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Background and Purpose Prediction of futile recanalization (FR), i.e. failure of long-term functional independence despite full reperfusion in mechanical thrombectomy (MT), is instrumental in patients undergoing endovascular therapy. Methods Retrospective single-center analysis of patients treated for anterior circulation LVO ensuing successful MT (mTICI 2c–3) between January 2014 and April 2019. FR was defined as modified Rankin Scale (mRS) 90 days after stroke onset > 2 or mRS > pre-stroke mRS. Multivariable analysis was performed with variables available before treatment initiation regarding their association with FR. Performance of the regression model was then compared with a model including parameters available after MT. Results Successful MT was experienced by 549/1146 patients in total. FR occurred in 262/549 (47.7%) patients. Independent predictors of FR were male sex, odds ratio (OR) with 95% confidence interval (CI) 1.98 (1.31–3.05, p 0.001), age (OR 1.05, CI 1.03–1.07, p p p 0.025), neutrophile-lymphocyte ratio (OR 1.03, CI 1.00–1.06, p 0.022), baseline ASPECTS (OR 0.77, CI 0.68–0.88, p p 0.016). The prediction model’s Area Under the Curve was 0.78 (CI 0.74–0.82) and increased with parameters available after MT to 0.86 (CI 0.83–0.89) with failure of early neurological improvement being the most important predictor of FR (OR 15.0, CI 7.2–33.8). Conclusion A variety of preinterventional factors may predict FR with substantial certainty, but the prediction model can still be improved by considering parameters only available after MT, in particular early neurological improvement.

BackgroundHyperdense artery sign (HAS) on non-contrast CT (NCCT) can indicate a large vessel occlusion (LVO) in patients with acute ischemic stroke. HAS detection belongs to routine reporting in patients with acute stroke and can help to identify patients in whom LVO is not initially suspected. We sought to evaluate automated HAS detection by commercial software and compared its performance to that of trained physicians against a reference standard.MethodsNon-contrast CT scans from 154 patients with and without LVO proven by CT angiography (CTA) were independently rated for HAS by two blinded neuroradiologists and an AI-driven algorithm (Brainomix®). Sensitivity and specificity were analyzed for the clinicians and the software. As a secondary analysis, the clot length was automatically calculated by the software and compared with the length manually outlined on CTA images as the reference standard.ResultsAmong 154 patients, 84 (54.5%) had CTA-proven LVO. HAS on the correct side was detected with a sensitivity and specificity of 0.77 (CI:0.66–0.85) and 0.87 (0.77–0.94), 0.8 (0.69–0.88) and 0.97 (0.89–0.99), and 0.93 (0.84–0.97) and 0.71 (0.59–0.81) by the software and readers 1 and 2, respectively. The automated estimation of the thrombus length was in moderate agreement with the CTA-based reference standard [intraclass correlation coefficient (ICC) 0.73].ConclusionAutomated detection of HAS and estimation of thrombus length on NCCT by the tested software is feasible with a sensitivity and specificity comparable to that of trained neuroradiologists.

Background and aim The aim of this study was to assess the diagnostic accuracy of e-CTA (product name) (Brainomix) in the automatic detection of large vessel occlusions in anterior circulation stroke. Methods Of 487 CT angiographies from patients with large vessel occlusions stroke, 327 were used to train the algorithm while the remaining cases together with 140 negative CT angiographies were used to validate its performance against ground truth. Of these 301 cases, 144 were randomly selected and used for an additional comparative analysis against 4 raters. Sensitivity, specificity, positive and negative predictive value (PPV and NPV), accuracy and level of agreement with ground truth (Cohen’s Kappa) were determined and compared to the performance of a neuroradiologist, a radiology resident, and two neurology residents. Results e-CTA had a sensitivity and specificity of 0.84 (0.77–0.89) and 0.96 (0.91–0.98) respectively for the detection of any large vessel occlusions on the correct side in the whole validation cohort. This performance was identical in the comparative analysis subgroup and was within the range of physicians at different levels of expertise: 0.86–0.97 and 0.91–1.00, respectively. For the detection of proximal occlusions, it was 0.92 (0.84–0.96) and 0.98 (0.94–1.00) for the whole cohort and 0.93 (0.80–0.98) and 1.00 (0.95–1.00) for the comparative analysis, respectively for e-CTA. The range was 0.8–0.97 for sensitivity and 0.97–1.00 for specificity for the four physicians. Conclusions The performance of e-CTA in detecting any large vessel occlusions is comparable to less experienced physicians but is similar to experienced physicians for detecting proximal large vessel occlusions.

Background and Purpose: Failure of early neurological improvement (fENI) despite successful mechanical thrombectomy in the anterior circulation is a clinically frequent occurrence. Purpose of this analysis was to define independent clinical, radiological, laboratory, or procedural predictors for fENI. Methods: Retrospective single-center analysis of patients treated for acute ischemic stroke in the anterior circulation ensuing successful mechanical thrombectomy between January 2014 and April 2019. Patients were compared according to fENI (equal or higher National Institutes of Health Stroke Scale) and ENI (lower National Institutes of Health Stroke Scale at discharge). Thirty-eight variables were examined in multivariable analysis for association with fENI. Results: Five hundred forty-nine out of 1146 patients experienced successful recanalization (modified Treatment in Cerebral Ischemia 2c-3). fENI occurred in 115/549 (20.9%) patients. Independent predictors of fENI were premorbid modified Rankin Scale (odds ratio [OR] per point [IC], 1.21 [1.00–1.46], P =0.049), end-stage renal failure (OR [IC], 12.18 [2.01–73.63], P =0.007), admission glucose (OR [IC], 1.018 [1.004–1.013] per mg/dL, P =0.001), bridging IV lysis (OR [IC], 0.57 [0.35–0.93], P : 0.024), time from groin puncture to final recanalization (OR [IC], 1.004 [1.001–1.007] per minute, P =0.015), general anesthesia during mechanical thrombectomy (OR, 2.41 [1.43–4.08], P P =0.004), and follow-up Alberta Stroke Program Early CT Score (OR [IC], 0.76 [0.69–0.84] per point, P P Conclusions: The extent of infarction and the involvement of motor cortex and internal capsule as well as higher premorbid modified Rankin Scale, end-stage renal failure, high glucose level on admission, absence of bridging IV lysis, general anesthesia, and a longer therapy interval are presumably independent predictors for fENI in patients with successful mechanical thrombectomy.

Supplemental material, sj-pdf-2-wso-10.1177_1747493021992592 for Diagnostic accuracy of automated occlusion detection in CT angiography using e-CTA by Fatih Seker, Johannes Alex Rolf Pfaff, Yahia Mokli, Anne Berberich, Rafael Namias, Steven Gerry, Simon Nagel, Martin Bendszus and Christian Herweh in International Journal of Stroke

Supplemental material, sj-pdf-3-wso-10.1177_1747493021992592 for Diagnostic accuracy of automated occlusion detection in CT angiography using e-CTA by Fatih Seker, Johannes Alex Rolf Pfaff, Yahia Mokli, Anne Berberich, Rafael Namias, Steven Gerry, Simon Nagel, Martin Bendszus and Christian Herweh in International Journal of Stroke

Supplemental material, sj-pdf-3-wso-10.1177_1747493021992592 for Diagnostic accuracy of automated occlusion detection in CT angiography using e-CTA by Fatih Seker, Johannes Alex Rolf Pfaff, Yahia Mokli, Anne Berberich, Rafael Namias, Steven Gerry, Simon Nagel, Martin Bendszus and Christian Herweh in International Journal of Stroke

Supplemental material, sj-pdf-1-wso-10.1177_1747493021992592 for Diagnostic accuracy of automated occlusion detection in CT angiography using e-CTA by Fatih Seker, Johannes Alex Rolf Pfaff, Yahia Mokli, Anne Berberich, Rafael Namias, Steven Gerry, Simon Nagel, Martin Bendszus and Christian Herweh in International Journal of Stroke

Supplemental material, sj-pdf-1-wso-10.1177_1747493021992592 for Diagnostic accuracy of automated occlusion detection in CT angiography using e-CTA by Fatih Seker, Johannes Alex Rolf Pfaff, Yahia Mokli, Anne Berberich, Rafael Namias, Steven Gerry, Simon Nagel, Martin Bendszus and Christian Herweh in International Journal of Stroke

Supplemental material, sj-pdf-2-wso-10.1177_1747493021992592 for Diagnostic accuracy of automated occlusion detection in CT angiography using e-CTA by Fatih Seker, Johannes Alex Rolf Pfaff, Yahia Mokli, Anne Berberich, Rafael Namias, Steven Gerry, Simon Nagel, Martin Bendszus and Christian Herweh in International Journal of Stroke

Introduction: Acute stroke care delivered by interdisciplinary teams is time-sensitive. Simulation-based team training is a promising tool to improve team performance in medical operations. It has the potential to improve process times, team communication, patient safety, and staff satisfaction. We aim to assess whether a multi-level approach consisting of a stringent workflow revision based on peer-to-peer review and 2–3 one-day in situ simulation trainings can improve acute stroke care processing times in high volume neurocenters within a 6 months period.Methods and Analysis: The trial is being carried out in a pre-test-post-test design at 7 tertiary care university hospital neurocenters in Germany. The intervention is directed at the interdisciplinary multiprofessional stroke teams. Before and after the intervention, process times of all direct-to-center stroke patients receiving IV thrombolysis (IVT) and/or endovascular therapy (EVT) will be recorded. The primary outcome measure will be the “door-to-needle” time of all consecutive stroke patients directly admitted to the neurocenters who receive IVT. Secondary outcome measures will be intervention-related process times of the fraction of patients undergoing EVT and effects on team communication, perceived patient safety, and staff satisfaction via a staff questionnaire.Interventions: We are applying a multi-level intervention in cooperation with three “STREAM multipliers” from each center. First step is a central meeting of the multipliers at the sponsor's institution with the purposes of algorithm review in a peer-to-peer process that is recorded in a protocol and an introduction to the principles of simulation training and debriefing as well as crew resource management and team communication. Thereafter, the multipliers cooperate with the stroke team trainers from the sponsor's institution to plan and execute 2–3 one-day simulation courses in situ in the emergency department and CT room of the trial centers whereupon they receive teaching materials to perpetuate the trainings.Clinical Trial Registration: STREAM is a registered trial at https://clinicaltrials.gov/ct2/show/NCT03228251.

Tools for medical image analysis have been developed to reduce the time needed to detect abnormalities and to provide more accurate results. Particularly, tools based on artificial intelligence and machine learning techniques have led to significant improvements in medical imaging interpretation in the last decade. Automatic evaluation of acute ischemic stroke in medical imaging is one of the fields that witnessed a major development. Commercially available products so far aim to identify (and quantify) the ischemic core, the ischemic penumbra, the site of arterial occlusion and the collateral flow but they are not (yet) intended as standalone diagnostic tools. Their use can be complementary; they are intended to support physicians’ interpretation of medical images and hence standardise selection of patients for acute treatment. This review provides an introduction into the field of computer-aided diagnosis and focuses on the automatic analysis of non-contrast-enhanced computed tomography, computed tomography angiography and perfusion imaging. Future studies are necessary that allow the evaluation and comparison of different imaging strategies and post-processing algorithms during the diagnosis process in patients with suspected acute ischemic stroke; which may further facilitate the standardisation of treatment and stroke management. Electronic supplementary material The online version of this article (10.1186/s42466-019-0028-y) contains supplementary material, which is available to authorized users.