Clinical change during inter-hospital transfer for thrombectomy: Incidence, associated factors, and relationship with outcome

BACKGROUND

Patients with acute ischemic stroke with a large vessel occlusion (LVO) admitted to non endovascular-capable centers often require inter-hospital transfer for thrombectomy. We aimed to describe the incidence of substantial clinical change during transfer, the factors associated with clinical change, and its relationship with 3-month outcome.

METHODS

We analyzed data from two cohorts of acute stroke patients transferred for thrombectomy to a comprehensive center (Stanford, USA, November 2019 to January 2023; Montpellier, France, January 2015 to January 2017), regardless of whether thrombectomy was eventually attempted. Patients were included if they had evidence of an LVO at the referring hospital and had a National Institute of Health Stroke Scale (NIHSS) score documented before and immediately after transfer. Inter-hospital clinical change was categorized as improvement (⩾4 points and ⩾25% decrease between the NIHSS score in the referring hospital and upon comprehensive center arrival), deterioration (⩾4 points and ⩾25% increase), or stability (neither improvement nor deterioration). The stable group was considered as the reference and was compared to the improvement or deterioration groups separately.

RESULTS

A total of 504 patients were included, of whom 22% experienced inter-hospital improvement, 14% deterioration, and 64% were stable. Pre-transfer variables independently associated with clinical improvement were intravenous thrombolysis use, more distal occlusions, and lower serum glucose; variables associated with deterioration included more proximal occlusions and higher serum glucose. On post-transfer imaging, clinical improvement was associated with arterial recanalization and smaller infarct growth and deterioration with larger infarct growth. As compared to stable patients, those with clinical improvement had better 3-month functional outcome (adjusted common odds ratio (cOR) = 2.43; 95% confidence interval (CI) = 1.59-3.71; p < 0.001), while those with deterioration had worse outcome (adjusted cOR = 0.60; 95% CI = 0.37-0.98; p = 0.044).

CONCLUSION

Substantial inter-hospital clinical changes are frequently observed in LVO-related ischemic strokes, with significant impact on functional outcome. There is a need to develop treatments that improves the clinical status during transfer.

DATA ACCESS STATEMENT

The data that support the findings of this study are available upon reasonable request.

USE-Evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging

Performance metrics for medical image segmentation models are used to measure the agreement between the reference annotation and the predicted segmentation. Usually, overlap metrics, such as the Dice, are used as a metric to evaluate the performance of these models in order for results to be comparable. However, there is a mismatch between the distributions of cases and the difficulty level of segmentation tasks in public data sets compared to clinical practice. Common metrics used to assess performance fail to capture the impact of this mismatch, particularly when dealing with datasets in clinical settings that involve challenging segmentation tasks, pathologies with low signal, and reference annotations that are uncertain, small, or empty. Limitations of common metrics may result in ineffective machine learning research in designing and optimizing models. To effectively evaluate the clinical value of such models, it is essential to consider factors such as the uncertainty associated with reference annotations, the ability to accurately measure performance regardless of the size of the reference annotation volume, and the classification of cases where reference annotations are empty. We study how uncertain, small, and empty reference annotations influence the value of metrics on a stroke in-house data set regardless of the model. We examine metrics behavior on the predictions of a standard deep learning framework in order to identify suitable metrics in such a setting. We compare our results to the BRATS 2019 and Spinal Cord public data sets. We show how uncertain, small, or empty reference annotations require a rethinking of the evaluation. The evaluation code was released to encourage further analysis of this topic https://github.com/SophieOstmeier/UncertainSmallEmpty.git.

Semiautomated Detection of Early Infarct Signs on Noncontrast CT Improves Interrater Agreement

BACKGROUND

Acute ischemic infarct identification on noncontrast computed tomography (NCCT) is highly variable between raters. A semiautomated method for segmentation of acute ischemic lesions on NCCT may improve interrater reliability.

METHODS

Patients with successful endovascular reperfusion from the DEFUSE 3 trial (Endovascular Therapy Following Imaging Evaluation for Ischemic Stroke) were included. We created relative NCCT (rNCCT) color-gradient overlays by comparing the density of a voxel on NCCT to the homologous region in the contralateral hemisphere. Regions with a relative hypodensity of at least 5% were visualized. We coregistered baseline and follow-up images. Two neuroradiologists and 6 nonradiologists segmented the acute ischemic lesion on the baseline scans with 2 methods: (1) manually outlining hypodense regions on the NCCT (unassisted segmentation) and (2) manually excluding areas deemed outside of the ischemic lesion on the rNCCT color map (rNCCT-assisted segmentation). Voxelwise interrater agreement was quantified using the Dice similarity coefficient and volumetric agreement between raters with the detection index (DI), defined as the true positive volume minus the false positive volume.

RESULTS

From a total of 92, we included 61 patients. Median age was 59 (64-77), and 57% were female. Stroke onset was known in 39%. Onset to NCCT was median, 8.5 hours (7-11) and median 10 hours (8.4-11.5) in patients with known and unknown onset, respectively. Compared with unassisted NCCT segmentation, rNCCT-assisted segmentation increased the Dice similarity coefficient by >50% for neuroradiologists (Dice similarity coefficient, 0.38 versus 0.83; P<0.001) and nonradiologists (Dice similarity coefficient, 0.14 versus 0.84; P<0.001), and improved the DI among nonradiologists (mean improvement, 5.8 mL [95% CI, 3.1-8.5] mL, P<0.001) but not among neuroradiologists.

CONCLUSIONS

The high variability of manual segmentations of the acute ischemic lesion on NCCT is greatly reduced using semiautomated rNCCT. The rNCCT map may therefore aid acute infarct detection and provide more reliable infarct estimates for clinicians with less experience.

Factors Associated With Fast Early Infarct Growth in Patients With Acute Ischemic Stroke With a Large Vessel Occlusion

BACKGROUND AND OBJECTIVES

The optimal methods for predicting early infarct growth rate (EIGR) in acute ischemic stroke with a large vessel occlusion (LVO) have not been established. We aimed to study the factors associated with EIGR, with a focus on the collateral circulation as assessed by the hypoperfusion intensity ratio (HIR) on perfusion imaging, and determine whether the associations found are consistent across imaging modalities.

METHODS

Retrospective multicenter international study including patients with anterior circulation LVO-related acute stroke with witnessed stroke onset and baseline perfusion imaging (MRI or CT) performed within 24 hours from symptom onset. To avoid selection bias, patients were selected from (1) the prospective registries of 4 comprehensive stroke centers with systematic use of perfusion imaging and including both thrombectomy-treated and untreated patients and (2) 1 prospective thrombectomy study where perfusion imaging was acquired per protocol, but treatment decisions were made blinded to the results. EIGR was defined as infarct volume on baseline imaging divided by onset-to-imaging time and fast progressors as EIGR ≥10 mL/h. The HIR, defined as the proportion of time-to-maximum (Tmax) >6 second with Tmax >10 second volume, was measured on perfusion imaging using RAPID software. The factors independently associated with fast progression were studied using multivariable logistic regression models, with separate analyses for CT- and MRI-assessed patients.

RESULTS

Overall, 1,127 patients were included (CT, n = 471; MRI, n = 656). Median age was 74 years (interquartile range [IQR] 62-83), 52% were male, median NIH Stroke Scale was 16 (IQR 9-21), median HIR was 0.42 (IQR 0.26-0.58), and 415 (37%) were fast progressors. The HIR was the primary factor associated with fast progression, with very similar results across imaging modalities: The proportion of fast progressors was 4% in the first HIR quartile (i.e., excellent collaterals), ∼15% in the second, ∼50% in the third, and ∼77% in the fourth (p < 0.001 for each imaging modality). Fast progression was independently associated with poor 3-month functional outcome in both the CT and MRI cohorts (p < 0.001 and p = 0.030, respectively).

DISCUSSION

The HIR is the primary factor associated with fast infarct progression, regardless of imaging modality. These results have implication for neuroprotection trial design, as well as informing triage decisions at primary stroke centers.

Non-inferiority of deep learning ischemic stroke segmentation on non-contrast CT within 16-hours compared to expert neuroradiologists

We determined if a convolutional neural network (CNN) deep learning model can accurately segment acute ischemic changes on non-contrast CT compared to neuroradiologists. Non-contrast CT (NCCT) examinations from 232 acute ischemic stroke patients who were enrolled in the DEFUSE 3 trial were included in this study. Three experienced neuroradiologists independently segmented hypodensity that reflected the ischemic core on each scan. The neuroradiologist with the most experience (expert A) served as the ground truth for deep learning model training. Two additional neuroradiologists' (experts B and C) segmentations were used for data testing. The 232 studies were randomly split into training and test sets. The training set was further randomly divided into 5 folds with training and validation sets. A 3-dimensional CNN architecture was trained and optimized to predict the segmentations of expert A from NCCT. The performance of the model was assessed using a set of volume, overlap, and distance metrics using non-inferiority thresholds of 20%, 3 ml, and 3 mm, respectively. The optimized model trained on expert A was compared to test experts B and C. We used a one-sided Wilcoxon signed-rank test to test for the non-inferiority of the model-expert compared to the inter-expert agreement. The final model performance for the ischemic core segmentation task reached a performance of 0.46 ± 0.09 Surface Dice at Tolerance 5mm and 0.47 ± 0.13 Dice when trained on expert A. Compared to the two test neuroradiologists the model-expert agreement was non-inferior to the inter-expert agreement, [Formula: see text]. The before, CNN accurately delineates the hypodense ischemic core on NCCT in acute ischemic stroke patients with an accuracy comparable to neuroradiologists.

Anatomical predictors of need for decompressive craniectomy after stroke using voxel-based lesion symptom mapping

BACKGROUND AND PURPOSE

Malignant cerebral edema (MCE) secondary to ischemic stroke is a highly morbid condition. Decompressive craniectomy (DC) is the only treatment for MCE that has been shown to reduce mortality. We examined whether early infarction and/or hypoperfusion in specific topographic regions was predictive of the need for later DC.

METHODS

A retrospective database of patients evaluated for large vessel occlusion (LVO) stroke at Stanford between 2010 and 2019 was used. Thirty patients with LVO and baseline perfusion MRI who underwent DC were evaluated. Propensity matching based on age, lesion size, and recanalization status was performed on the remaining cohort. Baseline masks of apparent diffusion coefficient (ADC) + Tmax  >6 seconds lesions were generated using automated perfusion software. Voxel-based lesion symptom maping was used to perform logistic regression at each voxel to generate statistical maps of lesion location associated with DC. Hemispheres were combined to increase statistical power.

RESULTS

Sixty patients were analyzed. After adjusting for age, lesion size, and recanalization status as covariates, scattered cortical regions, predominately within the temporal and frontal lobe, were mildly to moderately predictive of the need for DC (z-scores: 2.4-6.74, p < .01).

CONCLUSIONS

Scattered temporal and frontal lobe regions on baseline diffusion and perfusion MRI were found to be mildly to moderately predictive of the need for subsequent DC in patients with LVO stroke.

EEG pre-burst suppression: characterization and inverse association with preoperative cognitive function in older adults

The most common complication in older surgical patients is postoperative delirium (POD). POD is associated with preoperative cognitive impairment and longer durations of intraoperative burst suppression (BSup) - electroencephalography (EEG) with repeated periods of suppression (very low-voltage brain activity). However, BSup has modest sensitivity for predicting POD. We hypothesized that a brain state of lowered EEG power immediately precedes BSup, which we have termed "pre-burst suppression" (preBSup). Further, we hypothesized that even patients without BSup experience these preBSup transient reductions in EEG power, and that preBSup (like BSup) would be associated with preoperative cognitive function and delirium risk. Data included 83 32-channel intraoperative EEG recordings of the first hour of surgery from 2 prospective cohort studies of patients ≥age 60 scheduled for ≥2-h non-cardiac, non-neurologic surgery under general anesthesia (maintained with a potent inhaled anesthetic or a propofol infusion). Among patients with BSup, we defined preBSup as the difference in 3-35 Hz power (dB) during the 1-s preceding BSup relative to the average 3-35 Hz power of their intraoperative EEG recording. We then recorded the percentage of time that each patient spent in preBSup, including those without BSup. Next, we characterized the association between percentage of time in preBSup and (1) percentage of time in BSup, (2) preoperative cognitive function, and (3) POD incidence. The percentage of time in preBSup and BSup were correlated (Spearman's ρ [95% CI]: 0.52 [0.34, 0.66], p < 0.001). The percentage of time in BSup, preBSup, or their combination were each inversely associated with preoperative cognitive function (β [95% CI]: -0.10 [-0.19, -0.01], p = 0.024; -0.04 [-0.06, -0.01], p = 0.009; -0.04 [-0.06, -0.01], p = 0.003, respectively). Consistent with prior literature, BSup was significantly associated with POD (odds ratio [95% CI]: 1.34 [1.01, 1.78], p = 0.043), though this association did not hold for preBSup (odds ratio [95% CI]: 1.04 [0.95, 1.14], p = 0.421). While all patients had ≥1 preBSup instance, only 20.5% of patients had ≥1 BSup instance. These exploratory findings suggest that future studies are warranted to further study the extent to which preBSup, even in the absence of BSup, can identify patients with impaired preoperative cognition and/or POD risk.

CT perfusion to measure venous outflow in acute ischemic stroke in patients with a large vessel occlusion

BACKGROUND

Robust venous outflow (VO) profiles, measured by degree of venous opacification on pre-thrombectomy CT angiography (CTA) studies, are strongly correlated with favorable outcomes in patients with large vessel occlusion acute ischemic stroke treated by thrombectomy. However, VO measurements are laborious and require neuroimaging expertise.

OBJECTIVE

To develop a semi-automated method to measure VO using CTA and CT perfusion imaging studies.

METHODS

We developed a graphical interface using The Visualization Toolkit, allowing for voxel selection at the confluence and bilateral internal cerebral veins on CTA along with arterial input functions (AIFs) from both internal carotid arteries. We extracted concentration-time curves from the CT perfusion study at the corresponding locations associated with AIF and venous output function (VOF). Outcome analyses were primarily conducted by the Mann-Whitney U and Jonckheere-Terpstra tests.

RESULTS

Segmentation at the pre-selected AIF and VOF locations was performed on a sample of 97 patients. 65 patients had favorable VO (VO+) and 32 patients had unfavorable VO (VO-). VO+ patients were found to have a significantly shorter VOF time to peak (8.26; 95% CI 7.07 to 10.34) than VO- patients (9.44; 95% CI 8.61 to 10.91), P=0.007. No significant difference was found in VOF curve width and the difference in time between AIF and VOF peaks.

CONCLUSIONS

Time to peak of VOF at the confluence of sinuses was significantly associated with manually scored venous outflow. Further studies should aim to understand better the association between arterial inflow and venous outflow, and capture quantitative metrics of venous outflow at other locations.

Comprehensive Venous Outflow Predicts Functional Outcomes in Patients with Acute Ischemic Stroke Treated by Thrombectomy

BACKGROUND AND PURPOSE

Cortical venous outflow has emerged as a robust measure of collateral blood flow in acute ischemic stroke. The addition of deep venous drainage to this assessment may provide valuable information to further guide the treatment of these patients.

MATERIALS AND METHODS

We performed a multicenter retrospective cohort study of patients with acute ischemic stroke treated by thrombectomy between January 2013 and January 2021. The internal cerebral veins were scored on a scale of 0-2. This metric was combined with existing cortical vein opacification scores to create a comprehensive venous outflow score from 0 to 8 and stratify patients as having favorable-versus-unfavorable comprehensive venous outflow. Outcome analyses were primarily conducted using the Mann-Whitney U and χ2 tests.

RESULTS

Six hundred seventy-eight patients met the inclusion criteria. Three hundred fifteen were stratified as having favorable comprehensive venous outflow (mean age, 73 years; range, 62-81 years; 170 men), and 363, as having unfavorable comprehensive venous outflow (mean age, 77 years; range, 67-85 years; 154 men). There were significantly higher rates of functional independence (mRS 0-2; 194/296 versus 37/352, 66% versus 11%, P < .001) and excellent reperfusion (TICI 2c/3; 166/313 versus 142/358, 53% versus 40%, P < .001) in patients with favorable comprehensive venous outflow. There was a significant increase in the association of mRS with the comprehensive venous outflow score compared with the cortical vein opacification score (-0.74 versus -0.67, P = .006).

CONCLUSIONS

A favorable comprehensive venous profile is strongly associated with functional independence and excellent postthrombectomy reperfusion. Future studies should focus on patients with venous outflow status that is discrepant with the eventual outcome.

Quantification of Penumbral Volume in Association With Time From Stroke Onset in Acute Ischemic Stroke With Large Vessel Occlusion

Importance

The benefit of reperfusion therapies for acute ischemic stroke decreases over time. This decreasing benefit is presumably due to the disappearance of salvageable ischemic brain tissue (ie, the penumbra).

Objective

To study the association between stroke onset-to-imaging time and penumbral volume in patients with acute ischemic stroke with a large vessel occlusion.

Design, Setting, and Participants

A retrospective, multicenter, cross-sectional study was conducted from January 1, 2015, to June 30, 2022. To limit selection bias, patients were selected from (1) the prospective registries of 2 comprehensive centers with systematic use of magnetic resonance imaging (MRI) with perfusion, including both thrombectomy-treated and untreated patients, and (2) 1 prospective thrombectomy study in which MRI with perfusion was acquired per protocol but treatment decisions were made with clinicians blinded to the results. Consecutive patients with acute stroke with intracranial internal carotid artery or first segment of middle cerebral artery occlusion and adequate quality MRI, including perfusion, performed within 24 hours from known symptoms onset were included in the analysis.

Exposures

Time from stroke symptom onset to baseline MRI.

Main Outcomes and Measures

Penumbral volume, measured using automated software, was defined as the volume of tissue with critical hypoperfusion (time to maximum >6 seconds) minus the volume of the ischemic core. Substantial penumbra was defined as greater than or equal to 15 mL and a mismatch ratio (time to maximum >6-second volume/core volume) greater than or equal to 1.8.

Results

Of 940 patients screened, 516 were excluded (no MRI, n = 19; no perfusion imaging, n = 59; technically inadequate perfusion imaging, n = 75; second segment of the middle cerebral artery occlusion, n = 156; unwitnessed stroke onset, n = 207). Of 424 included patients, 226 (53.3%) were men, and mean (SD) age was 68.9 (15.1) years. Median onset-to-imaging time was 3.8 (IQR, 2.4-5.5) hours. Only 16 patients were admitted beyond 10 hours from symptom onset. Median core volume was 24 (IQR, 8-76) mL and median penumbral volume was 58 (IQR, 29-91) mL. An increment in onset-to-imaging time by 1 hour resulted in a decrease of 3.1 mL of penumbral volume (β coefficient = -3.1; 95% CI, -4.6 to -1.5; P < .001) and an increase of 3.0 mL of core volume (β coefficient = 3.0; 95% CI, 1.3-4.7; P < .001) after adjustment for confounders. The presence of a substantial penumbra ranged from approximately 80% in patients imaged at 1 hour to 70% at 5 hours, 60% at 10 hours, and 40% at 15 hours.

Conclusions and Relevance

Time is associated with increasing core and decreasing penumbral volumes. Despite this, a substantial percentage of patients have notable penumbra in extended time windows; the findings of this study suggest that a large proportion of patients with large vessel occlusion may benefit from therapeutic interventions.

Application of 89Zr-DFO*-immuno-PET to assess improved target engagement of a bispecific anti-amyloid-ß monoclonal antibody

PURPOSE

The recent conditional FDA approval of Aducanumab (Adu) for treating Alzheimer's disease (AD) and the continued discussions around that decision have increased interest in immunotherapy for AD and other brain diseases. Reliable techniques for brain imaging of antibodies may guide decision-making in the future but needs further development. In this study, we used ⁸⁹Zr-immuno-PET to evaluate the targeting and distribution of a bispecific brain-shuttle IgG based on Adu with transferrin receptor protein-1 (TfR1) shuttling mechanism, mAbAdu-scFab8D3, designated Adu-8D3, as a candidate theranostic for AD. We also validated the ⁸⁹Zr-immuno-PET platform as an enabling technology for developing new antibody-based theranostics for brain disorders.

METHODS

Adu, Adu-8D3, and the non-binding control construct B12-8D3 were modified with DFO*-NCS and radiolabeled with ⁸⁹Zr. APP/PS1 mice were injected with ⁸⁹Zr-labeled mAbs and imaged on days 3 and 7 by positron emission tomography (PET). Ex vivo biodistribution was performed on day 7, and ex vivo autoradiography and immunofluorescence staining were done on brain tissue to validate the PET imaging results and target engagement with amyloid-β plaques. Additionally, [⁸⁹Zr]Zr-DFO*-Adu-8D3 was evaluated in 3, 7, and 10-month-old APP/PS1 mice to test its potential in early stage disease.

RESULTS

A 7-fold higher brain uptake was observed for [⁸⁹Zr]Zr-DFO*-Adu-8D3 compared to [⁸⁹Zr]Zr-DFO*-Adu and a 2.7-fold higher uptake compared to [⁸⁹Zr]Zr-DFO*-B12-8D3 on day 7. Autoradiography and immunofluorescence of [⁸⁹Zr]Zr-DFO*-Adu-8D3 showed co-localization with amyloid plaques, which was not the case with the Adu and B12-8D3 conjugates. [⁸⁹Zr]Zr-DFO*-Adu-8D3 was able to detect low plaque load in 3-month-old APP/PS1 mice.

CONCLUSION

⁸⁹Zr-DFO*-immuno-PET revealed high and specific uptake of the bispecific Adu-8D3 in the brain and can be used for the early detection of Aβ plaque pathology. Here, we demonstrate that ⁸⁹Zr-DFO*-immuno-PET can be used to visualize and quantify brain uptake of mAbs and contribute to the evaluation of biological therapeutics for brain diseases.

Predicting Hypoperfusion Lesion and Target Mismatch in Stroke from Diffusion-weighted MRI Using Deep Learning

Background Perfusion imaging is important to identify a target mismatch in stroke but requires contrast agents and postprocessing software. Purpose To use a deep learning model to predict the hypoperfusion lesion in stroke and identify patients with a target mismatch profile from diffusion-weighted imaging (DWI) and clinical information alone, using perfusion MRI as the reference standard. Materials and Methods Imaging data sets of patients with acute ischemic stroke with baseline perfusion MRI and DWI were retrospectively reviewed from multicenter data available from 2008 to 2019 (Imaging Collaterals in Acute Stroke, Diffusion and Perfusion Imaging Evaluation for Understanding Stroke Evolution 2, and University of California, Los Angeles stroke registry). For perfusion MRI, rapid processing of perfusion and diffusion software automatically segmented the hypoperfusion lesion (time to maximum, ≥6 seconds) and ischemic core (apparent diffusion coefficient [ADC], ≤620 × 10-6 mm2/sec). A three-dimensional U-Net deep learning model was trained using baseline DWI, ADC, National Institutes of Health Stroke Scale score, and stroke symptom sidedness as inputs, with the union of hypoperfusion and ischemic core segmentation serving as the ground truth. Model performance was evaluated using the Dice score coefficient (DSC). Target mismatch classification based on the model was compared with that of the clinical-DWI mismatch approach defined by the DAWN trial by using the McNemar test. Results Overall, 413 patients (mean age, 67 years ± 15 [SD]; 207 men) were included for model development and primary analysis using fivefold cross-validation (247, 83, and 83 patients in the training, validation, and test sets, respectively, for each fold). The model predicted the hypoperfusion lesion with a median DSC of 0.61 (IQR, 0.45-0.71). The model identified patients with target mismatch with a sensitivity of 90% (254 of 283; 95% CI: 86, 93) and specificity of 77% (100 of 130; 95% CI: 69, 83) compared with the clinical-DWI mismatch sensitivity of 50% (140 of 281; 95% CI: 44, 56) and specificity of 89% (116 of 130; 95% CI: 83, 94) (P < .001 for all). Conclusion A three-dimensional U-Net deep learning model predicted the hypoperfusion lesion from diffusion-weighted imaging (DWI) and clinical information and identified patients with a target mismatch profile with higher sensitivity than the clinical-DWI mismatch approach. ClinicalTrials.gov registration nos. NCT02225730, NCT01349946, NCT02586415 © RSNA, 2022 Supplemental material is available for this article. See also the editorial by Kallmes and Rabinstein in this issue.

Hyperacute Perfusion Imaging Before Pediatric Thrombectomy: Analysis of the Save ChildS Study

BACKGROUND AND OBJECTIVES

Perfusion imaging can identify adult patients with salvageable brain tissue who would benefit from thrombectomy in later time windows. The feasibility of obtaining hyperacute perfusion sequences in pediatric stroke is unknown. The aim of this study was to determine whether contrast perfusion imaging delayed time to treatment and to assess perfusion profiles in children with large vessel occlusion stroke.

METHODS

The Save ChildS retrospective cohort study (January 2000-December 2018) enrolled children (1 month-18 years) with stroke who underwent thrombectomy from 27 European and U.S. stroke centers. This secondary analysis included patients with anterior circulation occlusion and available imaging for direct review by the neuroimaging core laboratory. Between-group comparisons were performed using the Wilcoxon rank-sum exact test for continuous variables or Fisher exact test for binary variables. Given the small number of patients, evaluation of perfusion imaging parameters was performed descriptively only.

RESULTS

Of 33 patients with available neuroimaging, 15 (45.4%) underwent perfusion (CT perfusion n = 6; MR perfusion n = 9); all were technically adequate. The median time from onset to recanalization did not differ between groups {4 hours (interquartile range [IQR] 4-7.5) perfusion+; 3.4 hours (IQR 2.5-6.5) perfusion-, p = 0.158}. Target mismatch criteria were met by 10/15 (66.7%) patients and did not correlate with reperfusion status or functional outcome. The hypoperfusion intensity ratio (HIR) was favorable in 11/15 patients and correlated with older age but not NIHSS, time to recanalization, or stroke etiology. Favorable HIR was associated with better functional outcome at 6 months (Pediatric Stroke Outcome Measure 1.0 [IQR 0.5-2.0] vs 2.0 [1.5-3.0], p = 0.026) and modified Rankin Scale 1.0 [0-1] vs 2.0 [1.5-3.5], p = 0.048) in this small sample.

DISCUSSION

Automated perfusion imaging is feasible to obtain acutely in children and does not delay time to recanalization. Larger prospective studies are needed to determine biomarkers of favorable outcome in pediatric ischemic stroke and to establish core and penumbral thresholds in children.

Validation of a suite of ERP and QEEG biomarkers in a pre-competitive, industry-led study in subjects with schizophrenia and healthy volunteers

OBJECTIVE

Complexity and lack of standardization have mostly limited the use of event-related potentials (ERPs) and quantitative EEG (QEEG) biomarkers in drug development to small early phase trials. We present results from a clinical study on healthy volunteers (HV) and patients with schizophrenia (SZ) that assessed test-retest, group differences, variance, and correlation with functional assessments for ERP and QEEG measures collected at clinical and commercial trial sites with standardized instrumentation and methods, and analyzed through an automated data analysis pipeline.

METHODS

81 HV and 80 SZ were tested at one of four study sites. Subjects were administered two ERP/EEG testing sessions on separate visits. Sessions included a mismatch negativity paradigm, a 40 Hz auditory steady-state response paradigm, an eyes-closed resting state EEG, and an active auditory oddball paradigm. SZ subjects were also tested on the Brief Assessment of Cognition (BAC), Positive and Negative Syndrome Scale (PANSS), and Virtual Reality Functional Capacity Assessment Tool (VRFCAT).

RESULTS

Standardized ERP/EEG instrumentation and methods ensured few test failures. The automated data analysis pipeline allowed for near real-time analysis with no human intervention. Test-retest reliability was fair-to-excellent for most of the outcome measures. SZ subjects showed significant deficits in ERP and QEEG measures consistent with published academic literature. A subset of ERP and QEEG measures correlated with functional assessments administered to the SZ subjects.

CONCLUSIONS

With standardized instrumentation and methods, complex ERP/EEG testing sessions can be reliably performed at clinical and commercial trial sites to produce high-quality data in near real-time.

Determinants of Infarct Core Growth During Inter-hospital Transfer for Thrombectomy

OBJECTIVE

Patients with acute ischemic stroke harboring a large vessel occlusion who present to primary stroke centers often require inter-hospital transfer for thrombectomy. We aimed to determine clinical and imaging factors independently associated with fast infarct growth (IG) during inter-hospital transfer.

METHODS

We retrospectively analyzed data from acute stroke patients with a large vessel occlusion transferred for thrombectomy from a primary stroke center to one of three French comprehensive stroke centers, with an MRI obtained at both the primary and comprehensive center before thrombectomy. Inter-hospital IG rate was defined as the difference in infarct volumes on diffusion-weighted imaging between the primary and comprehensive center, divided by the delay between the two MRI scans. The primary outcome was identification of fast progressors, defined as IG rate ≥5 mL/hour. The hypoperfusion intensity ratio (HIR), a surrogate marker of collateral blood flow, was automatically measured on perfusion imaging.

RESULTS

A total of 233 patients were included, of whom 27% patients were fast progressors. The percentage of fast progressors was 3% among patients with HIR < 0.40 and 71% among those with HIR ≥ 0.40. In multivariable analysis, fast progression was independently associated with HIR, intracranial carotid artery occlusion, and exclusively deep infarct location at the primary center (C-statistic = 0.95; 95% confidence interval [CI], 0.93-0.98). IG rate was independently associated with good functional outcome (adjusted OR = 0.91; 95% CI, 0.83-0.99; P = 0.037).

INTERPRETATION

Our findings show that a HIR > 0.40 is a powerful indicator of fast inter-hospital IG. These results have implication for neuroprotection trial design, as well as informing triage decisions at primary stroke centers. ANN NEUROL 2023.

Abstract 6: Relationship Between Hypoperfusion Intensity Ratio And Ischemic Core Growth Rate Is Similar On CT And MRI For Unselected Acute LVO Patients

Background: Predicting infarct growth rate (IGR) in acute stroke with large vessel occlusion (LVO) is important for treatment decision-making. IGR has typically been studied in patients treated with thrombectomy, which likely has underestimated the prevalence of ‘fast progressors’, as large core patients are less frequently treated. We aimed to study IGR in an unselected LVO population and study the association between Hypoperfusion Intensity Ratio (HIR, a surrogate marker of collaterals) and IGR as assessed by both CT and MRI.

Methods: Retrospective study including ICA/M1 stroke patients with witnessed stroke onset and baseline perfusion imaging (MRI or CT) performed within 24hrs from symptoms onset. To avoid selection bias, patients were selected from (1) the registries of 3 centers with systematic use of MRI- or CT-perfusion and including both MT-treated and untreated patients, and (2) one trial where thrombectomy decisions were performed blinded from perfusion MRI results. IGR was defined as core volume/onset-to-imaging time, and fast progressors as IGR≥10mL/hr. HIR was defined as the proportion of Tmax>6s volume with Tmax>10s.

Results: Overall, 423 and 215 patients were included in the MRI and CT cohorts. Median IGR was 6.4mL/hr (IQR 2.2-21.3) and 5.2mL/hr (0-25.2) in the MRI and CT cohorts, and median HIR was 0.44 (0.27-0.59) and 0.45 (0.25-0.60). 174 (41%) MRI patients and 86 (40%) CT patients were fast progressors. IGR was increasing with increase of HIR quartiles in both cohorts ( P <0.001, Figure). IGR≥10mL was found in 7%, 17%, 58%, and 83% of patients within respective increasing HIR quartiles in the MRI cohort ( P <0.001), and in 2%, 21%, 60% and 80% in the CT cohort ( P <0.001).

Conclusion: In this unselected LVO population, 40% of patients were fast progressors regardless of imaging modality. HIR was a strong predictor of IGR in both CT and MRI-assessed patients, and may help for patient triage, e.g . for transfer decision from an outside hospital for thrombectomy.

Abstract 69: Blood-brain Barrier Profile Influences Outcome After Mechanical Thrombectomy In The Frame Study

Background and Purpose: The FRAME study demonstrated that even in the early time window (<6hrs) perfusion imaging profiles can influence response to mechanical thrombectomy. Perfusion imaging (PWI) can also be used to measure damage to the blood-brain barrier (BBB) which has been shown to be associated with increased risk of hemorrhagic complications (HC) with treatment. We aimed to determine if BBB profiles in the FRAME study would influence outcome after mechanical thrombectomy (MT).

Methods: This was a post-hoc analysis of the FRAME study which enrolled stroke patients with large vessel occlusion who received MT within 6 hours of stroke onset. Patients with successful pre-treatment MRI PWI were included. We tested the hypothesis that more severe pre-treatment BBB disruption is associated with higher frequency of HC after MT. BBB disruption was measured as the percent of signal change due to gadolinium leakage on the PWI source images. Mean permeability derangement (MPD) was defined as the average of all voxels in the stroke core that are two standard deviations above normal. The outcome of HC was defined as any type of parenchymal hematoma (PH1 or PH2); poor functional outcome was defined as mRS >2 at 90 days. MPD was compared with HC and functional outcome using the Wilcoxon signed-rank test and logistic regression. A prespecified MPD threshold of 20% was tested as a predictor of HC based on prior studies.

Results: There were 164 patients included in the analysis, median age 74 and 48% female. HC occurred in 57 patients. The average MPD was 15.1% for patients with HC and 8.7% for patients without HC. Elevated MPD was significantly associated with HC (p<0.0001) with a 25% increased risk of HC for each 5% increase in MPD (OR 1.25; CI 1.09:1.45; p=0.0018). Increased MPD was also associated with poor functional outcome (p=0.0002). ROC analysis confirmed the prespecified MPD threshold, identifying 19.7% as the optimal cut point for classification. MPD greater than 20% more than tripled the risk of HC (OR 3.37; CI 1.49:7.85; p=0.004).

Conclusions: Increased pre-treatment BBB disruption has a substantial influence on the risk of HC after MT. Integration of BBB imaging into patient selection algorithms to improve MT outcomes should be tested further.

Abstract TMP68: Core/perfusion Mismatch In Acute Ischemic Stroke With M2 Occlusion: Prevalence And Associated Factors

Background: The benefit of mechanical thrombectomy (MT) in acute ischemic stroke (AIS) patients with M2 occlusion is uncertain. Observational studies suggest that perfusion imaging may help select optimal M2 candidates for MT. We aimed to study the prevalence and factors associated with core/perfusion mismatch, as assessed by both CT and MRI, in an unselected population of AIS with M2 occlusion.

Methods: Retrospective observational study including AIS patients with M2 occlusion and baseline perfusion imaging (MRI or CT) performed within 24hrs from last seen well. To avoid selection bias, patients were selected from the prospective registries of 3 centers with systematic use of perfusion imaging, including both MT-treated and untreated patients. Core/perfusion mismatch was defined as mismatch ratio (Tmax>6s/ core volume) >1.8 and mismatch volume (Tmax>6s - core volume) >15mL.

Results: Overall, 156 and 196 patients were included in the MRI and CT cohorts, respectively. Last-seen-well to imaging time was 5.6hrs (IQR 3.9-9.7) and 3.5hrs (1.5-9.8) in the MRI and CT cohorts, and 103/156 (66%) and 134/196 (68%) had proximal M2 occlusions (the remainder had distal M2 occlusions). Median ASPECT score was 7 (5-8) and 8 (7-9), and core/perfusion mismatch was present in 70/156 (45%) and 167/196 (85%) patients. In both cohorts, mismatch was less frequent in distal M2 occlusions and among patients with lower ASPECTS (Figure). Multivariable analysis showed higher ASPECT scores (OR=3.09, 95%CI=2.11-4.52, P <0.001 and OR=2.41, 95%CI 1.63-3.58, P <0.001 in the MRI and CT cohorts) and proximal M2 occlusion (with distal M2 as a reference: OR=3.94, 95%CI=1.68-9.26, P =0.002 and OR=32.78, 95%CI 8.36-128.47, P <0.001 in the MRI and CT cohorts) were independently associated with core/perfusion mismatch.

Conclusion: Perfusion imaging may be useful in triaging M2 patients, particularly for those with ASPECT score <8 and distal M2 occlusions. This has implication for trials.

Abstract TMP69: Random Rater Sampling For Deep Learning Algorithm To Segment Acute Ischemic Stroke On Non-contrast Computed Tomography

Introduction: The delineation of volume and location of acute ischemic brain tissue (AIBT) on Non-Contrast CT (NCCT) increases the efficiency of endovascular treatment decisions. However, the manual segmentation of the AIBT on NCCT is a challenging task and suffers from low inter-expert agreement. Whether supervised deep convolutional neural networks (CNN) are more accurate than expert raters remain to be determined, and the optimal ground truth segmentation of AIBT is unclear given the low inter-expert agreement. We hypothesized that randomly sampling ground truth segmentations of expert raters would enable the CNN to better approximate an accurate ground truth and increase performance.

Methods: The data set consisted of 200 NCCT images (Figure 1a)) of acute ischemic stroke patients presenting within 6-16h and consenting to the DEFUSE3 trial.

Three experienced neuroradiologists manually segmented the AIBT (Figure 1b)1.-3.). The aggregated validation sets of 5-fold-cross-validation were used to compare the (i) average inter-expert agreement, the average performance of (ii) three individual CNNs trained on each rater and (iii) one CNN trained with random rater sampling.

Results: (iii) Random rater sampling (Figure 1c)) lead to a CNN performance superior to (ii) the average performance of individually trained CNNs. The reliability of a CNN goes beyond the human inter-expert agreement (i) (Surface Dice at Tolerance 5mm: 0.88 versus 0.68 and 0.67, respectively; Table 1).

Conclusions: The volume and location of AIBT on NCCT can reliably be segmented by a CNN. The agreement between a randomly chosen rater and the CNN predictions surpasses the inter-expert agreement (Table 1).

Abstract WP104: Core/perfusion Mismatch Prevalence According To ASPECT Score In Acute Ischemic Stroke With Large Vessel Occlusion

Background: In acute ischemic stroke (AIS) with large vessel occlusion (LVO), core/perfusion mismatch modifies the effect of mechanical thrombectomy (MT) on clinical outcome, MT appears to have greater benefit in patients with significant mismatch. We aimed to study the prevalence of core/perfusion mismatch according to ASPECT score in a large population of LVO-related AIS imaged either with MRI or CT.

Methods: Retrospective study including AIS patients with ICA/M1 occlusion and baseline perfusion imaging (MRI or CT) performed within 24hrs from last seen well. To avoid selection bias, patients were selected from (1) the registries of 3 comprehensive centers with systematic use of MRI- or CT-perfusion imaging and including both MT-treated and untreated patients, and (2) one thrombectomy trial where MT decisions were performed blinded to the results of MRI perfusion imaging. Core/perfusion mismatch was defined as mismatch ratio (Tmax>6s volume/ core volume) >1.8 and volume (Tmax>6s - core volume) >15 mL. ASPECT score was rated on diffusion weighted imaging (DWI) or non-contrast CT blinded from the perfusion imaging.

Results: Overall, 580 and 350 patients were included in the MRI and CT cohorts. Last-seen-well to imaging time was 4.8hrs (IQR 3.0-8.7) and 3.2hrs (1.3-8.0) in the MRI and CT cohorts, respectively, median ASPECT score was 7 (5-8) and 8 (7-9), and core/perfusion mismatch was present in 393/580 (68%) and 315/350 (90%) patients. In both cohorts, 75% of patients were treated with MT following imaging. In the MRI cohort, mismatch prevalence was 44% (75/170) and 92% (378/410) for DWI-ASPECTS 0-5 and 6-10, respectively. In the CT cohort, mismatch prevalence was 47% (15/32) and 94% (300/318) for ASPECTS 0-5 and 6-10, respectively.

Conclusion: About 90% of patients with ASPECTS 6-10 have a core/perfusion mismatch regardless of imaging type. However, patients with ASPECTS ≤5 are heterogeneous in terms of mismatch status. Therefore, perfusion imaging may be particularly useful to select appropriate MT candidates with low ASPECT scores, regardless of imaging type, which has implications for large core trials.

Location-weighted versus Volume-weighted Mismatch at MRI for Response to Mechanical Thrombectomy in Acute Stroke

Background A target mismatch profile can identify good clinical response to recanalization after acute ischemic stroke, but does not consider region specificities. Purpose To test whether location-weighted infarction core and mismatch, determined from diffusion and perfusion MRI performed in patients with acute stroke, could improve prediction of good clinical response to mechanical thrombectomy compared with a target mismatch profile. Materials and Methods In this secondary analysis, two prospectively collected independent stroke data sets (2012-2015 and 2017-2019) were analyzed. From the brain before stroke (BBS) study data (data set 1), an eloquent map was computed through voxel-wise associations between the infarction core (based on diffusion MRI on days 1-3 following stroke) and National Institutes of Health Stroke Scale (NIHSS) score. The French acute multimodal imaging to select patients for mechanical thrombectomy (FRAME) data (data set 2) consisted of large vessel occlusion-related acute ischemic stroke successfully recanalized. From acute MRI studies (performed on arrival, prior to thrombectomy) in data set 2, target mismatch and eloquent (vs noneloquent) infarction core and mismatch were computed from the intersection of diffusion- and perfusion-detected lesions with the coregistered eloquent map. Associations of these imaging metrics with early neurologic improvement were tested in multivariable regression models, and areas under the receiver operating characteristic curve (AUCs) were compared. Results Data sets 1 and 2 included 321 (median age, 69 years [IQR, 58-80 years]; 207 men) and 173 (median age, 74 years [IQR, 65-82 years]; 90 women) patients, respectively. Eloquent mismatch was positively and independently associated with good clinical response (odds ratio [OR], 1.14; 95% CI: 1.02, 1.27; P = .02) and eloquent infarction core was negatively associated with good response (OR, 0.85; 95% CI: 0.77, 0.95; P = .004), while noneloquent mismatch was not associated with good response (OR, 1.03; 95% CI: 0.98, 1.07; P = .20). Moreover, adding eloquent metrics improved the prediction accuracy (AUC, 0.73; 95% CI: 0.65, 0.81) compared with clinical variables alone (AUC, 0.65; 95% CI: 0.56, 0.73; P = .01) or a target mismatch profile (AUC, 0.67; 95% CI: 0.59, 0.76; P = .03). Conclusion Location-weighted infarction core and mismatch on diffusion and perfusion MRI scans improved the identification of patients with acute stroke who would benefit from mechanical thrombectomy compared with the volume-based target mismatch profile. Clinical trial registration no. NCT03045146 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Nael in this issue.

Abstract WMP51: Baseline Ct Perfusion Parameters Differ In Large Vessel Occlusion Stroke Patients With Reduced Left Ventricular Ejection Fraction

Introduction: Reduced left ventricular ejection fraction (EF) is associated with worse outcomes after stroke. CT perfusion (CTP) is widely used in acute stroke evaluation; its reliability in patients with reduced EF is unknown. We hypothesized that patients with reduced EF would have abnormal dose-time curves that may impair standard perfusion maps and reduce their quality.

Methods: A retrospective database of all patients presenting to Stanford University for large vessel occlusion (LVO) stroke between 2010-2019 was used. CTPs were post-processed using RAPID software. Concentration-time curve metrics—width of the venous output function (VOF) at half maximum amplitude and VOF peak amplitude—were assessed automatically for each case. A reader blinded to EF visually evaluated the VOF curve for evidence of truncation (yes/no) and graded the quality of the time to maximum (Tmax) map on a scale from 0 (excellent) to 3 (poor), based on the degree of “speckling” present on the map. Continuous parameters were compared using the t-test or Mann-Whitney test and dichotomous parameters with the Fisher’s exact or Chi-square test, where appropriate.

Results: 160 patients with sufficient quality baseline CTP and in-hospital echocardiogram were evaluated; 34 had EF <50%. Mean age, scan time, and cumulative contrast dose did not differ; men were more prevalent in the reduced EF group (68% vs 44%; p=0.016). Compared to patients with normal EF, patients with low EF more often had truncation of the VOF (11.8% vs 0.8%; p=0.007), had a lower VOF peak amplitude (mean 245.04 HU vs 299.07; p=0.013, 95% CI for difference 11.61 to 96.45), had wider VOF at half maximum amplitude (mean 17.84 seconds vs 14.56; p<0.0001, 1.9 to 4.65), and had worse Tmax quality (median 2 (IQR 1-3) vs 1 (0-2); p=0.002).

Conclusion: Patients with reduced EF have dispersion of the contrast bolus as evidenced by a VOF curve that is wider and has a lower peak. Consequently, the quality of the Tmax map in patients with low EF is reduced, which may render automated CTP results unreliable. Additional studies are needed to determine to what extent poor CTP image quality in patients with low EF affects treatment decisions.

Predicting final ischemic stroke lesions from initial diffusion-weighted images using a deep neural network

BACKGROUND

For prognosis of stroke, measurement of the diffusion-perfusion mismatch is a common practice for estimating tissue at risk of infarction in the absence of timely reperfusion. However, perfusion-weighted imaging (PWI) adds time and expense to the acute stroke imaging workup. We explored whether a deep convolutional neural network (DCNN) model trained with diffusion-weighted imaging obtained at admission could predict final infarct volume and location in acute stroke patients.

METHODS

In 445 patients, we trained and validated an attention-gated (AG) DCNN to predict final infarcts as delineated on follow-up studies obtained 3 to 7 days after stroke. The input channels consisted of MR diffusion-weighted imaging (DWI), apparent diffusion coefficients (ADC) maps, and thresholded ADC maps with values less than 620 × 10^-6 mm²/s, while the output was a voxel-by-voxel probability map of tissue infarction. We evaluated performance of the model using the area under the receiver-operator characteristic curve (AUC), the Dice similarity coefficient (DSC), absolute lesion volume error, and the concordance correlation coefficient (ρ_c) of the predicted and true infarct volumes.

RESULTS

The model obtained a median AUC of 0.91 (IQR: 0.84-0.96). After thresholding at an infarction probability of 0.5, the median sensitivity and specificity were 0.60 (IQR: 0.16-0.84) and 0.97 (IQR: 0.93-0.99), respectively, while the median DSC and absolute volume error were 0.50 (IQR: 0.17-0.66) and 27 ml (IQR: 7-60 ml), respectively. The model's predicted lesion volumes showed high correlation with ground truth volumes (ρ_c = 0.73, p < 0.01).

CONCLUSION

An AG-DCNN using diffusion information alone upon admission was able to predict infarct volumes at 3-7 days after stroke onset with comparable accuracy to models that consider both DWI and PWI. This may enable treatment decisions to be made with shorter stroke imaging protocols.

Hypoperfusion Intensity Ratio Is Correlated With the Risk of Parenchymal Hematoma After Endovascular Stroke Treatment

BACKGROUND

Parenchymal hematoma (PH) is a major complication after endovascular treatment (EVT) for ischemic stroke. The hypoperfusion intensity ratio (HIR) represents a perfusion parameter reflecting arterial collateralization and cerebral microperfusion in ischemic brain tissue. We hypothesized that HIR correlates with the risk of PH after EVT.

METHODS

Retrospective multicenter cohort study of patients with large vessel occlusion who underwent EVT between 2013 and 2021 at one of the 2 comprehensive stroke centers (University Medical Center Hamburg-Eppendorf, Germany and Stanford University School of Medicine, CA). HIR was automatically calculated on computed tomography perfusion studies as the ratio of brain volume with time-to-max (Tmax) delay >10 s over volume with Tmax >6 s. Reperfusion hemorrhages were assessed according to the Heidelberg Bleeding Classification. Primary outcome was PH occurrence (PH+) or absence (PH-) on follow-up imaging. Secondary outcome was good clinical outcome defined as a 90-day modified Rankin Scale score of 0 to 2.

RESULTS

A total of 624 patients met the inclusion criteria. We observed PH in 91 (14.6%) patients after EVT. PH+ patients had higher HIR on admission compared with PH- patients (median, 0.6 versus 0.4; P<0.001). In multivariable regression, higher admission blood glucose (adjusted odds ratio [aOR], 1.08 [95% CI, 1.04-1.13]; P<0.001), extensive baseline infarct defined as Alberta Stroke Program Early CT Score ≤5 (aOR, 2.48 [1.37-4.42]; P=0.002), and higher HIR (aOR, 1.22 [1.09-1.38]; P<0.001) were independent determinants of PH after EVT. Both higher HIR (aOR, 0.83 [0.75-0.92]; P<0.001) and PH on follow-up imaging (aOR, 0.39 [0.18-0.80]; P=0.013) were independently associated with lower odds of achieving good clinical outcome.

CONCLUSIONS

Poorer (higher) HIR on admission perfusion imaging was strongly associated with PH occurrence after EVT. HIR as a surrogate for cerebral microperfusion might reflect tissue vulnerability for reperfusion hemorrhages. This automated and quickly available perfusion parameter might help to assess the need for intensive medical care after EVT.

Long-term neurological intact survival and quality of life after refractory out-of-hospital cardiac arrest treated with rescue mechanical circulatory support

Background

Mechanical circulatory support (MCS) with either veno-arterial extracorporeal membrane oxygenation (V-A ECMO) or Impella has emerged as a rescue therapy for refractory out-of-hospital cardiac arrest (OHCA). However, only short-term outcome is specified and most studies do not report follow-up beyond six months. Long-term survival and quality of life in this high-risk population remains unknown.

Purpose

To determine long-term neurological intact survival and quality of life in patients with refractory OHCA treated with MCS.

Methods

This was an observational, single-centre study of OHCA-patients from January 2015 to December 2019. Patients treated with MCS for OHCA were compared with patients receiving conventional cardiopulmonary resuscitation (CPR). A follow-up of long-term survivors in the MCS group was conducted (&gt;1 year after arrest). This included health related quality of life questionaries (Short Form-36 [SF-36]) and assessment of neurological function with Cerebral Performance Category (CPC). Good neurological outcome was defined as CPC 1 and CPC 2.

Results

A total of 1015 with OHCA were included; 101 received MCS for refractory cardiac arrest. Among these V-A ECMO was deployed in 97 patients and Impella in 4 patients. The MCS group had significantly longer low-flow times compared to the conventional group (105 [IQR, 94–123] minutes versus 18 [IQR 10–39] minutes) and were more metabolically deranged upon arrival at hospital (Table 1). In patients receiving MCS, the hospital discharge rate was 27% and good neurological outcome was seen in 93% among patients discharged. At follow-up, 15 out of 21 long-term survivors participated. Median follow-up time was 4.8±1.6 (range 2.8–6.1 years). Mean age at follow-up was 61±7.3 years, 11 (73%) were men. Neurological outcome with CPC 1 was found in 12 patients (80%), with CPC 2 in 2 patients (13%), and with CPC 3 in 1 patient (7%). Two had improved neurological status from CPC 2 to CPC 1 since discharge. Mean scores of the SF-36 revealed an overall high level of psychical and mental health in long-term survivors (Figure 1).

Conclusion

Long-term survival with good neurological outcome was high in patients with refractory OHCA treated with MCS despite prolonged resuscitation and severe metabolic derangement. These patients may expect a reasonable quality of life after discharge.

Funding Acknowledgement

Type of funding sources: Public hospital(s). Main funding source(s): Department of Cardiology, Aarhus University HospitalSnedkermester Sophus Jacobsen og hustru Astrid Jacobsens Fond

Extracorporeal cardiopulmonary resuscitation: a national study on the association between survival and biomarkers of hypoperfusion, inflammation, and organ failure

Background

In refractory out-of-hospital cardiac arrest (OHCA) with prolonged whole-body ischemia, global tissue injury proceeds even after establishment of circulation with extracorporeal cardiopulmonary resuscitation (ECPR).

Purpose

We aimed to investigate the role of biomarkers reflecting hypoperfusion, inflammation, and organ injury in prognostication of patients with refractory OHCA managed with ECPR.

Methods

This nationwide retrospective study included 226 adults with refractory OHCA managed with ECPR in Denmark (2011–2020). Biomarkers at admission and consecutively two days after ECPR initiation were retrieved. Odds ratio (OR) of 90-day survival were assessed by logistic regression analyses. Cut-off values were calculated from area under the curve (AUC) via the Youden index.

Results

Fifty-six patients (25%) survived to hospital discharge, all were still alive after 90-days and 91% had a favorable neurological status at discharge. Factors independently associated with 90-day survival were: male sex, shockable presenting rhythm, low flow time, platelets, pH, lactate, C-reactive protein, lactate dehydrogenase (LDH), alkaline phosphatase (ALP), and creatine kinase MB (CK-MB) level. Comparing the ability of standard predictive variables (age, sex, shockable presenting rhythm, witnessed arrest, and low flow time) and selected biomarkers (from multivariate analyses) in predicting 90-day survival, biomarkers day 2 after OHCA were significantly better than standard variables (AUC 0.79 vs. 0.56, p=0.01).

Conclusion

Biomarkers of hypoperfusion (low lactate and high pH), inflammation (high platelets and CRP), and organ failure (low LDH, ALP, and CK-MB) were independently associated with 90-day survival. Biomarkers on day 2 after OHCA (d-dimer, ALP, and CK-MB) were more predictive of 90-day survival than standard predictive variables.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Odense University Hospital's and Rigshospitalet's Common Research Foundation

Benefit of Intravenous Alteplase Before Thrombectomy Depends on ASPECTS

PURPOSE

Baseline variables could be used to guide the administration of additional intravenous alteplase (IVT) before mechanical thrombectomy (MT). The aim of this study was to determine how baseline imaging and demographic parameters modify the effect of IVT on clinical outcomes in patients with ischemic stroke due to large vessel occlusion.

METHODS

Multicenter retrospective cohort study of ischemic stroke patients triaged by multimodal-CT undergoing MT treatment after direct admission to an MT-eligible center. Inverse-probability weighting analysis (IPW) was used to assess the treatment effect of IVT adjusted for baseline variables. Multivariable logistic regression analysis with IPW-weighting and interaction terms for IVT was performed to predict functional independence (mRS 0-2 at 90-days).

RESULTS

720 patients were included, of which 366 (51%) received IVT. In IPW, the treatment effect of IVT on outcome (mRS 0-2) distinctively varied according to the ASPECTS subgroup (ASPECTS 9-10: +15%, ASPECTS 6-8: +7%, ASPECTS <6: -11%). In multivariable logistic regression analysis, IVT was independently associated with functional independence (aOR: 1.57, 95%CI: 1.16-2.14, p=0.003) and the interaction term was significant for ASPECTS and IVT revealing that IVT was only significantly associated with better outcomes in patients with higher ASPECTS. No other significant baseline variable interaction terms were identified.

INTERPRETATION

ASPECTS was the only baseline variable that showed a significant interaction with IVT for outcome prediction. The application of IVT in patients with an ASPECTS of <6 might have detrimental effects on outcome and may only be considered carefully. This article is protected by copyright. All rights reserved.

Intravenous tPA (Tissue-Type Plasminogen Activator) Correlates With Favorable Venous Outflow Profiles in Acute Ischemic Stroke

BACKGROUND

Intravenous tPA (tissue-type plasminogen activator) is often administered before endovascular thrombectomy (EVT). Recent studies have questioned whether tPA is necessary given the high rates of arterial recanalization achieved by EVT, but whether tPA impacts venous outflow (VO) is unknown. We investigated whether tPA improves VO profiles on baseline computed tomography (CT) angiography (CTA) images before EVT.

METHODS

Retrospective multicenter cohort study of patients with acute ischemic stroke due to large vessel occlusion undergoing EVT triage. Included patients underwent CT, CTA, and CT perfusion before EVT. VO profiles were determined by opacification of the vein of Labbé, sphenoparietal sinus, and superficial middle cerebral vein on CTA as 0, not visible; 1, moderate opacification; and 2, full. Pial arterial collaterals were graded on CTA, and tissue-level collaterals were assessed on CT perfusion using the hypoperfusion intensity ratio. Clinical and demographic data were determined from the electronic medical record. Using multivariable regression analysis, we determined the correlation between tPA administration and favorable VO profiles.

RESULTS

Seven hundred seventeen patients met inclusion criteria. Three hundred sixty-five patients received tPA (tPA+), while 352 patients were not treated with tPA (tPA-). Fewer tPA+ patients had atrial fibrillation (n=128 [35%] versus n=156 [44%]; P=0.012) and anticoagulants/antiplatelet treatment before acute ischemic stroke due to large vessel occlusion onset (n=130 [36%] versus n=178 [52%]; P<0.001) compared with tPA- patients. One hundred eighty-five patients (51%) in the tPA+ and 100 patients (28%) in the tPA- group exhibited favorable VO (P<0.001). Multivariable regression analysis showed that tPA administration was a strong independent predictor of favorable VO profiles (OR, 2.6 [95% CI, 1.7-4.0]; P<0.001) after control for favorable pial arterial CTA collaterals, favorable tissue-level collaterals on CT perfusion, age, presentation National Institutes of Health Stroke Scale, antiplatelet/anticoagulant treatment, history of atrial fibrillation and time from symptom onset to imaging.

CONCLUSIONS

In patients with acute ischemic stroke due to large vessel occlusion undergoing thrombectomy triage, tPA administration was strongly associated with the presence of favorable VO profiles.

The Cerebral Collateral Cascade: Comprehensive Blood Flow in Ischemic Stroke

BACKGROUND AND OBJECTIVES

Robust cerebral collaterals are associated with favorable outcomes in patients with acute ischemic stroke due to large vessel occlusion treated by thrombectomy. However, collateral status assessment mostly relies on single imaging biomarkers and a more comprehensive holistic approach may provide deeper insights into the biology of collateral perfusion on medical imaging. Comprehensive collateralization is defined as blood flow of cerebral arteries through the brain tissue and into draining veins. We hypothesized that a comprehensive analysis of the cerebral collateral cascade (CCC) on an arterial, tissue, and venous level would predict clinical and radiologic outcomes.

METHODS

This was a multicenter retrospective cohort study of patients with acute stroke undergoing thrombectomy triage. CCC was determined by quantifying pial arterial collaterals, tissue-level collaterals, and venous outflow (VO). Pial arterial collaterals were determined by CT angiography; tissue-level collaterals were assessed on CT perfusion. VO was assessed on CT angiography using the cortical vein opacification score. Three groups were defined: CCC+ (good pial collaterals, tissue-level collaterals, and VO), CCC- (poor pial collaterals, tissue-level collaterals, and VO), and CCCmixed (the remainder of the patients). Primary outcome was functional independence (modified Rankin Scale score 0-2) at 90 days. Secondary outcome was final infarct volume.

RESULTS

A total of 647 patients met inclusion criteria: 176 CCC+, 345 CCCmixed, and 126 CCC-. Multivariable ordinal logistic regression showed that CCC+ predicted good functional outcomes (odds ratio [OR] 18.9 [95% CI 8-44.5]; p < 0.001) compared with CCC- and CCCmixed. CCCmixed patients likely had better functional outcomes compared with CCC- patients (OR 2.5 [95% CI 1.2-5.4]; p = 0.014). Quantile regression analysis (50th percentile) showed that CCC+ (β -78.5, 95% CI -96.0 to -61.1; p < 0.001) and CCCmixed (β -64.0, 95% CI -82.4 to -45.6; p < 0.001) profiles were associated with considerably lower final infarct volumes compared with CCC- profiles.

DISCUSSION

Comprehensive assessment of the collateral blood flow cascade in patients with acute stroke is a strong predictor of clinical and radiologic outcomes in patients treated by thrombectomy.

Correlates of late-onset antipsychotic treatment resistance

Introduction

There is emerging evidence of heterogeneity within treatment-resistance schizophrenia (TRS), with some people not responding to antipsychotic treatment from illness onset and a smaller group becoming treatment-resistant after an initial response period. It has been suggested that these groups have different aetiologies. Few studies have investigated socio-demographic and clinical differences between early and late onset of TRS.

Objectives

This study aims to investigate socio-demographic and clinical correlates of late-onset of TRS.

Methods

Using data from the electronic health records of the South London and Maudsley, we identified a cohort of people with TRS. Regression analyses were conducted to identify correlates of the length of treatment to TRS. Analysed predictors include gender, age, ethnicity, positive symptoms severity, problems with activities of daily living, psychiatric comorbidities, involuntary hospitalisation and treatment with long-acting injectable antipsychotics.

Results

We observed a continuum of the length of treatment until TRS presentation. Having severe hallucinations and delusions at treatment start was associated shorter duration of treatment until the presentation of TRS.

Conclusions

Our findings do not support a clear cut categorisation between early and late TRS, based on length of treatment until treatment resistance onset. More severe positive symptoms predict earlier onset of treatment resistance.

Disclosure

DFdF, GKS, EF and IR have received research funding from Janssen and H. Lundbeck A/S. RDH and HS have received research funding from Roche, Pfizer, Janssen and Lundbeck. SES is employed on a grant held by Cardiff University from Takeda Pharmaceutical Comp

Accuracy of CT Perfusion-Based Core Estimation of Follow-up Infarction: Effects of Time Since Last Known Well

BACKGROUND AND OBJECTIVES

To assess the accuracy of baseline CT perfusion (CTP) ischemic core estimates.

METHODS

From SELECT (Optimizing Patient Selection for Endovascular Treatment in Acute Ischemic Stroke), a prospective multicenter cohort study of imaging selection, patients undergoing endovascular thrombectomy who achieved complete reperfusion (modified Thrombolysis In Cerebral Ischemia score 3) and had follow-up diffusion-weighted imaging (DWI) available were evaluated. Follow-up DWI lesions were coregistered to baseline CTP. The difference between baseline CTP core (relative cerebral blood flow [rCBF] <30%) volume and follow-up infarct volume was classified as overestimation (core ≥10 mL larger than infarct), adequate, or underestimation (core ≥25 mL smaller than infarct) and spatial overlap was evaluated.

RESULTS

Of 101 included patients, median time from last known well (LKW) to imaging acquisition was 138 (82-244) minutes. The median baseline ischemic core estimate was 9 (0-31.9) mL and median follow-up infarct volume was 18.4 (5.3-68.7) mL. All 6/101 (6%) patients with overestimation of the subsequent infarct volume were imaged within 90 minutes of LKW and achieved rapid reperfusion (within 120 minutes of CTP). Using rCBF <20% threshold to estimate ischemic core in patients presenting within 90 minutes eliminated overestimation. Volumetric correlation between the ischemic core estimate and follow-up imaging improved as LKW time to imaging acquisition increased: Spearman ρ <90 minutes 0.33 (p = 0.049), 90-270 minutes 0.63 (p < 0.0001), >270 minutes 0.86 (p < 0.0001). Assessment of the spatial overlap between baseline CTP ischemic core lesion and follow-up infarct demonstrated that a median of 3.2 (0.0-9.0) mL of estimated core fell outside the subsequent infarct. These regions were predominantly in white matter.

DISCUSSION

Significant overestimation of irreversibly injured ischemic core volume was rare, was only observed in patients who presented within 90 minutes of LKW and achieved reperfusion within 120 minutes of CTP acquisition, and occurred primarily in white matter. Use of a more conservative (rCBF <20%) threshold for estimating ischemic core in patients presenting within 90 minutes eliminated all significant overestimation cases.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov: NCT03876457.

Favourable arterial, tissue-level and venous collaterals correlate with early neurological improvement after successful thrombectomy treatment of acute ischaemic stroke

BACKGROUND AND PURPOSE

Early neurological improvement (ENI) after thrombectomy is associated with better long-term outcomes in patients with acute ischaemic stroke due to large vessel occlusion (AIS-LVO). Whether cerebral collaterals influence the likelihood of ENI is poorly described. We hypothesised that favourable collateral perfusion at the arterial, tissue-level and venous outflow (VO) levels is associated with ENI after thrombectomy.

MATERIALS AND METHODS

Multicentre retrospective study of patients with AIS-LVO treated by thrombectomy. Tissue-level collaterals (TLC) were measured on cerebral perfusion studies by the hypoperfusion intensity ratio. VO and pial arterial collaterals (PAC) were determined by the Cortical Vein Opacification Score and the modified Tan scale on CT angiography, respectively. ENI was defined as improvement of ≥8 points or a National Institutes of Health Stroke Scale score of 0 hour or 1 24 hours after treatment. Multivariable regression analyses were used to determine the association of collateral biomarkers with ENI and good functional outcomes (modified Rankin Scale 0-2).

RESULTS

646 patients met inclusion criteria. Favourable PAC (OR: 1.9, CI 1.2 to 3.1; p=0.01), favourable VO (OR: 3.3, CI 2.1 to 5.1; p<0.001) and successful reperfusion (OR: 3.1, CI 1.7 to 5.8; p<0.001) were associated with ENI, but favourable TLC were not (p=0.431). Good functional outcomes at 90-days were associated with favourable TLC (OR: 2.2, CI 1.4 to 3.6; p=0.001), VO (OR: 5.7, CI 3.5 to 9.3; p<0.001) and ENI (OR: 5.7, CI 3.3 to 9.8; p<0.001), but not PAC status (p=0.647).

CONCLUSION

Favourable PAC and VO were associated with ENI after thrombectomy. Favourable TLC predicted longer term functional recovery after thrombectomy, but the impact of TLC on ENI is strongly dependent on vessel reperfusion.

Healthcare cost variation in patients with heart failure: a nationwide study

OBJECTIVE

Heart failure (HF) imposes a major economic burden; however, the individual management for patients varies, potentially leading to large cost heterogeneity. The aim of this study was to investigate the spectrum of health cost by patients with HF and factors associated with high direct health cost.

STUDY DESIGN

This was a nationwide, retrospective longitudinal study.

METHODS

Using Danish nationwide registries from 2012 to 2015, we identified all patients aged >18 years with a first-time diagnosis of HF. Total health costs were investigated using two perspectives-at index and during 3 years of follow-up. Patients were investigated by decile cost groups. A multivariable logistic regression was used to identify variables associated with being in the highest cost decile compared with the rest (90%).

RESULTS

A total of 11,170 patients with HF were included, and those in the highest cost decile (n = 1117, 10%) were younger (69 vs. 75 years), fewer were females (34% vs. 43%), and more were inpatients (83% vs. 70%) compared with the rest of the patients with HF (n = 10,053, 90%). Patients in the highest cost decile (10%) incurred a 30 times higher cost with a mean total health cost in index year of €86,607 compared with €2893 for patients in lowest cost decile (10%). The results were similar for 3 years aggregated (€139,473 vs. €4086), corresponding to a 34 times higher cost.

CONCLUSION

In patients with HF, a large total health cost heterogeneity exists with younger age, inpatient admittance, male sex, and comorbidities being associated with a higher likelihood of belonging to the highest cost group.

Cerebral Hypoperfusion Intensity Ratio Is Linked to Progressive Early Edema Formation

The hypoperfusion intensity ratio (HIR) is associated with collateral status and reflects the impaired microperfusion of brain tissue in patients with acute ischemic stroke and large vessel occlusion (AIS-LVO). As a deterioration in cerebral blood flow is associated with brain edema, we aimed to investigate whether HIR is correlated with the early edema progression rate (EPR) determined by the ischemic net water uptake (NWU) in a multicenter retrospective analysis of AIS-LVO patients anticipated for thrombectomy treatment. HIR was automatically calculated as the ratio of time-to-maximum (TMax) > 10 s/(TMax) > 6 s. HIRs < 0.4 were regarded as favorable (HIR+) and ≥0.4 as unfavorable (HIR−). Quantitative ischemic lesion NWU was delineated on baseline NCCT images and EPR was calculated as the ratio of NWU/time from symptom onset to imaging. Multivariable regression analysis was used to assess the association of HIR with EPR. This study included 731 patients. HIR+ patients exhibited a reduced median NWU upon admission CT (4% (IQR: 2.1−7.6) versus 8.2% (6−10.4); p < 0.001) and less median EPR (0.016%/h (IQR: 0.007−0.04) versus 0.044%/h (IQR: 0.021−0.089; p < 0.001) compared to HIR− patients. Multivariable regression showed that HIR+ (β: 0.53, SE: 0.02; p = 0.003) and presentation of the National Institutes of Health Stroke Scale (β: 0.2, SE: 0.0006; p = 0.001) were independently associated with EPR. In conclusion, favorable HIR was associated with lower early edema progression and decreased ischemic edema formation on baseline NCCT.

Abstract WP103: Comparison Of Acute Infarct Lesions Between Non-contrast CT, DWI And FLAIR Using Back-to-back Imaging

Introduction: Size and location of the acute infarct is a major determinant of stroke outcome and eligibility for therapy. Recently, there have been efforts to train deep learning networks to detect lesions on Non-Contrast CT (NCCT) using concurrent DWI imaging as the gold standard. However, little is known about the radiological correspondence between concurrent NCCT and DWI lesion sizes. We performed an exploratory analysis comparing the stroke lesion volume on acute NCCT to that on DWI and FLAIR images performed shortly after.

Methods: Population: DEFUSE 3 trial patients scanned 6-16h after last known well with DWI and NCCT <1h apart. NCCT was segmented using an algorithm detecting more than 5% depression compared to the contralateral homologous region. The DWIs and FLAIR were co-registered to NCCT and manually segmented in ITK-Snap.

Results: Thirteen patients fulfilled inclusion criteria. DWI volumes were (median, [IQR]) 52 mL [39 - 102], FLAIR volumes 35 mL [18 - 66] and NCCT lesion volumes 14 mL [8 - 22]. NCCT lesions were significantly smaller than both DWI and FLAIR, p < 0.001 and p < 0.048. The Dice coefficient was 0.2 [0.1 - 0.3] for FLAIR vs NCCT and 0.3 [0.1 - 0.5] for DWI vs NCCT.

Conclusion: NCCT lesion volumes were consistently smaller than both DWI and FLAIR lesions although the volumetric agreement with FLAIR lesions was better. Both FLAIR and NCCT are sensitive to influx of parenchymal water and as such may have more similar lesions than DWI imaging which is sensitive to early occurring intraparenchymal displacements. The findings suggest that the training of deep learning networks to detect early NCCT hypodensity should focus on FLAIR or expert outlines drawn directly on the NCCT rather than DWI as the gold standard.

Abstract 127: Anatomical Predictors Of Malignant Cerebral Edema Using Voxel-based Lesion Symptom Mapping

Introduction: Prior publications indicate an increased risk of developing malignant cerebral edema in acute ischemic stroke patients with temporal lobe involvement. We examined on a voxel-by-voxel basis whether topographic locations of baseline diffusion and perfusion weighted MRI lesions could predict subsequent need for treatment of malignant cerebral edema with either decompressive hemicraniectomy (DHC) or hyperosmolar therapy (HT).

Methods: We used a registry of 898 patients evaluated for acute treatment for suspected large vessel occlusion (LVO) stroke. Fifty-nine cases, receiving either DHC and/or HT and having sufficient data for evaluation, were manually matched with 59 controls for age, lesion size, and Thrombolysis in Cerebral Infarction (TICI) score. Binary masks of ADC + Tmax >6s lesions generated from automated RAPID software output were created. Lesions were co-registered to standard MNI atlas space. Voxel-based lesion symptom mapping (Version 2.55) was used to generate statistical maps of lesion contribution to malignant cerebral edema formation. Maps were thresholded to P<0.01 on basis of cluster size and permutation method. Hemispheres were combined to increase statistical power.

Results and Conclusions: 118 patients were analyzed. After controlling for age, TICI score, and lesion volume, only punctate regions of the parieto-occipital lobe were found to be mildly predictive of the need for either DHC or HT (T-scores 2.5-3, p<0.01). There does not appear to be any significant topographic region of the brain involved on baseline diffusion-perfusion MRI that predicts subsequent need for treatment of malignant cerebral edema in patients with LVO stroke.

Abstract TMP12: Artificial Intelligence Prediction Of Delayed Cerebral Ischemia After Cerebral Aneurysm Rupture

Background: Aneurysmal subarachnoid hemorrhage (aSAH) results in significant mortality and disability, which is worsened by the development of Delayed Cerebral Ischemia (DCI). Tests to identify patients with DCI prospectively are needed.

Objective: We created a machine learning (ML) system based on clinical variables to predict DCI in aSAH patients and to determine which variables have the most impact on DCI prediction.

Methods: We performed a retrospective cohort study of aSAH patients from January 2006 to September 2014. The ML algorithm was trained on age, sex, HTN, diabetes, hyperlipidemia, CHF, CAD, smoking history, family history of aneurysm, Fisher Grade, Hunt and Hess score, and external ventricular drain (EVD) placement. Prediction outcome of the ML algorithm was DCI+, which was defined as new neurologic deterioration that could not be attributed to aneurysm re-bleeding, hydrocephalus, infection, seizure, hyponatremia or other metabolic abnormality. SHAP was used to explain and visualize the role of each feature’s contribution to the model prediction.

Results: 500 aSAH patients were identified and 369 met inclusion criteria: 70 patients developed DCI (DCI+) and 299 did not (DCI-). Random Forest was selected for this project after a 5-fold cross validation. 276 cases (222 DCI- and 54 DCI+) were used for training and 93 cases (77 DCI- and 16 DCI+) were used for testing the algorithm. The Random Forest ML algorithm predicted DCI: Accuracy: 81.7%, Sensitivity: 12.5%, Specificity: 96.1%, PPV: 40%, and NPV: 84.1%. SHAP value demonstrated Age, EVD placement, Fisher Grade, and Hunt and Hess score, and HTN had the highest predictive values for DCI. Lower age, absence of hypertension, higher Hunt and Hess score, higher Fisher Grade, and EVD placement increased risk of DCI.

Conclusion: ML models based upon clinical variable predict DCI with high specificity and modest accuracy. The addition of imaging or other biomarkers may improve the sensitivity of the ML algorithm.

Abstract 8: Hypoperfusion Lesion And Target Mismatch Prediction In Acute Ischemic Stroke From Baseline Mr Diffusion Imaging Using A 3d Convolutional Neural Network

Purpose: Perfusion imaging assesses target mismatch but requires contrast and processing software. Clinical/diffusion mismatch can miss cases that have target mismatch and could benefit from thrombectomy. We explored whether a neural network can predict hypoperfusion and identify target mismatch from diffusion-weighted imaging (DWI) and clinical information alone.

Methods: Acute ischemic stroke cases with baseline MR perfusion and DWI were included from two multi-center trials and one registry for model development and a separate randomized trial for external validation. MR perfusion images were processed by RAPID, which segments Tmax lesion (Tmax≥6s) and the ischemic core lesion (apparent diffusion coefficient [ADC]≤ 620). A 3D U-Net was trained using baseline DWI, ADC, NIH stroke scale, and side of stroke as input, and the union of Tmax and ischemic core segmentation as the ground truth. 5-fold cross-validation was performed for model development cohort. Model performance was evaluated by Dice score coefficient (DSC) and volume difference. Sensitivity and specificity of model target mismatch and clinical/diffusion mismatch criteria from the DAWN were compared, using the DEFUSE 3 target mismatch as reference.

Results: 413 patients were included for model development and 46 for external validation. In model development and external validation cohort, the model achieved median DSC of 0.61 (IQR 0.45, 0.71) and 0.62 (IQR 0.53, 0.72); and volume difference of 3 ml (IQR -37, 41) and 7 ml (IQR -24, 32), respectively. Compared to the clinical/diffusion mismatch approach, the model identified target mismatch with a sensitivity of 89.5% vs 49.3%, a specificity of 77.5% vs 89.2% in the model development cohort, and a sensitivity of 95.6% vs 41.3% in external validation cohort.

Conclusion: A 3D U-Net can predict hypoperfusion lesions from baseline DWI and clinical information, with more sensitive classification of target mismatch than clinical/diffusion mismatch.

Prediction of Stroke Infarct Growth Rates by Baseline Perfusion Imaging

BACKGROUND AND PURPOSE

Computed tomography perfusion imaging allows estimation of tissue status in patients with acute ischemic stroke. We aimed to improve prediction of the final infarct and individual infarct growth rates using a deep learning approach.

METHODS

We trained a deep neural network to predict the final infarct volume in patients with acute stroke presenting with large vessel occlusions based on the native computed tomography perfusion images, time to reperfusion and reperfusion status in a derivation cohort (MR CLEAN trial [Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands]). The model was internally validated in a 5-fold cross-validation and externally in an independent dataset (CRISP study [CT Perfusion to Predict Response to Recanalization in Ischemic Stroke Project]). We calculated the mean absolute difference between the predictions of the deep learning model and the final infarct volume versus the mean absolute difference between computed tomography perfusion imaging processing by RAPID software (iSchemaView, Menlo Park, CA) and the final infarct volume. Next, we determined infarct growth rates for every patient.

RESULTS

We included 127 patients from the MR CLEAN (derivation) and 101 patients of the CRISP study (validation). The deep learning model improved final infarct volume prediction compared with the RAPID software in both the derivation, mean absolute difference 34.5 versus 52.4 mL, and validation cohort, 41.2 versus 52.4 mL (P<0.01). We obtained individual infarct growth rates enabling the estimation of final infarct volume based on time and grade of reperfusion.

CONCLUSIONS

We validated a deep learning-based method which improved final infarct volume estimations compared with classic computed tomography perfusion imaging processing. In addition, the deep learning model predicted individual infarct growth rates which could enable the introduction of tissue clocks during the management of acute stroke.

Cerebrovascular Collateral Integrity in Pediatric Large Vessel Occlusion: Analysis of the Save ChildS Study

BACKGROUND AND OBJECTIVES

Robust cerebrovascular collaterals in adult patients with large vessel occlusion stroke have been associated with longer treatment windows, better recanalization rates, and improved outcomes, but the role of collaterals in pediatric stroke is not known. The primary aim was to determine whether favorable collaterals correlated with better radiographic and clinical outcomes in children with ischemic stroke who underwent thrombectomy.

METHODS

This study analyzed a subset of children enrolled in SaveChildS, a retrospective, multicenter, observational cohort study of 73 pediatric patients with stroke who underwent thrombectomy between 2000 and 2018 at 27 US and European centers. Included patients had baseline angiographic imaging and follow-up modified Rankin Scale scores available for review. Posterior circulation occlusions were excluded. Cerebrovascular collaterals were graded on acute neuroimaging by 2 blinded neuroradiologists according to the Tan collateral score, in which favorable collaterals are defined as >50% filling and unfavorable collaterals as <50% filling distal to the occluded vessel. Collateral status was correlated with clinical and neuroimaging characteristics and outcomes. Between-group comparisons were performed with the Wilcoxon rank-sum test for continuous variables or Fisher exact test for binary variables.

RESULTS

Thirty-three children (mean age 10.9 [SD ±4.9]) years were included; 14 (42.4%) had favorable collaterals. Median final stroke volume as a percent of total brain volume (TBV) was significantly lower in patients with favorable collaterals (1.35% [interquartile range (IQR) 1.14%-3.76%] vs 7.86% [IQR 1.54%-11.07%], p = 0.049). Collateral status did not correlate with clinical outcome, infarct growth, or final Alberta Stroke Program Early CT Score (ASPECTS) in our cohort. Patients with favorable collaterals had higher baseline ASPECTS (7 [IQR 6-8] vs 5.5 [4-6], p = 0.006), smaller baseline ischemic volume (1.57% TBV [IQR 1.09%-2.29%] vs 3.42% TBV [IQR 1.26%-5.33%], p = 0.035), and slower early infarct growth rate (2.4 mL/h [IQR 1.5-5.1 mL/h] vs 10.4 mL/h [IQR 3.0-30.7 mL/h], p = 0.028).

DISCUSSION

Favorable collaterals were associated with smaller final stroke burden and slower early infarct growth rate but not with better clinical outcome in our study. Prospective studies are needed to determine the impact of collaterals in childhood stroke.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that in children with ischemic stroke undergoing thrombectomy, favorable collaterals were associated with improved radiographic outcomes but not with better clinical outcomes.

Venous outflow profiles are associated with early edema progression in ischemic stroke

BACKGROUND

In patients with acute ischemic stroke due to large vessel occlusion (AIS-LVO), development of extensive early ischemic brain edema is associated with poor functional outcomes, despite timely treatment. Robust cortical venous outflow (VO) profiles correlate with favorable tissue perfusion. We hypothesized that favorable VO profiles (VO+) correlate with a reduced early edema progression rate (EPR) and good functional outcomes.

METHODS

Multicenter, retrospective analysis to investigate AIS-LVO patients treated by mechanical thrombectomy between May 2013 and December 2020. Baseline computed tomography angiography (CTA) was used to determine VO using the cortical vein opacification score (COVES); VO+ was defined as COVES ⩾ 3 and unfavorable as COVES ⩽ 2. EPR was determined as the ratio of net water uptake (NWU) on baseline non-contrast CT and time from symptom onset to admission imaging. Multivariable regression analysis was performed to assess primary (EPR) and secondary outcome (good functional outcomes defined as 0-2 points on the modified Rankin scale).

RESULTS

A total of 728 patients were included. Primary outcome analysis showed VO+ (β: -0.03, SE: 0.009, p = 0.002), lower presentation National Institutes of Health Stroke Scale (NIHSS; β: 0.002, SE: 0.001, p = 0.002), and decreased time from onset to admission imaging (β: -0.00002, SE: 0.00004, p < 0.001) were independently associated with reduced EPR. VO+ also predicted good functional outcomes (odds ratio (OR): 5.07, 95% CI: 2.839-9.039, p < 0.001), while controlling for presentation NIHSS, time from onset to imaging, general vessel reperfusion, baseline Alberta Stroke Program Early CT Score, infarct core volume, EPR, and favorable arterial collaterals.

CONCLUSIONS

Favorable VO profiles were associated with slower infarct edema progression and good long-term functional outcomes as well as better neurological status and ischemic brain alterations at admission.

What predicts poor outcome after successful thrombectomy in early time window?

BACKGROUND

Half of the patients with large vessel occlusion (LVO)-related acute ischemic stroke (AIS) who undergo endovascular reperfusion are dead or dependent at 3 months. We hypothesize that in addition to established prognostic factors, baseline imaging profile predicts outcome among reperfusers.

METHODS

Consecutive patients receiving endovascular treatment (EVT) within 6 hours after onset with Thrombolysis In Cerebral Infarction (TICI) 2b, 2c and 3 revascularization were included. Poor outcome was defined by a modified Rankin scale (mRS) 3-6 at 90 days. No mismatch (NoMM) profile was defined as a mismatch (MM) ratio ≤1.2 and/or a volume <10 mL on pretreatment imaging.

RESULTS

187 patients were included, and 81 (43%) had a poor outcome. Median delay from stroke onset to the end of EVT was 259 min (IQR 209-340). After multivariable logistic regression analysis, older age (OR 1.26, 95% CI 1.06 to 1.5; p=0.01), higher National Institutes of Health Stroke Scale (NIHSS) (OR 1.15, 95% CI 1.06 to 1.25; p<0.0001), internal carotid artery (ICA) occlusion (OR 3.02, 95% CI 1.2 to 8.0; p=0.021), and NoMM (OR 4.87, 95% CI 1.09 to 22.8; p=0.004) were associated with poor outcome. In addition, post-EVT hemorrhage (OR 3.64, 95% CI 1.5 to 9.1; p=0.04) was also associated with poor outcome.

CONCLUSIONS

The absence of a penumbra defined by a NoMM profile on baseline imaging appears to be an independent predictor of poor outcome after reperfusion. Strategies aiming to preserve the penumbra may be encouraged to improve these patients' outcomes.

Cerebral venous outflow profiles are associated with the first pass effect in endovascular thrombectomy

Background

Recent studies found that favorable venous outflow (VO) profiles are associated with higher reperfusion rates after mechanical thrombectomy (MT) in patients with acute ischemic stroke due to large vessel occlusion (AIS-LVO). Fewer retrieval attempts and first-pass revascularization during MT lead to better functional outcomes.

Objective

To examine the hypothesis that favorable VO profiles assessed on baseline CT angiography (CTA) images correlate with successful vessel reperfusion after the first retrieval attempt and fewer retrieval attempts.

Methods

A multicenter retrospective cohort study of patients with AIS-LVO treated by MT. Baseline CTA was used to determine the cortical vein opacification score (COVES). Favorable VO was defined as COVES ≥3. Primary outcomes were successful with excellent vessel reperfusion status, defined as Thrombolysis in Cerebral Infarction (TICI) 2b/3 and 2c/3 after first retrieval attempt.

Results

617 patients were included in this study, of whom 205 (33.2%) had first pass reperfusion. In univariate analysis, ordinal COVES (p=0.011) values were significantly higher in patients with first pass than in those with non-first pass reperfusion, while the number of patients exhibiting favorable pial arterial collaterals using the Maas scale on CTA did not differ (p=0.243). In multivariable logistic regression analysis, higher COVES were independently associated with TICI 2b/3 (OR=1.25, 95% CI 1.1 to 1.42; p=0.001) and TICI 2c/3 (OR=1.2, 95% CI 1.04 to 1.36; p=0.011) reperfusion after one retrieval attempt, controlling for penumbra volume and time from symptom onset to vessel reperfusion.

Conclusions

Favorable VO, classified as higher COVES, is independently associated with successful and excellent first pass reperfusion in patients with AIS-LVO treated by endovascular thrombectomy.

Mechanical circulatory support for refractory out-of-hospital cardiac arrest: a nationwide multicentre study

Background

Extracorporeal cardiopulmonary resuscitation (ECPR) has shown potential as a salvage therapy for patients with refractory out-of-hospital cardiac arrest (OHCA). Despite growing interest in and a growing body of literature on ECPR for refractory OHCA, robust evidence on patient eligibility is still lacking.

Purpose

To describe the survival, neurological outcome, and adherence to the national consensus with respect to use of ECPR for OHCA, and to identify factors associated with outcome.

Methods

Retrospective, observational cohort study of patients who underwent ECPR for OHCA at four cardiac arrest centres. Binary logistic regression and Kaplan-Meier survival curves were performed to assess association with 30-day mortality.

Results

A total of 259 patients receiving ECPR for OHCA between July 2011 and December 2020 were included in the study. Thirty-day survival was 26% and a good neurological outcome Cerebral Performance Category (CPC) 1–2 was observed in 94% of patients at discharge. Strict adherence to the national consensus showed a 30-day survival rate of 30%. Adding one or more of the following criteria to the national consensus: signs of life during cardiopulmonary resuscitation (CPR), pre-hospital low-flow &lt;100 minutes, pH &gt;6.8 and lactate &lt;15 mmol/L increased the survival rate to 48%, but would exclude 58% of the survivors from the current cohort. Logistic regression identified initial presenting rhythm with asystole (RR 1.36, 95% CI 1.18–1.57), pulseless electrical activity (PEA) (RR 1.20, 95% CI 1.03–1.41), initial pH &lt;6.8 (RR 1.28, 95% CI 1.12–1.46) and lactate levels &gt;15 mmol/L (RR 1.16, 95% CI 1.16–1.53) as factors associated with increased risk of 30-day mortality. Patients presenting signs of life during CPR had threefold higher survival rate than patients without signs of life (45% versus 13%, p&lt;0.001)

Conclusion

A high survival rate with a good neurological outcome was observed in this population of patients treated with ECPR for OHCA. Signs of life during CPR may aid the decision-making in the selection of appropriate candidates. Stringent patient selection for ECPR may produce higher survival rates but potentially withholds life-saving treatment in a significant proportion of survivors, why optimization of the selection criteria is still necessary.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): This work was supported by the Danish Heart Foundation [20-R142-A9498-22178]; and Health Research Foundation of Central Denmark Region [R64-A3178-B1349] Survival and adherence to consensusSigns of life during CPR

Distinct intra-arterial clot localization affects tissue-level collaterals and venous outflow profiles

BACKGROUND AND PURPOSE

Arterial clot localization affects collateral flow to ischemic brain in patients with acute ischemic stroke due to large vessel occlusion (AIS-LVO). We determined the association between vessel occlusion locations, tissue-level collaterals (TLC), and venous outflow (VO) profiles and their impact on good functional outcomes.

METHODS

We conducted a multicenter retrospective cohort study of consecutive AIS-LVO patients who underwent thrombectomy triage. Baseline computed tomographic angiography (CTA) was used to localize vessel occlusion, which was dichotomized into proximal vessel occlusion (PVO; internal carotid artery and proximal first segment of the middle cerebral artery [M1]) and distal vessel occlusion (DVO; distal M1 and M2), and to assess collateral scores. TLC were assessed on computed tomographic perfusion data using the hypoperfusion intensity ratio. VO was determined on baseline CTA by the cortical vein opacification score. Primary outcomes were favorable VO and TLC; secondary outcome was the modified Rankin Scale after 90 days.

RESULTS

A total of 649 patients met inclusion criteria. Of these, 376 patients (58%) had a PVO and 273 patients (42%) had a DVO. Multivariate ordinal logistic regression showed that DVO predicted favorable TLC (odds ratio [OR] = 1.77, 95% confidence interval [CI] = 1.24-2.52, p = 0.002) and favorable VO (OR = 7.2, 95% CI = 5.2-11.9, p < 0.001). DVO (OR = 3.4, 95% CI = 2.1-5.6, p < 0.001), favorable VO (OR = 6.4, 95% CI = 3.8-10.6, p < 0.001), and favorable TLC (OR = 3.2, 95% CI = 2-5.3, p < 0.001), but not CTA collaterals (OR = 1.07, 95% CI = 0.60-1.91, p = 0.813), were predictors of good functional outcome.

CONCLUSIONS

DVO in AIS-LVO patients correlates with favorable TLC and VO profiles, which are associated with good functional outcome.

Perfusion imaging-based tissue-level collaterals predict ischemic lesion net water uptake in patients with acute ischemic stroke and large vessel occlusion

Ischemic lesion Net Water Uptake (NWU) quantifies cerebral edema formation and likely correlates with the microvascular perfusion status of patients with acute ischemic stroke due to large vessel occlusion (AIS-LVO). We hypothesized that favorable tissue-level collaterals (TLC) predict less NWU and good functional outcomes. We performed a retrospective multicenter analysis of AIS-LVO patients who underwent thrombectomy triage. TLC were measured on cerebral perfusion studies using the hypoperfusion intensity ratio (HIR; volume ratio of brain tissue with [Tmax > 10 sec/Tmax > 6 sec]); favorable TLC were regarded as HIR ≤ 0.4. NWU was determined using a quantitative densitometry approach on follow-up CT. Primary outcome was NWU. Secondary outcome was a good functional outcome (modified Rankin Scale [mRS] 0-2).580 patients met inclusion criteria. Favorable TLC (β: 4.23, SE: 0.65; p < 0.001) predicted smaller NWU after treatment. Favorable TLC (OR: 2.35, [95% CI: 1.31-4.21]; p < 0.001), and decreased NWU (OR: 0.75, [95% CI: 0.70-0.79]; p < 0.001) predicted good functional outcome, while controlling for age, glucose, CTA collaterals, baseline NIHSS and good vessel reperfusion status.We conclude that favorable TLC predict less ischemic lesion NWU after treatment in AIS-LVO patients. Favorable TLC and decreased NWU were independent predictors of good functional outcome.