CT perfusion core and ASPECT score prediction of outcomes in DEFUSE 3

Automated estimation of ischemic core volume on noncontrast-enhanced CT via machine learning

BACKGROUND

Accurate estimation of ischemic core on baseline imaging has treatment implications in patients with acute ischemic stroke (AIS). Machine learning (ML) algorithms have shown promising results in estimating ischemic core using routine noncontrast computed tomography (NCCT).

OBJECTIVE

We used an ML-trained algorithm to quantify ischemic core volume on NCCT in a comparative analysis to pretreatment magnetic resonance imaging (MRI) diffusion-weighted imaging (DWI) in patients with AIS.

METHODS

Patients with AIS who had both pretreatment NCCT and MRI were enrolled. An automatic segmentation ML approach was applied using Brainomix software (Oxford, UK) to segment the ischemic voxels and calculate ischemic core volume on NCCT. Ischemic core volume was also calculated on baseline MRI DWI. Comparative analysis was performed using Bland-Altman plots and Pearson correlation.

RESULTS

A total of 72 patients were included. The time-to-stroke onset time was 134.2/89.5 minutes (mean/median). The time difference between NCCT and MRI was 64.8/44.5 minutes (mean/median). In patients who presented within 1 hour from stroke onset, the ischemic core volumes were significantly (p  =  0.005) underestimated by ML-NCCT. In patients presented beyond 1 hour, the ML-NCCT estimated ischemic core volumes approximated those obtained by MRI-DWI and with significant correlation (r  =  0.56, p < 0.001).

CONCLUSION

The ischemic core volumes calculated by the described ML approach on NCCT approximate those obtained by MRI in patients with AIS who present beyond 1 hour from stroke onset.

Early identification of stroke through deep learning with multi-modal human speech and movement data

JOURNAL/nrgr/04.03/01300535-202501000-00031/figure1/v/2024-05-14T021156Z/r/image-tiff Early identification and treatment of stroke can greatly improve patient outcomes and quality of life. Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale (CPSS) and the Face Arm Speech Test (FAST) are commonly used for stroke screening, accurate administration is dependent on specialized training. In this study, we proposed a novel multimodal deep learning approach, based on the FAST, for assessing suspected stroke patients exhibiting symptoms such as limb weakness, facial paresis, and speech disorders in acute settings. We collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements, facial expressions, and speech tests based on the FAST. We compared the constructed deep learning model, which was designed to process multi-modal datasets, with six prior models that achieved good action classification performance, including the I3D, SlowFast, X3D, TPN, TimeSformer, and MViT. We found that the findings of our deep learning model had a higher clinical value compared with the other approaches. Moreover, the multi-modal model outperformed its single-module variants, highlighting the benefit of utilizing multiple types of patient data, such as action videos and speech audio. These results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke, thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.

Predicting final infarct size and clinical outcomes in patients with acute ischemic stroke after endovascular thrombectomy using the Alberta Stroke Program early CT score on venous-phase CT

BACKGROUND

The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is a semi-quantitative tool for evaluating the extent and distribution of early ischemic changes.

PURPOSE

To assess the value of ASPECTS on non-contrast CT (NCCT), arterial-phase CT (APCT), or venous-phase CT (VPCT) in predicting the final infarct core (IC) on follow-up diffusion-weighted imaging (DWI) and the clinical outcomes of patients with acute ischemic stroke (AIS) after endovascular thrombectomy (EVT).

MATERIAL AND METHODS

In total, 120 patients with AIS who underwent EVT in our center were retrospectively enrolled. Correlations between CT-ASPECTS and follow-up DWI-ASPECTS were analyzed using Spearman's rank correlation coefficient. Mean differences and limit of agreement (LoA) between CT-ASPECTS and follow-up DWI-ASPECTS were assessed using the Bland-Altman plots. Multivariate logistic regression and receiver operating characteristic curve analyses were used to identify independent factors and evaluate their performances in predicting the clinical outcomes.

RESULTS

VPCT-ASPECTS exhibited the highest correlation with follow-up DWI-ASPECTS (r = 0.846, P < 0.001), followed by APCT-ASPECTS (r = 0.613, P < 0.001) and NCCT-ASPECTS (r = 0.557, P < 0.001). The mean difference between VPCT-ASPECTS and follow-up DWI-ASPECTS was 0.0 (limit of agreement = -2.1 to 2.1). National Institute of Health Stroke Scale (NIHSS) scores at admission (NIHSSpre) (odds ratio [OR]=1.162, 95% confidence interval [CI]=1.063-1.270; P = 0.001) and VPCT-ASPECTS (OR=0.728, 95% CI=0.535-0.991; P = 0.044) were the independent factors associated with clinical outcomes. The combined model integrating NIHSSpre and VPCT-ASPECTS exhibited an excellent performance in predicting good clinical outcomes (area under curve [AUC]=0.807; sensitivity=75.0%; specificity=72.3%).

CONCLUSION

VPCT-ASPECTS may be a promising imaging biomarker to predict the final IC and the clinical outcome of the patients with AIS after EVT.

Predictors of good outcomes and mortality after thrombectomy for basilar artery occlusion within 12 hours of onset

BACKGROUND

Patients with acute basilar artery occlusion (ABAO) who undergo combined standard medical treatment (SMT) and endovascular thrombectomy (EVT) may still have unsatisfactory outcomes. This study was conducted to identify the factors that may impact their outcomes.

METHODS

We retrospectively reviewed the data of all patients with ABAO combined with SMT and EVT in the endovascular treatment for acute basilar artery occlusion (ATTENTION) trial. A good outcome is defined as a modified Rankin Scale (mRS) score of 0-3, a poor outcome as mRS score of 4-6, and mortality as death at 90-day follow-up. The study analyzed various factors influencing the patients' good outcomes and mortality.

RESULTS

The study included 221 patients (148 men and 73 women). Among these patients, 45.7% achieved an mRS score of 0-3, while the overall mortality rate was 37.1% (82/221). A good outcome was significantly associated with younger age (adjusted OR 0.96; 95% CI 0.93 to 0.99; P=0.019), a baseline posterior circulation Alberta Stroke Program Early CT Score (pc-ASPECTS) of 8-10 (adjusted OR 2.34; 95% CI 1.07 to 5.12; P=0.034), and post-procedure pc-ASPECTS of 8-10 (adjusted OR 1.40; 95% CI 1.07 to 1.84; P=0.013). Additionally, time from puncture to reperfusion (adjusted OR 2.02; 95% CI 1.2 to 3.41; P=0.008) and intracranial hemorrhage (adjusted OR 3.59; 95% CI 1.09 to 11.8; P=0.035) were associated with 90-day mortality.

CONCLUSIONS

Younger age, baseline pc-ASPECTS of 8-10, and higher post-procedure pc-ASPECTS could effectively predict good outcomes for patients with ABAO undergoing EVT. Additionally, a prolonged time from puncture to reperfusion and intracranial hemorrhage can independently predict mortality.

TRIAL REGISTRATION NUMBER

NCT04751708.

Nomogram for Predicting Emergent Conversion to General Anaesthesia in Stroke Patients During Thrombectomy

RATIONALE AND OBJECTIVES

The aim of this study was to develop and validate a nomogram for predicting emergent conversion to general anaesthesia (GA) in stroke patients during thrombectomy.

METHODS

In this retrospective study, 458 patients (320 and 138 were randomised into the training and validation cohorts) were enroled. Univariable and multivariable logistic regression analyses were employed to identify risk factors for emergent conversion to GA. Subsequently, a nomogram was constructed based on the identified risk factors. The discriminative ability, calibration, and clinical utility of the nomogram were assessed in both the training and validation cohorts using receiver operating characteristic (ROC) curve analysis, Hosmer-Lemeshow test, and decision curve analysis (DCA).

RESULTS

The emergent conversion to GA occurred in 56 cases (12.2%). In the training cohort, four independent predictors of emergent conversion to GA were identified and incorporated into the nomogram: core infarct volume > 70 mL, severe aphasia, severe cerebral vessel tortuosity, and vertebrobasilar occlusion. The ROC curves illustrated area under curve values of 0.931 (95% CI: 0.863-0.998) and 0.893 (95% CI: 0.852-0.935) for the training and validation cohorts, respectively. Hosmer-Lemeshow testing resulted in average absolute errors of 0.028 and 0.031 for the two cohorts. DCA demonstrated the nomogram's exceptional utility and accuracy across a majority of threshold probabilities.

CONCLUSION

The constructed nomogram displayed promising predictive accuracy for emergent conversion to GA in stroke patients during thrombectomy, thereby providing potential assistance for clinical decision-making.

Hybrid CNN-Transformer Network With Circular Feature Interaction for Acute Ischemic Stroke Lesion Segmentation on Non-Contrast CT Scans

Lesion segmentation is a fundamental step for the diagnosis of acute ischemic stroke (AIS). Non-contrast CT (NCCT) is still a mainstream imaging modality for AIS lesion measurement. However, AIS lesion segmentation on NCCT is challenging due to low contrast, noise and artifacts. To achieve accurate AIS lesion segmentation on NCCT, this study proposes a hybrid convolutional neural network (CNN) and Transformer network with circular feature interaction and bilateral difference learning. It consists of parallel CNN and Transformer encoders, a circular feature interaction module, and a shared CNN decoder with a bilateral difference learning module. A new Transformer block is particularly designed to solve the weak inductive bias problem of the traditional Transformer. To effectively combine features from CNN and Transformer encoders, we first design a multi-level feature aggregation module to combine multi-scale features in each encoder and then propose a novel feature interaction module containing circular CNN-to-Transformer and Transformer-to-CNN interaction blocks. Besides, a bilateral difference learning module is proposed at the bottom level of the decoder to learn the different information between the ischemic and contralateral sides of the brain. The proposed method is evaluated on three AIS datasets: the public AISD, a private dataset and an external dataset. Experimental results show that the proposed method achieves Dices of 61.39% and 46.74% on the AISD and the private dataset, respectively, outperforming 17 state-of-the-art segmentation methods. Besides, volumetric analysis on segmented lesions and external validation results imply that the proposed method is potential to provide support information for AIS diagnosis.

Preliminary findings on diagnostic performance of computed tomography perfusion images for intracranial arterial stenosis: a retrospective study

OBJECTIVES

Computed tomographic perfusion (CTP) can play an auxiliary role in the selection of patients with acute ischemic stroke for endovascular treatment. However, data on CTP in non-stroke patients with intracranial arterial stenosis are scarce. We aimed to investigate images in patients with asymptomatic intracranial arterial stenosis to determine the detection accuracy and interpretation time of large/medium-artery stenosis or occlusion when combining computed tomographic angiography (CTA) and CTP images.

METHODS

We retrospectively reviewed 39 patients with asymptomatic intracranial arterial stenosis from our hospital database from January 2021 to August 2023 who underwent head CTP, head CTA, and digital subtraction angiography (DSA). Head CTA images were generated from the CTP data, and the diagnostic performance for each artery was assessed. Two readers independently interpreted the CTA images before and after CTP, and the results were analyzed.

RESULTS

After adding CTP maps, the accuracy (area under the curve) of diagnosing internal carotid artery (R1: 0.847 vs. 0.907, R2: 0.776 vs. 0.887), middle cerebral artery (R1: 0.934 vs. 0.933, R2: 0.927 vs. 0.981), anterior cerebral artery (R1: 0.625 vs. 0.750, R2: 0.609 vs. 0.750), vertebral artery (R1: 0.743 vs. 0.764, R2: 0.748 vs. 0.846), and posterior cerebral artery (R1: 0.390 vs. 0.575, R2: 0.390 vs. 0.585) occlusions increased for both readers (p < 0.05). Mean interpretation time (R1: 72.4 ± 6.1 s vs. 67.7 ± 6.4 s, R2: 77.7 ± 3.8 s vs. 72.6 ± 4.7 s) decreased when using a combination of both images both readers (p < 0.001).

CONCLUSIONS

The addition of CTP images improved the accuracy of interpreting CTA images and reduced the interpretation time in asymptomatic intracranial arterial stenosis. These findings support the use of CTP imaging in patients with asymptomatic intracranial arterial stenosis.

Subtyping treatment response of tirofiban in acute ischemic stroke based on neuroimaging features

In a previously published clinical trial, we demonstrated that tirofiban was effective and safe in acute ischemic stroke (AIS) patients who did not undergo early recanalization treatments. We aimed to evaluate neuroimaging characteristics and their clinical significance to guide tirofiban treatment. In this post hoc analysis, location of infarcts (anterior circulation stroke [ACS] vs. posterior circulation stroke [PCS]), degree of cerebral artery stenosis (≤69% vs. ≥70% or occlusion), total infarct volume, and ASPECTS were used to predict the treatment effects of tirofiban, defined as the proportions of excellent and favorable functional outcome (modified Rankin Scale [mRS] score of 0-1, 0-2) at 90 days. ACS patients were more likely to achieve excellent (OR 2.08; 95% CI 1.25-3.45; p = 0.004) and favorable functional outcome (OR 2.28; 95% CI 1.24-4.22; p = 0.008) when treated with tirofiban. However, there was no significant difference in PCS patients between tirofiban and the control group. For patients with severe stenosis (≥70% or occlusion), tirofiban treatment improved the proportion of good outcomes (OR 2.84; 95% CI 1.44-5.60; p = 0.002 for mRS 0-1; OR 2.42; 95% CI 1.22-4.77; p = 0.011 for mRS 0-2). Meanwhile, we found that tirofiban improved outcome in patients with ASPECTS 8-10 and was independent of total infarct volume. These findings support the hypothesis that patients with ACS and severe stenosis may be recommended for tirofiban treatment, which can be predicted independent of total infarct volume.

Prediction of adenocarcinoma and squamous carcinoma based on CT perfusion parameters of brain metastases from lung cancer: a pilot study

Objectives

Predicting pathological types in patients with adenocarcinoma and squamous carcinoma using CT perfusion imaging parameters based on brain metastasis lesions from lung cancer.

Methods

We retrospectively studied adenocarcinoma and squamous carcinoma patients with brain metastases who received treatment and had been pathologically tested in our hospital from 2019 to 2021. CT perfusion images of the brain were used to segment enhancing tumors and peritumoral edema and to extract CT perfusion parameters. The most relevant perfusion parameters were identified to classify the pathological types. Of the 45 patients in the study cohort (mean age 65.64 ± 10.08 years; M:F = 24:21), 16 were found to have squamous cell carcinoma. Twenty patients were with brain metastases only, and 25 patients were found to have multiple organ metastases in addition to brain metastases. After admission, all patients were subjected to the CT perfusion imaging examination. Differences in CT perfusion parameters between adenocarcinoma and squamous carcinoma were analyzed. The receiver operating characteristic (ROC) curves were used to predict the types of pathology of the patients.

Results

Among the perfusion parameters, cerebral blood flow (CBF) and mean transit time (MTT) were significantly different between the two lung cancers (adenocarcinoma vs. squamous cell carcinoma: p < 0.001, p = 0.012.). Gender and tumor location were identified as the clinical predictive factors. For the classification of adenocarcinoma and squamous carcinoma, the model combined with CBF and clinical predictive factors showed better performance [area under the curve (AUC): 0.918, 95% confidence interval (CI): 0.797-0.979). The multiple organ metastasis model showed better performance than the brain metastasis alone model in subgroup analyses (AUC: 0.958, 95% CI: 0.794-0.999).

Conclusion

CT perfusion parameter analysis of brain metastases in patients with primary lung cancer could be used to classify adenocarcinoma and squamous carcinoma.

Prediction of stress-related gastrointestinal bleeding in patients with aneurysmal subarachnoid hemorrhage using caudate Hounsfield unit value in ASPECT score

Background

Stress-related gastrointestinal bleeding (SRGB) is one of the major complications after aneurysmal subarachnoid hemorrhage (aSAH), and it can present challenges in patient care and treatment. The aim of this study was to explore the clinical significance of the caudate Hounsfield unit (HU) value in the Alberta Stroke Program Early CT (ASPECT) score for predicting SRGB in patients with aSAH.

Methods

We retrospectively analyzed the data of 531 aSAH patients admitted to our institution between 2019 and 2022. Potential predictors of SRGB were identified using multivariate Cox regression analysis. We used a restricted cubic spline (RCS) to evaluate whether there is a nonlinear relationship between the right caudate HU value and SRGB. MaxStat analysis (titled as maximally selected rank statistics) was performed to identify the optimal cutoff point for the right caudate HU value. Another Kaplan-Meier method with the log-rank test was used to analyze the right caudate HU value in predicting the occurrence of SRGB.

Results

The incidence rate of SRGB was 17.9%. In the multivariate Cox regression analysis, the right caudate HU value was an independent predictor of SRGB [Hazard ratio (HR) = 0.913; 95% confidence interval (CI): 0.847-0.983, and p = 0.016]. The RCS indicated that the incidence of developing SRGB reduces with increasing right caudate HU values (nonlinear p = 0.78). The optimal cut-off value of the right caudate HU was 25.1.

Conclusion

Among aSAH patients, lower right caudate HU values indicated a higher risk of developing SRGB. Our findings provide further evidence for the relationship between the gastrointestinal system and the brain.

CT Perfusion vs Noncontrast CT for Late Window Stroke Thrombectomy: A Systematic Review and Meta-analysis

BACKGROUND AND OBJECTIVES

Patients with acute ischemic stroke (AIS) treated with endovascular thrombectomy (EVT) in the late window (6-24 hours) can be evaluated with CT perfusion (CTP) or with noncontrast CT (NCCT) only. Whether outcomes differ depending on the type of imaging selection is unknown. We conducted a systematic review and meta-analysis comparing outcomes between CTP and NCCT for EVT selection in the late therapeutic window.

METHODS

This study is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses 2020 guidelines. A systematic literature review of the English language literature was conducted using Web of Science, Embase, Scopus, and PubMed databases. Studies focusing on late-window AIS undergoing EVT imaged through CTP and NCCT were included. Data were pooled using a random-effects model. The primary outcome of interest was rate of functional independence, defined as modified Rankin scale 0-2. The secondary outcomes of interest included rates of successful reperfusion, defined as thrombolysis in cerebral infarction 2b-3, mortality, and symptomatic intracranial hemorrhage (sICH).

RESULTS

Five studies with 3,384 patients were included in our analysis. There were comparable rates of functional independence (odds ratio [OR] 1.03, 95% CI 0.87-1.22; p = 0.71) and sICH (OR 1.09, 95% CI 0.58-2.04; p = 0.80) between the 2 groups. Patients imaged with CTP had higher rates of successful reperfusion (OR 1.31, 95% CI 1.05-1.64; p = 0.015) and lower rates of mortality (OR 0.79, 95% CI 0.65-0.96; p = 0.017).

DISCUSSION

Although recovery of functional independence after late-window EVT was not more common in patients selected by CTP when compared with patients selected by NCCT only, patients selected by CTP had lower mortality.

Neuroimaging in Patient Selection for Thrombectomy, From the AJR Special Series on Emergency Radiology

Endovascular thrombectomy has become the standard-of-care treatment for carefully selected patients with acute ischemic stroke due to a large-vessel occlusion of the anterior circulation. Neuroimaging plays a vital role in determining patient eligibility for thrombectomy, both in the early (0-6 hours from symptom onset) and late (> 6 to 24 hours from symptom onset) time windows. Various neuroimaging algorithms are used to determine thrombectomy eligibility, and each algorithm must be optimized for institutional workflow. In this review, we describe common imaging modalities and recommended algorithms for the evaluation of patients for endovascular thrombectomy. We also discuss emerging patient populations who might qualify for thrombectomy in the coming years.

Collateral Blood Flow and Ischemic Core Growth

Treatment of a large vessel occlusion in the acute ischemic stroke setting focuses on vessel recanalization, and endovascular thrombectomy results in favorable outcomes in appropriate candidates. Expeditious treatment is imperative, but patients often present to institutions that do not have neurointerventional surgeons and need to be transferred to a comprehensive stroke center. These treatment delays are common, and it is important to identify factors that mitigate the progression of the ischemic core in order to maximize the preservation of salvageable brain tissue. Collateral blood flow is the strongest factor known to influence ischemic core growth, which includes the input arterial vessels, tissue-level vessels, and venous outflow. Collateral blood flow at these different levels may be imaged by specific imaging techniques that may also predict ischemic core growth during treatment delays and help identify patients who would benefit from transfer and endovascular therapy, as well as identify those patients in whom transfer may be futile. Here we review collateral blood flow and its relationship to ischemic core growth in stroke patients.

Thrombectomy in acute ischemic stroke in the extended time window: Real-life experience in a high-volume center

OBJECTIVES

Selected patients with acute ischemic stroke (AIS) caused by proximal middle cerebral artery (MCA) or internal carotid artery occlusion benefit from endovascular thrombectomy (EVT) in extended time window (6-24 h from last seen well) based on two landmark randomized controlled trials (RCTs) DAWN and DEFUSE-3. We evaluated patients' outcome in the real-life with the focus on adherence to protocol of the two RCTs.

MATERIALS AND METHODS

We included consecutive patients with AIS (excluding basilar artery occlusions) referred to EVT in our stroke center in the extended time window between January 2018 and December 2019 and compared the outcome of patients who fulfilled criteria of the RCTs with those who did not.

RESULTS

Of the total of 100 patients, 23 complied with RCT's criteria and 18 presented with minor non-adherence (lower NIHSS score or longer treatment delay), whereas 22 patients had large baseline ischemia (>1/3 MCA), 28 presented with M2 and more distal occlusions, and 9 patients did not undergo perfusion imaging prior to EVT. Good 3-month outcome (modified Rankin Scale 0-2) was observed in 54% of those who either met the RCT criteria or presented with lower NIHSS score or longer treatment delay, but only in 30% of M2 occlusions, and in none of the patients with large baseline ischemia.

CONCLUSIONS

Our findings highlight the impact of mostly large baseline ischemia but also vessel status when selecting patients for EVT in the extended time window and emphasize the need for further data in these patient subgroups.

Mechanical thrombectomy versus medical care alone in large ischemic core: An up-to-date meta-analysis

OBJECTIVE

We compared outcomes and adverse events of thrombectomy versus medical management in acute ischemic stroke (AIS) patients with baseline large infarct core.

METHODS

We searched Ovid MEDLINE(R) ALL, Cochrane Library Clinical Controlled Trials and EMBASE from inception to January 2021 for studies comparing thrombectomy and medical management alone in AIS patients who had ASPECTS <=7 or ischemic core volume >=50 ml. Imaging modalities to valuate ASPECTS and core volume were without restriction. The functional outcome was measured by mRS (modified Rankin Scale) score 0-2 at 90 days or discharge. The safety end point included the rates of mortality and sICH (symptomatic intracranial hemorrhage) or PH2 (parenchymal hematoma type 2).

RESULTS

Fourteen studies with a total of 2547 patients (thrombectomy n = [1197]; medical care alone [n = 1350]) fulfilled our criteria. As for patients with low ASPECTS, pooled results indicated a higher odds of good functional outcome (OR = 3.47; 95% CI 1.99 to 6.07; P < 0.0001, I²=66%) and a lower risk of mortality (OR = 0.62; 95% CI 0.46 to 0.83; P = 0.001, I²=32%) in thrombectomy group compared with no thrombectomy group, but the risk of sICH or PH2 did not differ between two groups. As for patients with large core volume, both functional outcome and safety end point between two groups showed no statistically significant difference.

CONCLUSION

Thrombectomy remained safe and effective by careful selection in patients with low ASPECTS. More studies were warranted to explore contraindications for mechanical thrombectomy in AIS patients, especially in patients with large core volume.

Impact of Encephalomalacia and White Matter Hyperintensities on ASPECTS in Patients With Acute Ischemic Stroke: Comparison of Automated- and Radiologist-Derived Scores

Background: Automated software-based Alberta Stroke Program Early CT Score (ASPECTS) on unenhanced CT is associated with clinical outcomes after acute stroke. However, encephalomalacia or white matter hyperintensities (WMHs) may result in a falsely low automated ASPECTS if such findings are interpreted as early ischemia. Objective: To assess the impact of encephalomalacia and WMH on automated ASPECTS in patients with acute stroke, in comparison with radiologist-derived ASPECTS and clinical outcomes. Methods: This retrospective three-center study included 459 patients (322 men, 137 women; median age, 65 years) with acute ischemic stroke treated by IV thrombolysis who underwent baseline unenhanced CT within 6 hours after symptom onset and MRI within 24 hours after treatment. ASPECTS was determined by automated software and by three radiologists in consensus. Presence of encephalomalacia and extent of WMHs [categorized using the modified Scheltens scale (mSS)] were also determined using MRI. Kappa coefficients were used to compare ASPECTS between automated and radiologist-consensus methods. Multivariable logistic regression analyses and ROC analyses were performed to explore the predictive utility of baseline ASPECTS for unfavorable clinical outcome (90-day modified Rankin Scale score of 3-6) after thrombolysis. Results: Median automated ASPECTS was 9, and median radiologist-consensus ASPECTS was 10. Agreement between automated and radiologist-consensus ASPECTS, expressed as kappa, was 0.68, though was 0.76 in patients without encephalomalacia and 0.08 in patients with encephalomalacia. In patients without encephalomalacia, agreement decreased as the mSS score increased (e.g., 0.78 in subgroup with mSS score <10 vs 0.19 in subgroup with mSS >20). By anatomic region, agreement was highest for M5 (κ=0.52) and lowest for internal capsule (κ=0.18). In multivariable analyses, both automated (odds ratio=0.69) and radiologist-consensus (odds ratio=0.57) ASPECTS independently predicted unfavorable clinical outcome. For unfavorable outcome, automated ASPECTS had AUC of 0.70, sensitivity of 60.4%, and specificity of 71.0%, while radiologist-consensus ASPECTS had AUC of 0.72, sensitivity of 60.4%, and specificity of 80.5%. Conclusion: Presence of encephalomalacia or extensive WMH results in lower automated ASPECTS than radiologist-consensus ASPECTS, which may impact predictive utility of automated ASPECTS. Clinical Impact: When using automated ASPECTS, radiologists should manually confirm the score in patients with encephalomalacia or extensive leukoencephalopathy.

Adapting Clinical Practice of Thrombolysis for Acute Ischemic Stroke Beyond 4.5 Hours: A Review of the Literature

Several clinical trials have demonstrated that advanced neuroimaging can select patients for recanalization therapy in an extended time window. The favorable functional outcomes and safety profile of these studies have led to the incorporation of neuroimaging in endovascular treatment guidelines, and most recently, also extended to decision making on thrombolysis. Two randomized clinical trials have demonstrated that patients who are not amenable to endovascular thrombectomy within 4.5 hours from symptoms discovery or beyond 4.5 hours from the last-known-well time may also be safely treated with intravenous thrombolysis and have a clinical benefit above the risk of safety concerns. With the growing aging population, increased stroke incidence in the young, and the impact of evolving medical practice, healthcare and stroke systems of care need to adapt continuously to provide evidence-based care efficiently. Therefore, understanding and incorporating appropriate screening strategies is critical for the prompt recognition of potentially eligible patients for extended-window intravenous thrombolysis. Here we review the clinical trial evidence for thrombolysis for acute ischemic stroke in the extended time window and provide a review of new enrolling clinical trials that include thrombolysis intervention beyond the 4.5 hour window.

Decomposing Acute Symptom Severity in Large Vessel Occlusion Stroke: Association With Multiparametric CT Imaging and Clinical Parameters

Background and Purpose: Acute ischemic stroke of the anterior circulation due to large vessel occlusion (LVO) is a multifactorial process, which causes neurologic symptoms of different degree. Our aim was to examine the impact of neuromorphologic and vascular correlates as well as clinical factors on acute symptom severity in LVO stroke. Methods: We selected LVO stroke patients with known onset time from a consecutive cohort which underwent multiparametric CT including non-contrast CT, CT angiography and CT perfusion (CTP) before thrombectomy. Software-based quantification was used to calculate CTP total ischemic and ischemic core volume. Symptom severity was assessed using the National Institutes of Health Stroke Scale (NIHSS) upon admission. Multivariable regression analysis was performed to determine independent associations of admission NIHSS with imaging and clinical parameters. Receiver operating characteristics (ROC) analyses were used to examine performance of imaging parameters to classify symptom severity. Results: We included 142 patients. Linear and ordinal regression analyses for NIHSS and NIHSS severity groups identified significant associations for total ischemic volume [β = 0.31, p = 0.01; Odds ratio (OR) = 1.11, 95%-confidence-interval (CI): 1.02-1.19], clot burden score (β = -0.28, p = 0.01; OR = 0.76, 95%-CI: 0.64-0.90) and age (β = 0.17, p = 0.04). No association was found for ischemic core volume, stroke side, collaterals and time from onset. Stroke topography according to the Alberta Stroke Program CT Score template did not display significant influence after correction for multiple comparisons. AUC for classification of the NIHSS threshold ≥6 by total ischemic volume was 0.81 (p < 0.001). Conclusions: We determined total ischemic volume, clot burden and age as relevant drivers for baseline NIHSS in acute LVO stroke. This suggests that not only mere volume but also degree of occlusion influences symptom severity. Use of imaging parameters as surrogate for baseline NIHSS reached limited performance underlining the need for combined clinical and imaging assessment in acute stroke management.

Proceedings from the Neurotherapeutics Symposium on Neurological Emergencies: Shaping the Future of Neurocritical Care

Effective treatment options for patients with life-threatening neurological disorders are limited. To address this unmet need, high-impact translational research is essential for the advancement and development of novel therapeutic approaches in neurocritical care. "The Neurotherapeutics Symposium 2019-Neurological Emergencies" conference, held in Rochester, New York, in June 2019, was designed to accelerate translation of neurocritical care research via transdisciplinary team science and diversity enhancement. Diversity excellence in the neuroscience workforce brings innovative and creative perspectives, and team science broadens the scientific approach by incorporating views from multiple stakeholders. Both are essential components needed to address complex scientific questions. Under represented minorities and women were involved in the organization of the conference and accounted for 30-40% of speakers, moderators, and attendees. Participants represented a diverse group of stakeholders committed to translational research. Topics discussed at the conference included acute ischemic and hemorrhagic strokes, neurogenic respiratory dysregulation, seizures and status epilepticus, brain telemetry, neuroprognostication, disorders of consciousness, and multimodal monitoring. In these proceedings, we summarize the topics covered at the conference and suggest the groundwork for future high-yield research in neurologic emergencies.