Association Between Intravenous Thrombolysis and Clinical Outcomes Among Patients With Ischemic Stroke and Unsuccessful Mechanical Reperfusion.

IMPORTANCE Clinical evidence of the potential treatment benefit of intravenous thrombolysis preceding unsuccessful mechanical thrombectomy (MT) is scarce. OBJECTIVE To determine whether intravenous thrombolysis (IVT) prior to unsuccessful MT improves functional outcomes in patients with acute ischemic stroke. DESIGN, SETTING, AND PARTICIPANTS Patients were enrolled in this retrospective cohort study from the prospective, observational, multicenter German Stroke Registry-Endovascular Treatment between May 1, 2015, and December 31, 2021. This study compared IVT plus MT vs MT alone in patients with acute ischemic stroke due to anterior circulation large-vessel occlusion in whom mechanical reperfusion was unsuccessful. Unsuccessful mechanical reperfusion was defined as failed (final modified Thrombolysis in Cerebral Infarction grade of 0 or 1) or partial (grade 2a). Patients meeting the inclusion criteria were matched by treatment group using 1:1 propensity score matching. INTERVENTIONS Mechanical thrombectomy with or without IVT. MAIN OUTCOMES AND MEASURES Primary outcome was functional independence at 90 days, defined as a modified Rankin Scale score of 0 to 2. Safety outcomes were the occurrence of symptomatic intracranial hemorrhage and death. RESULTS After matching, 746 patients were compared by treatment arms (median age, 78 [IQR, 68-84] years; 438 women [58.7%]). The proportion of patients who were functionally independent at 90 days was 68 of 373 (18.2%) in the IVT plus MT and 42 of 373 (11.3%) in the MT alone group (adjusted odds ratio [AOR], 2.63 [95% CI, 1.41-5.11]; P = .003). There was a shift toward better functional outcomes on the modified Rankin Scale favoring IVT plus MT (adjusted common OR, 1.98 [95% CI, 1.35-2.92]; P < .001). The treatment benefit of IVT was greater in patients with partial reperfusion compared with failed reperfusion. There was no difference in symptomatic intracranial hemorrhages between treatment groups (AOR, 0.71 [95% CI, 0.29-1.81]; P = .45), while the death rate was lower after IVT plus MT (AOR, 0.54 [95% CI, 0.34-0.86]; P = .01). CONCLUSIONS AND RELEVANCE These findings suggest that prior IVT was safe and improved functional outcomes at 90 days. Partial reperfusion was associated with a greater treatment benefit of IVT, indicating a positive interaction between IVT and MT. These results support current guidelines that all eligible patients with stroke should receive IVT before MT and add a new perspective to the debate on noninferiority of combined stroke treatment

Remote Training of Neurointerventions by Audiovisual Streaming : Experiences from the European ESMINT-EYMINT E-Fellowship Program.

BACKGROUND Remote access of trainees to training centers via video streaming (tele-observership, e‑fellowship) emerges as an alternative to acquire knowledge in endovascular interventions. Situational awareness is a summary term that is also used in surgical procedures for perceiving and understanding the situation and projecting what will happen next. A high situational awareness would serve as prerequisite for meaningful learning success during tele-observerships. We hypothesized that live perception of the angiographical procedures using streaming technology is feasible and sufficient to gain useful situational awareness of the procedure. METHODS During a European tele-observership organized by the European Society of Minimally Invasive Neurological Therapy (ESMINT) and its trainee association (EYMINT), a total of six neurointerventional fellows in five countries observed live cases performed by experienced neurointerventionalists (mentors) in six different high-volume neurovascular centers across Europe equipped with live-streaming technology (Tegus Medical, Hamburg, Germany). Cases were prospectively evaluated during a 12-month period, followed by a final questionnaire after completion of the course. RESULTS A total of 102/161 (63%) cases with a 1:1 allocation of fellow and mentor were evaluated during a 12-month period. Most frequent conditions were ischemic stroke (27.5%), followed by embolization of unruptured aneurysms (25.5%) and arteriovenous malformations (AVMs) (15.7%). A high level of situational awareness was reported by fellows in 75.5% of all cases. After finishing the program, the general improvement of neurointerventional knowledge was evaluated to be extensive (1/6 fellows), substantial (3/6), and moderate (2/6). The specific fields of improvement were procedural knowledge (6/6 fellows), technical knowledge (3/6) and complication management (2/6). CONCLUSION Online streaming technology facilitates location-independent training of complex neurointerventional procedures through high levels of situational awareness and can therefore supplement live hands-on-training. In addition, it leads to a training effect for fellows with a perceived improvement of their neurointerventional knowledge

ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset

Magnetic resonance imaging (MRI) is an important imaging modality in stroke. Computer based automated medical image processing is increasingly finding its way into clinical routine. The Ischemic Stroke Lesion Segmentation (ISLES) challenge is a continuous effort to develop and identify benchmark methods for acute and sub-acute ischemic stroke lesion segmentation. Here we introduce an expert-annotated, multicenter MRI dataset for segmentation of acute to subacute stroke lesions (https://doi.org/10.5281/zenodo.7153326). This dataset comprises 400 multi-vendor MRI cases with high variability in stroke lesion size, quantity and location. It is split into a training dataset of n = 250 and a test dataset of n = 150. All training data is publicly available. The test dataset will be used for model validation only and will not be released to the public. This dataset serves as the foundation of the ISLES 2022 challenge (https://www.isles-challenge.org/) with the goal of finding algorithmic methods to enable the development and benchmarking of automatic, robust and accurate segmentation methods for ischemic stroke

ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset.

Magnetic resonance imaging (MRI) is an important imaging modality in stroke. Computer based automated medical image processing is increasingly finding its way into clinical routine. The Ischemic Stroke Lesion Segmentation (ISLES) challenge is a continuous effort to develop and identify benchmark methods for acute and sub-acute ischemic stroke lesion segmentation. Here we introduce an expert-annotated, multicenter MRI dataset for segmentation of acute to subacute stroke lesions ( https://doi.org/10.5281/zenodo.7153326 ). This dataset comprises 400 multi-vendor MRI cases with high variability in stroke lesion size, quantity and location. It is split into a training dataset of n = 250 and a test dataset of n = 150. All training data is publicly available. The test dataset will be used for model validation only and will not be released to the public. This dataset serves as the foundation of the ISLES 2022 challenge ( https://www.isles-challenge.org/ ) with the goal of finding algorithmic methods to enable the development and benchmarking of automatic, robust and accurate segmentation methods for ischemic stroke

Development of Cortical Lesion Volumes on Double Inversion Recovery MRI in Patients With Relapse-Onset Multiple Sclerosis

Background and Objective: In multiple sclerosis (MS) patients, Double Inversion Recovery (DIR) magnetic resonance imaging (MRI) can be used to detect cortical lesions (CL). While the quantity and distribution of CLs seems to be associated with patients' disease course, literature lacks frequent assessments of CL volumes (CL-V) in this context. We investigated the reliability of DIR for the longitudinal assessment of CL-V development with frequent follow-up MRIs and examined the course of CL-V progressions in relation to white-matter lesions (WML), contrast enhancing lesions (CEL) and clinical parameters in patients with Relapsing-Remitting Multiple Sclerosis (RRMS).Methods: In this post-hoc analysis, image- and clinical data of a subset of 24 subjects that were part of a phase IIa clinical trial on the “Safety, Tolerability and Mechanisms of Action of Boswellic Acids in Multiple Sclerosis (SABA)” (ClinicalTrials.gov, NCT01450124) were included. The study was divided in three phases (screening, treatment, study-end). All patients received 12 MRI follow-up-examinations (including DIR) during a 16-months period. CL-Vs were assessed for each patient on each follow-up MRI separately by two experienced neuroradiologists. Results of neurological screening tests, as well as other MRI parameters (WML number and volume and CELs) were included from the SABA investigation data.Results: Inter-rater agreement regarding CL-V assessment over time was good-to-excellent (κ = 0.89). Mean intraobserver variability was 1.1%. In all patients, a total number of 218 CLs was found. Total CL-Vs of all patients increased during the 4 months of baseline screening followed by a continuous and significant decrease from month 5 until study-end (p &lt; 0.001, Kendall'W = 0.413). A positive association between WML volumes and CL-Vs was observed during baseline screening. Decreased CL-V were associated with lower EDSS and also with improvements of SDMT- and SCRIPPS scores.Conclusion: DIR MRI seems to be a reliable tool for the frequent assessment of CL-Vs. Overall CL-Vs decreased during the follow-up period and were associated with improvements of cognitive and disability status scores. Our results suggest the presence of short-term CL-V dynamics in RRMS patients and we presume that the laborious evaluation of lesion volumes may be worthwhile for future investigations.Clinical Trial Numbers:www.ClinicalTrials.gov, “The SABA trial”; number: NCT0145012

A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge

Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable AI algorithms with clinical value. We address this gap by presenting a novel ensemble algorithm derived from the 2022 Ischemic Stroke Lesion Segmentation (ISLES) challenge. ISLES'22 provided 400 patient scans with ischemic stroke from various medical centers, facilitating the development of a wide range of cutting-edge segmentation algorithms by the research community. Through collaboration with leading teams, we combined top-performing algorithms into an ensemble model that overcomes the limitations of individual solutions. Our ensemble model achieved superior ischemic lesion detection and segmentation accuracy on our internal test set compared to individual algorithms. This accuracy generalized well across diverse image and disease variables. Furthermore, the model excelled in extracting clinical biomarkers. Notably, in a Turing-like test, neuroradiologists consistently preferred the algorithm's segmentations over manual expert efforts, highlighting increased comprehensiveness and precision. Validation using a real-world external dataset (N=1686) confirmed the model's generalizability. The algorithm's outputs also demonstrated strong correlations with clinical scores (admission NIHSS and 90-day mRS) on par with or exceeding expert-derived results, underlining its clinical relevance. This study offers two key findings. First, we present an ensemble algorithm (https://github.com/Tabrisrei/ISLES22_Ensemble) that detects and segments ischemic stroke lesions on DWI across diverse scenarios on par with expert (neuro)radiologists. Second, we show the potential for biomedical challenge outputs to extend beyond the challenge's initial objectives, demonstrating their real-world clinical applicability

Woven EndoBridge (WEB) Width at the Aneurysm Neck Level Affects Early Angiographic Aneurysm Occlusion

Purpose!#!Endovascular therapy with the Woven EndoBridge (WEB) device is a safe treatment approach, whereby neoendothelialization at the neck area is a crucial element for aneurysm occlusion. We hypothesized that WEB sizing at the aneurysmal neck level has an impact on early aneurysm occlusion.!##!Methods!#!Patients with short-term follow-up digital subtraction angiography following WEB treatment of unruptured aneurysms were included. Aneurysms were categorized according to the Bicêtre Occlusion Scale Score (BOSS) as adequately (BOSS 0, 0', 1) or partially occluded (BOSS 2, 3, 1 + 3). The WEB device dimensions, including the average aneurysm diameter (AADi) and the average neck diameter (ANDi) as well as baseline patient characteristics were documented.!##!Results!#!In this study 75 patients with 76 aneurysms were included and 65 aneurysms showed adequate occlusion at short-term follow-up (86%). In univariable logistic regression analysis, smaller differences in WEB size to ANDi (D-ANDi) were significantly associated with adequate aneurysm occlusion (odds ratio, OR = 0.41, 95% confidence interval, CI 0.23-0.71, p = 0.002). Receiver operating characteristic (ROC) curve analyses displayed higher discriminative power for the D‑ANDi (AUC = 0.77, 95% CI 0.66-0.86, cut-off ≤2.9 mm) compared to the difference in WEB size to the average aneurysm diameter (D-AADi, AUC = 0.65, 95% CI 0.53-0.75, cut-off ≤1.0 mm).!##!Conclusion!#!Smaller differences between the WEB width and ANDi were associated with adequate early aneurysm occlusion and might thus have a higher impact on the results than the traditional device sizing considering the mean aneurysm diameter. D‑ANDi ≤2.9 mm served as an optimal cut-off to classify occlusion after WEB treatment at the short-term follow-up. Further external validation is warranted

Quantification of ischemic brain edema after mechanical thrombectomy using dual-energy computed tomography in patients with ischemic stroke

Abstract Net water uptake (NWU) is a quantitative imaging biomarker used to assess cerebral edema resulting from ischemia via Computed Tomography (CT)-densitometry. It serves as a strong predictor of clinical outcome. Nevertheless, NWU measurements on follow-up CT scans after mechanical thrombectomy (MT) can be affected by contrast staining. To improve the accuracy of edema estimation, virtual non-contrast images (VNC-I) from dual-energy CT scans (DECT) were compared to conventional polychromatic CT images (CP-I) in this study. We examined NWU measurements derived from VNC-I and CP-I to assess their agreement and predictive value in clinical outcome. 88 consecutive patients who received DECT as follow-up after MT were included. NWU was quantified on CP-I (cNWU) and VNC-I (vNWU). The clinical endpoint was functional independence at discharge. cNWU and vNWU were highly correlated (r = 0.71, p < 0.0001). The median difference between cNWU and vNWU was 8.7% (IQR: 4.5–14.1%), associated with successful vessel recanalization (mTICI2b-3) (ß: 11.6%, 95% CI 2.9–23.0%, p = 0.04), and age (ß: 4.2%, 95% CI 1.3–7.0%, p = 0.005). The diagnostic accuracy to classify outcome between cNWU and vNWU was similar (AUC:0.78 versus 0.77). Although there was an 8.7% median difference, indicating potential edema underestimation on CP-I, it did not have short-term clinical implications