or TIA (13). For classifying patients as stroke/TIA or not, the clinical data model had area under the curve=62.3, whereas clinical+electroencephalography using deep learning neural network model had area under the curve=87.8. Results were comparable for classifying patients as stroke with LVO or not. Conclusions: Adding electroencephalography data to clinical measures improves diagnosis of acute stroke/TIA and of acute stroke with LVO. Rapid acquisition of dry-lead electroencephalography is feasible in the emergency department and merits prehospital evaluation.

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Establishment of a prediction model for early and mid-term complications for patients undergoing catheter insertion for peritoneal dialysis

Journal of International Medical Research ◽

10.1177/03000605211004524 ◽

2021 ◽

Vol 49 (4) ◽

pp. 030006052110045

Author(s):

Yibo Ma ◽

Shuiqing Liu ◽

Min Yang ◽

Yun Zou ◽

Dong Xue ◽

...

Keyword(s):

Peritoneal Dialysis ◽

Confidence Interval ◽

Prediction Model ◽

Prediction Models ◽

Multivariate Logistic Regression Analysis ◽

Area Under The Curve ◽

General Information ◽

Catheter Insertion ◽

Early Complications ◽

Roc Curve Analysis

Objective To investigate the factors involved in early and mid-term complications after catheter insertion for peritoneal dialysis and to establish prediction models. Methods A total of 158 patients with peritoneal dialysis in the Department of Nephrology of our hospital were retrospectively analyzed. General information, laboratory indices, early complications (within 1 month after the operation), mid-term complications (1–6 months after the operation), and other relevant data were recorded. Multivariate logistic regression analysis was performed to establish a prediction model of complications and generate a nomogram. Receiver operating characteristic (ROC) curve analysis was used to evaluate the efficacy of the model. Results Among the patients, 48 (30.8%) had early complications, which were mainly catheter-related complications, and 29 (18.4%) had mid-term complications, which were mainly abdominal infection and catheter migration. We constructed a prediction model for early complications (area under the curve = 0.697, 95% confidence interval: 0.609–0.785) and mid-term complications (area under the curve = 0.730, 95% confidence interval: 0.622–0.839). The sensitivity was 0.750 and 0.607, and the specificity was 0.589 and 0.765, respectively. Conclusions Our prediction model has clinical significance for risk assessment of early and mid-term complications and prevention of complications after catheterization for peritoneal dialysis.

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Global Epidemiology of Stroke and Access to Acute Ischemic Stroke Interventions

Neurology ◽

10.1212/wnl.0000000000012781 ◽

2021 ◽

Vol 97 (20 Supplement 2) ◽

pp. S6-S16

Author(s):

Vasu Saini ◽

Luis Guada ◽

Dileep R. Yavagal

Keyword(s):

Ischemic Stroke ◽

Acute Stroke ◽

Acute Ischemic Stroke ◽

Randomized Clinical Trials ◽

Time Window ◽

Systems Of Care ◽

Stroke Care ◽

Acute Stroke Care ◽

Vessel Occlusion ◽

Global Epidemiology

Purpose of the ReviewTo provide an up-to-date review of the incidence of stroke and large vessel occlusion (LVO) around the globe, as well as the eligibility and access to IV thrombolysis (IVT) and mechanical thrombectomy (MT) worldwide.Recent FindingsRandomized clinical trials have established MT with or without IVT as the usual care for patients with LVO stroke for up to 24 hours from symptom onset. Eligibility for IVT has extended beyond 4.5 hours based on permissible imaging criteria. With these advances in the last 5 years, there has been a notable increase in the population of patients eligible for acute stroke interventions. However, access to acute stroke care and utilization of MT or IVT is lagging in these patients.SummaryStroke is the second leading cause of both disability and death worldwide, with the highest burden of the disease shared by low- and middle-income countries. In 2016, there were 13.7 million new incident strokes globally; ≈87% of these were ischemic strokes and by conservative estimation about 10%–20% of these account for LVO. Fewer than 5% of patients with acute ischemic stroke received IVT globally in the eligible therapeutic time window and fewer than 100,000 MTs were performed worldwide in 2016. This highlights the large gap among eligible patients and the low utilization rates of these advances across the globe. Multiple global initiatives are underway to investigate interventions to improve systems of care and bridge this gap.

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Quality Assessment of CEUS in Individuals with Small Renal Masses—Which Individual Factors Are Associated with High Image Quality?

Journal of Clinical Medicine ◽

10.3390/jcm9124081 ◽

2020 ◽

Vol 9 (12) ◽

pp. 4081

Author(s):

Paul Spiesecke ◽

Thomas Fischer ◽

Frank Friedersdorff ◽

Bernd Hamm ◽

Markus Herbert Lerchbaumer

Keyword(s):

Image Quality ◽

Area Under The Curve ◽

Abdominal Ultrasound ◽

Lesion Size ◽

Individual Factors ◽

Renal Lesion ◽

Operating Characteristics ◽

Roc Curve Analysis ◽

Renal Masses ◽

Contrast Enhanced

Obesity and bowel gas are known to impair image quality in abdominal ultrasound (US). The present study aims at identifying individual factors in B-mode US that influence contrast-enhanced US (CEUS) image quality to optimize further imaging workup of incidentally detected focal renal masses. We retrospectively analyzed renal CEUS of focal renal masses ≤ 4 cm performed at our center in 143 patients between 2016 and 2020. Patient and lesion characteristics were tested for their influence on focal and overall image quality assessed by two experienced radiologists using Likert scales. Effects of significant variables were quantified by receiver operating characteristics (ROC) curve analysis with area under the curve (AUC), and combined effects were assessed by binary logistic regression. Shrunken kidney, kidney depth, lesion depth, lesion size, and exophytic lesion growth were found to influence focal renal lesion image quality, and all factors except lesion size also influenced overall image quality. Combination of all parameters except kidney depth best predicted good CEUS image quality showing an AUC of 0.91 (p < 0.001, 95%-CI 0.863–0.958). The B-mode US parameters investigated can identify patients expected to have good CEUS image quality and thus help select the most suitable contrast-enhanced imaging strategy for workup of renal lesions.

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Abstract TP253: A Novel Prehospital Scale to Predict Candidates for Acute Stroke Thrombectomy : The Fukuoka Acute Stroke ThrombEctomy pRediction (FASTER) Scale

Stroke ◽

10.1161/str.48.suppl_1.tp253 ◽

2017 ◽

Vol 48 (suppl_1) ◽

Author(s):

Yuichi Miyazaki ◽

Tomoyuki Tsumoto ◽

Ryu Matsuo ◽

Tetsuro Ago ◽

Masahiro Kamouchi ◽

...

Keyword(s):

Acute Stroke ◽

Predictive Value ◽

Area Under The Curve ◽

Arterial Occlusion ◽

Stroke Severity ◽

Vessel Occlusion ◽

Discriminative Performance ◽

Stroke Registry ◽

Intracranial Vessel ◽

Promising Tool

Background: We aimed to design a prehospital scale to predict candidates for endovascular thrombectomy (CET) in patients with acute ischemic stroke (AIS). Materials and methods: In the Fukuoka Stroke Registry, we identified 3,470 patients with AIS who were transferred by emergency medical service within 24 hours of stroke onset and underwent intracranial vessel evaluation on admission from September 2007 to December 2015. CET were defined as patients with causative occlusion of internal carotid artery, middle cerebral artery, or basilar artery, and National Institute of Health Stroke Scale (NIHSS) score ≥ 6. The Fukuoka Acute Stroke ThrombEctomy pRediction (FASTER) scale was developed with NIHSS items based on the predictive importance derived from random forest analysis to predict CET. The discriminative performance was compared with other published scales for large vessel occlusion. Results: The FASTER scale was designed comprising of 4 NIHSS items : one point each was given for extinction and inattention (NIHSS subscore ≥ 1), best gaze (≥ 1), best language (≥ 1), and motor arm (≥ 2). Receiver operator curves demonstrated that the area under the curve of the FASTER scale was significantly larger than that of the Cincinnati Prehospital Stroke Severity Scale (0.907 vs 0.881, p<0.001), and not significantly different from that of the Rapid Arterial oCclusion Evaluation scale (vs 0.910, p= 0.68). The FASTER scale score ≥2 showed sensitivity of 88.4%, specificity 82.3%, positive predictive value 51.3%, and negative predictive value 97.1% for detecting CET. Conclusion: The FASTER scale is a simple and promising tool that can identify CET in the prehospital setting.

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Acute Stroke Biomarkers: Are We There Yet?

Frontiers in Neurology ◽

10.3389/fneur.2021.619721 ◽

2021 ◽

Vol 12 ◽

Author(s):

Marie Dagonnier ◽

Geoffrey A. Donnan ◽

Stephen M. Davis ◽

Helen M. Dewey ◽

David W. Howells

Keyword(s):

Ischemic Stroke ◽

Acute Stroke ◽

Matrix Protein ◽

Time Window ◽

Onset Time ◽

Stroke Onset ◽

Blood Biomarkers ◽

Vessel Occlusion ◽

Specificity And Sensitivity ◽

Stroke Diagnosis

Background: Distinguishing between stroke subtypes and knowing the time of stroke onset are critical in clinical practice. Thrombolysis and thrombectomy are very effective treatments in selected patients with acute ischemic stroke. Neuroimaging helps decide who should be treated and how they should be treated but is expensive, not always available and can have contraindications. These limitations contribute to the under use of these reperfusion therapies.Aim: An alternative approach in acute stroke diagnosis is to identify blood biomarkers which reflect the body's response to the damage caused by the different types of stroke. Specific blood biomarkers capable of differentiating ischemic from hemorrhagic stroke and mimics, identifying large vessel occlusion and capable of predicting stroke onset time would expedite diagnosis and increase eligibility for reperfusion therapies.Summary of Review: To date, measurements of candidate biomarkers have usually occurred beyond the time window for thrombolysis. Nevertheless, some candidate markers of brain tissue damage, particularly the highly abundant glial structural proteins like GFAP and S100β and the matrix protein MMP-9 offer promising results. Grouping of biomarkers in panels can offer additional specificity and sensitivity for ischemic stroke diagnosis. Unbiased “omics” approaches have great potential for biomarker identification because of greater gene, protein, and metabolite coverage but seem unlikely to be the detection methodology of choice because of their inherent cost.Conclusion: To date, despite the evolution of the techniques used in their evaluation, no individual candidate or multimarker panel has proven to have adequate performance for use in an acute clinical setting where decisions about an individual patient are being made. Timing of biomarker measurement, particularly early when decision making is most important, requires urgent and systematic study.

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Diagnostic value of transcranial ultrasonography for selecting subjects with large vessel occlusion: a systematic review

The Ultrasound Journal ◽

10.1186/s13089-019-0143-6 ◽

2019 ◽

Vol 11 (1) ◽

Cited By ~ 1

Author(s):

Daria Antipova ◽

Leila Eadie ◽

Ashish Stephen Macaden ◽

Philip Wilson

Keyword(s):

Systematic Review ◽

Diagnostic Accuracy ◽

Acute Stroke ◽

Clinical Assessment ◽

Assessment Tools ◽

Large Vessel ◽

Cochrane Library ◽

Direct Transfer ◽

Large Vessel Occlusion ◽

Vessel Occlusion

Abstract Introduction A number of pre-hospital clinical assessment tools have been developed to triage subjects with acute stroke due to large vessel occlusion (LVO) to a specialised endovascular centre, but their false negative rates remain high leading to inappropriate and costly emergency transfers. Transcranial ultrasonography may represent a valuable pre-hospital tool for selecting patients with LVO who could benefit from rapid transfer to a dedicated centre. Methods Diagnostic accuracy of transcranial ultrasonography in acute stroke was subjected to systematic review. Medline, Embase, PubMed, Scopus, and The Cochrane Library were searched. Published articles reporting diagnostic accuracy of transcranial ultrasonography in comparison to a reference imaging method were selected. Studies reporting estimates of diagnostic accuracy were included in the meta-analysis. Results Twenty-seven published articles were selected for the systematic review. Transcranial Doppler findings, such as absent or diminished blood flow signal in a major cerebral artery and asymmetry index ≥ 21% were shown to be suggestive of LVO. It demonstrated sensitivity ranging from 68 to 100% and specificity of 78–99% for detecting acute steno-occlusive lesions. Area under the receiver operating characteristics curve was 0.91. Transcranial ultrasonography can also detect haemorrhagic foci, however, its application is largely restricted by lesion location. Conclusions Transcranial ultrasonography might potentially be used for the selection of subjects with acute LVO, to help streamline patient care and allow direct transfer to specialised endovascular centres. It can also assist in detecting haemorrhagic lesions in some cases, however, its applicability here is largely restricted. Additional research should optimize the scanning technique. Further work is required to demonstrate whether this diagnostic approach, possibly combined with clinical assessment, could be used at the pre-hospital stage to justify direct transfer to a regional thrombectomy centre in suitable cases.

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