Combining acute diffusion-weighted imaging and mean transmit time lesion volumes with National Institutes of Health Stroke Scale Score improves the prediction of acute stroke outcome

Correlation between DWI-ASPECTS Score, Ischemic Stroke Volume on DWI, Clinical Severity and Short-Term Prognosis: A Single-Center Study

Ischemic stroke is a significant public health concern, with its incidence expected to double over the next 40 years, particularly among individuals over 75 years old. Previous studies, such as the DAWN trial, have highlighted the importance of correlating clinical severity with ischemic stroke volume to optimize patient management. Our study aimed to correlate the clinical severity of ischemic stroke, as assessed by the NIHSS score, with ischemic stroke volume measured using DWI, and short-term prognosis quantified by the mRS score at discharge. Conducted at the largest hospital in Gorj County from January 2023 to December 2023, this study enrolled 43 consecutive patients with acute ischemic stroke. In our patient cohort, we observed a strong positive correlation between NIHSS score and ischemic stroke volume (Spearman correlation coefficient = 0.982, p < 0.01), and a strong negative correlation between ASPECTS-DWI score and mRS score (Spearman correlation coefficient = -0.952, p < 0.01). Multiple linear regression analysis revealed a significant collective relationship between ASPECTS score, ischemic stroke volume, and NIHSS score (F(1, 41) = 600.28, p < 0.001, R2 = 0.94, R2adj = 0.93). These findings underscore the importance of DWI in assessing ischemic stroke severity and prognosis, warranting further investigation for its integration into clinical practice.

Predictors of 30-day mortality following the first episode of stroke among patients admitted at referral hospitals in Dodoma, central Tanzania: A prospective longitudinal observational study

Background and Aims

Stroke is the leading cause of disability and the second most common cause of death after ischemic heart disease worldwide. Understanding predictors of early poststroke mortality provides opportunities for interventions and favorable outcomes. This study aimed to determine the incidence and predictors of 30-day mortality among patients admitted with the first stroke at referral hospitals in Dodoma.

Methods

A prospective longitudinal observational design enrolled patients with acute stroke confirmed by CT scan or MRI admitted at referral hospitals in Dodoma. The National Institute of Health Stroke Scale was used to assess stroke severity at baseline. A comparison of risk factors, clinical profiles, and mortality was done using the Chi-square test. A logistic regression model was used to determine the predictors of 30-day mortality in patients with the stroke while the 30-day probability of survival was estimated using Kaplan-Meier analysis.

Results

Out of 226 patients with first-ever stroke, 121(54%) were males, and the population mean age was 63(15) years. The 140(62%) had Ischemic stroke, and 154(68%) survived at the 30th day. Patients with a history of smoking 2.4 [95% confidence interval (CI) (1.0-5.6), p = 0.048], loss of consciousness 2.7 [95% CI (1.2-6.4; p = 0.019] and unequal pupil size 13.7 [95% CI (4.1-58.1, p < 0.001 were significantly more associated with mortality within 30 days. The median survival was 7 (3-9) days, whereas alcohol drinkers and those aged above 60 years had a shorter time to mortality compared to non-alcohol drinkers and those aged <60 years.

Conclusion

The study showed a high incidence of mortality within 30 days after the first stroke episode, with the highest proportion dying within 7 days of being hospitalized. Advanced age of ≥60 years, smoking, alcohol use, and severe stroke at admission warrant special attention.

Taxonomy of Acute Stroke: Imaging, Processing, and Treatment

Stroke management employs a variety of diagnostic imaging modalities, image processing and analysis methods, and treatment procedures. This work categorizes methods for stroke imaging, image processing and analysis, and treatment, and provides their taxonomies illustrated by a state-of-the-art review. Imaging plays a critical role in stroke management, and the most frequently employed modalities are computed tomography (CT) and magnetic resonance (MR). CT includes unenhanced non-contrast CT as the first-line diagnosis, CT angiography, and CT perfusion. MR is the most complete method to examine stroke patients. MR angiography is useful to evaluate the severity of artery stenosis, vascular occlusion, and collateral flow. Diffusion-weighted imaging is the gold standard for evaluating ischemia. MR perfusion-weighted imaging assesses the penumbra. The stroke image processing methods are divided into non-atlas/template-based and atlas/template-based. The non-atlas/template-based methods are subdivided into intensity and contrast transformations, local segmentation-related, anatomy-guided, global density-guided, and artificial intelligence/deep learning-based. The atlas/template-based methods are subdivided into intensity templates and atlases with three atlas types: anatomy atlases, vascular atlases, and lesion-derived atlases. The treatment procedures for arterial and venous strokes include intravenous and intraarterial thrombolysis and mechanical thrombectomy. This work captures the state-of-the-art in stroke management summarized in the form of comprehensive and straightforward taxonomy diagrams. All three introduced taxonomies in diagnostic imaging, image processing and analysis, and treatment are widely illustrated and compared against other state-of-the-art classifications.

Ischemic stroke outcome prediction with diversity features from whole brain tissue using deep learning network

Objectives

This study proposed an outcome prediction method to improve the accuracy and efficacy of ischemic stroke outcome prediction based on the diversity of whole brain features, without using basic information about patients and image features in lesions.

Design

In this study, we directly extracted dynamic radiomics features (DRFs) from dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) and further extracted static radiomics features (SRFs) and static encoding features (SEFs) from the minimum intensity projection (MinIP) map, which was generated from the time dimension of DSC-PWI images. After selecting whole brain features Ffuse from the combinations of DRFs, SRFs, and SEFs by the Lasso algorithm, various machine and deep learning models were used to evaluate the role of Ffuse in predicting stroke outcomes.

Results

The experimental results show that the feature Ffuse generated from DRFs, SRFs, and SEFs (Resnet 18) outperformed other single and combination features and achieved the best mean score of 0.971 both on machine learning models and deep learning models and the 95% CI were (0.703, 0.877) and (0.92, 0.983), respectively. Besides, the deep learning models generally performed better than the machine learning models.

Conclusion

The method used in our study can achieve an accurate assessment of stroke outcomes without segmentation of ischemic lesions, which is of great significance for rapid, efficient, and accurate clinical stroke treatment.

Amide proton transfer imaging in stroke

Amide proton transfer (APT) imaging, a variant of chemical exchange saturation transfer MRI, has shown promise in detecting ischemic tissue acidosis following impaired aerobic metabolism in animal models and in human stroke patients due to the sensitivity of the amide proton exchange rate to changes in pH within the physiological range. Recent studies have demonstrated the possibility of using APT-MRI to detect acidosis of the ischemic penumbra, enabling the assessment of stroke severity and risk of progression, monitoring of treatment progress, and prognostication of clinical outcome. This paper reviews current APT imaging methods actively used in ischemic stroke research and explores the clinical aspects of ischemic stroke and future applications for these methods.

Interpretable deep learning for the prognosis of long-term functional outcome post-stroke using acute diffusion weighted imaging

Advances in deep learning can be applied to acute stroke imaging to build powerful and explainable prediction models that could supersede traditionally used biomarkers. We aimed to evaluate the performance and interpretability of a deep learning model based on convolutional neural networks (CNN) in predicting long-term functional outcome with diffusion-weighted imaging (DWI) acquired at day 1 post-stroke. Ischemic stroke patients (n = 322) were included from the ASTER and INSULINFARCT trials as well as the Pitié-Salpêtrière registry. We trained a CNN to predict long-term functional outcome assessed at 3 months with the modified Rankin Scale (dichotomized as good [mRS ≤ 2] vs. poor [mRS ≥ 3]) and compared its performance to two logistic regression models using lesion volume and ASPECTS. The CNN contained an attention mechanism, which allowed to visualize the areas of the brain that drove prediction. The deep learning model yielded a significantly higher area under the curve (0.83 95%CI [0.78-0.87]) than lesion volume (0.78 [0.73-0.83]) and ASPECTS (0.77 [0.71-0.83]) (p < 0.05). Setting all classifiers to the specificity as the deep learning model (i.e., 0.87 [0.82-0.92]), the CNN yielded a significantly higher sensitivity (0.67 [0.59-0.73]) than lesion volume (0.48 [0.40-0.56]) and ASPECTS (0.50 [0.41-0.58]) (p = 0.002). The attention mechanism revealed that the network learned to naturally attend to the lesion to predict outcome.

Research and application advances in rehabilitation assessment of stroke

Stroke has a high incidence and disability rate, and rehabilitation is an effective means to reduce the disability rate of patients. To systematize rehabilitation assessment, which is the foundation for rehabilitation therapy, we summarize the assessment methods commonly used in research and clinical applications, including the various types of stroke rehabilitation scales and their applicability, and related biomedical detection technologies, including surface electromyography (sEMG), motion analysis systems, transcranial magnetic stimulation (TMS), magnetic resonance imaging (MRI), and combinations of different techniques. We also introduce some assessment techniques that are still in the experimental phase, such as the prospective application of artificial intelligence (AI) with optical correlation tomography (OCT) in stroke rehabilitation. This review provides a useful bibliography for the assessment of not only the severity of stroke injury, but also the therapeutic effects of stroke rehabilitation, and establishes a solid base for the future development of stroke rehabilitation skills.

MRI whole-lesion texture analysis on ADC maps for the prognostic assessment of ischemic stroke

Background

This study aims is to explore whether it is feasible to use magnetic resonance texture analysis (MRTA) in order to distinguish favorable from unfavorable function outcomes and determine the prognostic factors associated with favorable outcomes of stroke.

Methods

The retrospective study included 103 consecutive patients who confirmed unilateral anterior circulation subacute ischemic stroke by computed tomography angiography between January 2018 and September 2019. Patients were divided into favorable outcome (modified Rankin scale, mRS ≤ 2) and unfavorable outcome (mRS > 2) groups according to mRS scores at day 90. Two radiologists manually segmented the infarction lesions based on diffusion-weighted imaging and transferred the images to corresponding apparent diffusion coefficient (ADC) maps in order to extract texture features. The prediction models including clinical characteristics and texture features were built using multiple logistic regression. A univariate analysis was conducted to assess the performance of the mean ADC value of the infarction lesion. A Delong’s test was used to compare the predictive performance of models through the receiver operating characteristic curve.

Results

The mean ADC performance was moderate [AUC = 0.60, 95% confidence interval (CI) 0.49–0.71]. The texture feature model of the ADC map (tADC), contained seven texture features, and presented good prediction performance (AUC = 0.83, 95%CI 0.75–0.91). The energy obtained after wavelet transform, and the kurtosis and skewness obtained after Laplacian of Gaussian transformation were identified as independent prognostic factors for the favorable stroke outcomes. In addition, the combination of the tADC model and clinical characteristics (hypertension, diabetes mellitus, smoking, and atrial fibrillation) exhibited a subtly better performance (AUC = 0.86, 95%CI 0.79–0.93; P > 0.05, Delong’s).

Conclusion

The models based on MRTA on ADC maps are useful to evaluate the clinical function outcomes in patients with unilateral anterior circulation ischemic stroke. Energy obtained after wavelet transform, kurtosis obtained after Laplacian of Gaussian transform, and skewness obtained after Laplacian of Gaussian transform were identified as independent prognostic factors for favorable stroke outcomes.

Portable, low-field magnetic resonance imaging enables highly accessible and dynamic bedside evaluation of ischemic stroke

Brain imaging is essential to the clinical management of patients with ischemic stroke. Timely and accessible neuroimaging, however, can be limited in clinical stroke pathways. Here, portable magnetic resonance imaging (pMRI) acquired at very low magnetic field strength (0.064 T) is used to obtain actionable bedside neuroimaging for 50 confirmed patients with ischemic stroke. Low-field pMRI detected infarcts in 45 (90%) patients across cortical, subcortical, and cerebellar structures. Lesions as small as 4 mm were captured. Infarcts appeared as hyperintense regions on T2-weighted, fluid-attenuated inversion recovery and diffusion-weighted imaging sequences. Stroke volume measurements were consistent across pMRI sequences and between low-field pMRI and conventional high-field MRI studies. Low-field pMRI stroke volumes significantly correlated with stroke severity and functional outcome at discharge. These results validate the use of low-field pMRI to obtain clinically useful imaging of stroke, setting the stage for use in resource-limited environments.

Association of Socioeconomic Status and Infarct Volume With Functional Outcome in Patients With Ischemic Stroke

IMPORTANCE

Long-term disability after stroke is associated with socioeconomic status (SES). However, the reasons for such disparities in outcomes remain unclear.

OBJECTIVE

To assess whether lower SES is associated with larger admission infarct volume and whether initial infarct volume accounts for the association between SES and long-term disability.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study was conducted in a prospective, consecutive population (n = 1256) presenting with acute ischemic stroke who underwent magnetic resonance imaging (MRI) within 24 hours of admission. Patients were recruited in Massachusetts General Hospital, Boston, from May 31, 2009, to December 31, 2011. Data were analyzed from May 1, 2019, until June 30, 2020.

MAIN OUTCOMES AND MEASURES

Initial stroke severity (within 24 hours of presentation) was determined using clinical (National Institutes of Health Stroke Scale [NIHSS]) and imaging (infarct volume by diffusion-weighted MRI) measures. Stroke etiologic subtypes were determined using the Causative Classification of Ischemic Stroke algorithm. Long-term stroke disability was measured using the modified Rankin Scale. Socioeconomic status was estimated using zip code-derived median household income and census block group-derived area deprivation index (ADI). Regression and mediation analyses were performed.

RESULTS

A total of 1098 patients had imaging and SES data available (mean [SD] age, 68.1 [15.7] years; 607 men [55.3%]). Income was inversely associated with initial infarct volume (standardized β, -0.074 [95% CI, -0.127 to -0.020]; P = .007), initial NIHSS (standardized β, -0.113 [95% CI, -0.171 to -0.054]; P < .001), and long-term disability (standardized β, -0.092 [95% CI, -0.149 to -0.035]; P = .001), which remained significant after multivariable adjustments. Initial stroke severity accounted for 64% of the association between SES and long-term disability (standardized β, -0.063 [95% CI, -0.095 to -0.029]; P < .05). Findings were similar when SES was alternatively assessed using ADI.

CONCLUSIONS AND RELEVANCE

The findings of this cohort study suggest that lower SES is associated with larger infarct volumes on presentation. These SES-associated differences in initial stroke severity accounted for most of the subsequent disparities in long-term disability in this study. These findings shift the culpability for SES-associated disparities in poststroke disability from poststroke factors to those that precede presentation.

Primer reporte de inmaduros de Cryptocephalus Geoffroy, 1762 (Coleoptera: Chrysomelidae) de Brasil con notas de su bioecología sobre Wedelia goyazensis Gardner (Asteraceae) y síntesis de los registros de presencia del género en territorio brasileño

Cryptocephalus Geoffroy, 1762 es reconocido por su distribución cosmopolita y gran riqueza, con al menos 1700 especies descritas. Sin embargo, falta información para Brasil: (1) no hay registro de inmaduros; y (2) no se conoce casi nada sobre la biología de este género. En este trabajo se documentan por primera vez las etapas inmaduras de Cryptocephalus de Brasil y se presentan algunas notas sobre su bioecología en la planta huésped. Además, se recopilan sus registros en territorio brasileño a partir de la bibliografía.

A Review on Computer Aided Diagnosis of Acute Brain Stroke

Amongst the most common causes of death globally, stroke is one of top three affecting over 100 million people worldwide annually. There are two classes of stroke, namely ischemic stroke (due to impairment of blood supply, accounting for ~70% of all strokes) and hemorrhagic stroke (due to bleeding), both of which can result, if untreated, in permanently damaged brain tissue. The discovery that the affected brain tissue (i.e., 'ischemic penumbra') can be salvaged from permanent damage and the bourgeoning growth in computer aided diagnosis has led to major advances in stroke management. Abiding to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines, we have surveyed a total of 177 research papers published between 2010 and 2021 to highlight the current status and challenges faced by computer aided diagnosis (CAD), machine learning (ML) and deep learning (DL) based techniques for CT and MRI as prime modalities for stroke detection and lesion region segmentation. This work concludes by showcasing the current requirement of this domain, the preferred modality, and prospective research areas.

An integrative multivariate approach for predicting functional recovery using magnetic resonance imaging parameters in a translational pig ischemic stroke model

Magnetic resonance imaging (MRI) is a clinically relevant, real-time imaging modality that is frequently utilized to assess stroke type and severity. However, specific MRI biomarkers that can be used to predict long-term functional recovery are still a critical need. Consequently, the present study sought to examine the prognostic value of commonly utilized MRI parameters to predict functional outcomes in a porcine model of ischemic stroke. Stroke was induced via permanent middle cerebral artery occlusion. At 24 hours post-stroke, MRI analysis revealed focal ischemic lesions, decreased diffusivity, hemispheric swelling, and white matter degradation. Functional deficits including behavioral abnormalities in open field and novel object exploration as well as spatiotemporal gait impairments were observed at 4 weeks post-stroke. Gaussian graphical models identified specific MRI outputs and functional recovery variables, including white matter integrity and gait performance, that exhibited strong conditional dependencies. Canonical correlation analysis revealed a prognostic relationship between lesion volume and white matter integrity and novel object exploration and gait performance. Consequently, these analyses may also have the potential of predicting patient recovery at chronic time points as pigs and humans share many anatomical similarities (e.g., white matter composition) that have proven to be critical in ischemic stroke pathophysiology. The study was approved by the University of Georgia (UGA) Institutional Animal Care and Use Committee (IACUC; Protocol Number: A2014-07-021-Y3-A11 and 2018-01-029-Y1-A5) on November 22, 2017.

Characterization of tissue and functional deficits in a clinically translational pig model of acute ischemic stroke

The acute stroke phase is a critical time frame used to evaluate stroke severity, therapeutic options, and prognosis while also serving as a major tool for the development of diagnostics. To further understand stroke pathophysiology and to enhance the development of treatments, our group developed a translational pig ischemic stroke model. In this study, the evolution of acute ischemic tissue damage, immune responses, and functional deficits were further characterized. Stroke was induced by middle cerebral artery occlusion in Landrace pigs. At 24 h post-stroke, magnetic resonance imaging revealed a decrease in ipsilateral diffusivity, an increase in hemispheric swelling resulting in notable midline shift, and intracerebral hemorrhage. Stroke negatively impacted white matter integrity with decreased fractional anisotropy values in the internal capsule. Like patients, pigs showed a reduction in circulating lymphocytes and a surge in neutrophils and band cells. Functional responses corresponded with structural changes through reductions in open field exploration and impairments in spatiotemporal gait parameters. Characterization of acute ischemic stroke in pigs provided important insights into tissue and functional-level assessments that could be used to identify potential biomarkers and improve preclinical testing of novel therapeutics.

Diffusion-weighted imaging (DWI) ischemic volume is related to FLAIR hyperintensity-DWI mismatch and functional outcome after endovascular therapy

BACKGROUND

We assessed whether diffusion-weighted imaging (DWI) volume was associated with fluid-attenuated inversion recovery vascular hyperintensities (FVH)-DWI mismatch and functional outcome in patients with acute stroke who received endovascular therapy (EVT).

METHODS

Fifty-three acute stroke patients who received EVT were enrolled. FVH-DWI mismatch, DWI volume on admission, DWI volume on follow-up, DWI volume growth, the functional outcome at 3 months (mRS) and other clinical data were collected. Receiver operating characteristic (ROC) analysis was performed to evaluate the value of DWI volume in predicting functional outcome after stroke.

RESULTS

The FVH-DWI mismatch group had a smaller DWI volume on admission (13.86±19.58 vs. 65.07±52.21; t=-4.301, P=0.000), a smaller DWI volume on follow-up (29.88±33.52 vs. 112.43±87.19; t=-4.143, P=0.000), and a lower DWI volume growth (16.02±19.90 vs. 47.36±40.06; t=-3.326, P=0.003) than those of the no FVH-DWI mismatch group. The good functional outcome group had a smaller DWI volume on admission (13.30±13.26 vs. 68.56±54.28; t=-5.611, P=0.000), a smaller DWI volume on follow-up (27.65±18.80 vs. 120.25±90.37; t=-5.720, P=0.000), lower DWI volume growth (14.35±15.06 vs. 51.69±41.17; t=-4.737, P=0.001) and a higher FVH-DWI mismatch ratio (75.76% vs. 35%; t=8.647; P=0.004) than those of the poor functional outcome group. ROC analysis showed that the sensitivity and specificity of DWI volume on admission for predicting functional outcome were 65% and 96.97%, respectively (the optimal cut-off value: 33.50 mL); DWI volume on follow-up was 48.6 mL, with a sensitivity and specificity of 80% and 87.88%, respectively; DWI volume growth was 22.25 mL, with a sensitivity and specificity of 70% and 87.88%, respectively.

CONCLUSIONS

DWI volume and DWI volume growth can provide the prognostic information of acute stroke patients after thrombectomy.

Diffusion-weighted imaging volume and diffusion-weighted imaging volume growth in acute stroke: associations with fluid-attenuated inversion recovery hyperintensities-diffusion-weighted imaging mismatch and functional outcome

PURPOSE

This study assessed the association between diffusion-weighted imaging (DWI) volume and fluid-attenuated inversion recovery vascular hyperintensity (FVH)-DWI mismatch, functional outcome in patients with acute stroke patients receiving endovascular therapy, as well as the value of DWI volume in predicting functional outcome with stroke patients.

METHODS

In 38 stroke patients who received endovascular therapy, FVH-DWI mismatch, DWI volume on admission, DWI volume on follow-up, DWI volume growth, the functional outcome at 3 months [modified Rankin scale (mRS)], and other clinical data were collected. Statistical analysis was performed to compare the associations with the above variables and predict functional outcome after stroke.

RESULTS

Compared with no FVH-DWI mismatch group (n = 15), FVH-DWI mismatch group (n = 23) had a smaller DWI volume on admission (t = -2.980; P = 0.008), smaller DWI volume on follow-up (t = -2.911; P = 0.009), lower DWI volume growth (t = -2.328; P = 0.031). The 3-month outcome (1.87 ± 0.92) in patients with FVH-DWI mismatch was better than that (2.93 ± 1.62) of patients with no FVH-DWI mismatch (t = -2.307; P = 0.032). Spearman's rank correlation analysis revealed that FVH-DWI mismatch (r = 0.327; P = 0.045), DWI volume on admission (r = 0.414; P = 0.010), DWI volume on follow-up (r = 0.486; P = 0.002), and DWI volume growth (r = 0.467; P = 0.003) were positively correlated with mRS at 3 months. ROC analysis showed when the optimal cutoff value of DWI volume on admission was 33.50, the sensitivity and specificity for predicting functional outcome was 60 and 95.65%, respectively.

CONCLUSIONS

Evaluating DWI volume on admission, DWI volume on follow-up as well as DWI volume growth comprehensively may be useful in predicting the functional outcome of acute stroke patients after thrombectomy.

A New Era of Extended Time Window Acute Stroke Interventions Guided by Imaging

Ischemic stroke is one of the most debilitating and deadliest conditions worldwide. Intravenous t-PA is the current standard treatment within 4 hours after onset of symptoms. Recent randomized controlled trials have demonstrated the efficacy of neurointerventional intra-arterial treatment in acute ischemic stroke. About 20% of acute ischemic stroke are classified as wake-up strokes, which falls out of the conventional treatment time window. New evidence suggests that some patients with longer time from symptom onset (up to 24 hours) may benefit from thrombectomy, probably in part due to variations in collateral circulation among individual patients. Advanced imaging can play a crucial role in identifying patients who could benefit from endovascular intervention presenting within extended treatment time windows. In this article, we review the advanced imaging algorithm for ischemic stroke workup in the multiple studies published to date and summarize the results of the clinical trials for late ischemic stroke that can be clinically useful.

Hemorrhage After Endovascular Recanalization in Acute Stroke: Lesion Extent, Collaterals and Degree of Ischemic Water Uptake Mediate Tissue Vulnerability

Background and Purpose: Intracranial hemorrhage (ICH) remains a major complication of endovascular treatment (ET) in acute stroke. The aim of this study was to identify clinical and imaging predictors for ICH in patients with acute ischemic stroke undergoing successful ET.

Methods: We performed a retrospective analysis of patients with large vessel occlusion in the anterior circulation who underwent successful ET at our university medical center between 2015 and 2018. ICH was diagnosed on non-enhanced CT and a binary outcome was defined: ICH occurrence in the immediate post-interventional phase within 12–36 h (yes/no). The impacts of clinical, radiological, and interventional parameters on outcome were assessed in logistic regression models.

Results: One hundred and seven patients fulfilled the inclusion criteria. 37 (34.6%) showed an ICH of which 7 (6.5%) patients were diagnosed as symptomatic and 30 (28.04%) as asymptomatic. Multivariable regression analyses identified a lower ASPECTS (adjusted odds ratio (OR) 1.95, 95%CI: 1.4–3.63, P = 0.037), low collateral score (adjusted OR 0.12, 95%CI: 0.03–0.49, P = 0.003) and high Net Water Uptake (NWU) (adjusted OR 1.56, 95%CI: 2.34–1.03, P = 0.007) as independent predictors of ICH after successful ET.

Conclusions: CT-based quantitative NWU, ASPECTS, and collateral score mediate tissue vulnerability and are reliable independent predictors of a bleeding event after successful ET. This imaging-based prediction model might be useful for early stratification of patients at high risk of a bleeding event after ET, especially with low ASPECTS.

The effect of software post-processing applications on identification of the penumbra and core within the ischaemic region in perfusion computed tomography

Purpose

Assessment of software applications designed for post-processing of CT imaging data and perfusion maps in terms of their ability to consistently define the penumbra and core in an ischemic area.

Material and methods

This study is based on measurements conducted in a group of 65 patients with neurological symptoms suggestive of ischaemia in the area of the MCA within 12 hours following onset of the first symptoms. Non-contrast and perfusion CT were performed during an emergency duty. The acquired data were processed using various programs to obtain defined ischaemic areas and parameters. Finally, the results obtained were compared to the distribution of penumbra and core within the ischaemic area received from different perfusion mapping programs.

Results

The programs designed to convert the acquired data and to map the distribution of perfusion were also assessed for their viability in dividing the ischaemic zone into penumbra and core. There was a statistically strong correlation (0.784-0.846) between results obtained by processing of imaging data with two different packages, and then by post-processing with one package, and a poor correlation (0.315-0.554) between results obtained by processing of data with the same package, and post-processing with two different packages designed for measuring penumbra and core areas.

Conclusions

The results obtained by processing of imaging data with different software applications and by post-processing with one program developed for identifying penumbra and core areas show a strong correlation. However, the results obtained by processing imaging data with the same software application and by post-processing with different programs measuring penumbra and core areas reveal poor correlation.

Multivariate prediction of functional outcome using lesion topography characterized by acute diffusion tensor imaging

The relationship between stroke topography and functional outcome has largely been studied with binary manual lesion segmentations. However, stroke topography may be better characterized by continuous variables capable of reflecting the severity of ischemia, which may be more pertinent for long-term outcome. Diffusion Tensor Imaging (DTI) constitutes a powerful means of quantifying the degree of acute ischemia and its potential relation to functional outcome. Our aim was to investigate whether using more clinically pertinent imaging parameters with powerful machine learning techniques could improve prediction models and thus provide valuable insight on critical brain areas important for long-term outcome. Eighty-seven thrombolyzed patients underwent a DTI sequence at 24 h post-stroke. Functional outcome was evaluated at 3 months post-stroke with the modified Rankin Score and was dichotomized into good (mRS ≤ 2) and poor (mRS > 2) outcome. We used support vector machines (SVM) to classify patients into good vs. poor outcome and evaluate the accuracy of different models built with fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity asymmetry maps, and lesion segmentations in combination with lesion volume, age, recanalization status, and thrombectomy treatment. SVM classifiers built with axial diffusivity maps yielded the best accuracy of all imaging parameters (median [IQR] accuracy = 82.8 [79.3-86.2]%), compared to that of lesion segmentations (76.7 [73.3-82.8]%) when predicting 3-month functional outcome. The analysis revealed a strong contribution of clinical variables, notably - in descending order - lesion volume, thrombectomy treatment, and recanalization status, in addition to the deep white matter at the crossroads of major white matter tracts, represented by brain regions where model weights were highest. Axial diffusivity is a more appropriate imaging marker to characterize stroke topography for predicting long-term outcome than binary lesion segmentations.

Imaging in neurointerventional stroke treatment: review of the recent trials and what your neurointerventionalist wants to know from emergency radiologists

Stroke is one of the leading causes of death and disability worldwide. Standard treatment for stroke is intravenous (IV) injection of tissue plasminogen activator (t-PA) rapidly after symptom onset. However, there are limitations of IV t-PA treatment, such as a short time window for administration and risk for hemorrhage. Recent trials have demonstrated the benefit of endovascular treatment when added to standard treatment to improve outcomes for patients. Advanced imaging was utilized in some trials to identify patients with proximal intracranial occlusion to target for endovascular reperfusion therapy, and to exclude patients with large infarct cores or poor collateral circulation who would not be expected to benefit from intervention. This article summarizes the use of imaging in recent stroke trials in details, provides a stroke imaging protocol, and provides tips which radiologists should know to help their neurointerventionalists.

The Role of Diffusion-Weighted Magnetic Resonance Imaging in the Differentiation of Head and Neck Masses

The purpose of this study was to evaluate the value of diffusion-weighted MRI (DW-MRI) in differentiating benign and malignant head and neck masses by comparing their apparent diffusion coefficient (ADC) values. The study included 32 patients with a neck mass >1 cm in diameter who were examined with echo planar DW-MRI. Two different diffusion gradients (b values of b = 0 and b = 1000 s/mm²) were applied. DWI and ADC maps of 32 neck masses in 32 patients were obtained. Mean ADC values of benign and malignant neck lesions were measured and compared statistically. A total of 15 (46.9%) malignant masses and 17 (53.1%) benign masses were determined. Of all the neck masses, the ADC value of cystic masses was the highest and that of lymphomas was the lowest. The mean ADC values of benign and malignant neck masses were 1.57 × 10⁻³ mm²/s and 0.90 × 10⁻³ mm²/s, respectively. The difference between mean ADC values of benign and malignant neck masses was significant (p < 0.01). Diffusion-weighted MRI with ADC measurements can be useful in the differential diagnosis of neck masses.

Contribution of Neuro-Imaging for Prediction of Functional Recovery after Ischemic Stroke

Prediction measures of recovery and outcome after stroke perform with only modest levels of accuracy if based only on clinical data. Prediction scores can be improved by including morphologic imaging data, where size, location, and development of the ischemic lesion is best documented by magnetic resonance imaging. In addition to the primary lesion, the involvement of fiber tracts contributes to prognosis, and consequently the use of diffusion tensor imaging (DTI) to assess primary and secondary pathways improves the prediction of outcome and of therapeutic effects. The recovery of ischemic tissue and the progression of damage are dependent on the quality of blood supply. Therefore, the status of the supplying arteries and of the collateral flow is not only crucial for determining eligibility for acute interventions, but also has an impact on the potential to integrate areas surrounding the lesion that are not typically part of a functional network into the recovery process. The changes in these functional networks after a localized lesion are assessed by functional imaging methods, which additionally show altered pathways and activated secondary centers related to residual functions and demonstrate changes in activation patterns within these networks with improved performance. These strategies in some instances record activation in secondary centers of a network, for example, also in homolog contralateral areas, which might be inhibitory to the recovery of primary centers. Such findings might have therapeutic consequences, for example, image-guided inhibitory stimulation of these areas. In the future, a combination of morphological imaging including DTI of fiber tracts and activation studies during specific tasks might yield the best information on residual function, reserve capacity, and prospects for recovery after ischemic stroke.

Glyburide Advantage in Malignant Edema and Stroke (GAMES-RP) Trial: Rationale and Design

BACKGROUND

Patients with large territory infarction are at high risk of cerebral edema and neurological deterioration, including death. Preclinical studies have shown that a continuous infusion of glyburide blocks edema formation and improves outcome. We hypothesize that treatment with RP-1127 (Glyburide for Injection) reduces formation of brain edema in patients after large anterior circulation infarction.

METHODS

GAMES-RP is a prospective, randomized, double-blind, multicenter trial designed to evaluate RP-1127 in patients at high risk for the development of malignant cerebral edema. The study population consisted of subjects with a clinical diagnosis of acute severe anterior circulation ischemic stroke with a baseline diffusion-weighted image lesion between 82 and 300 cm(3) who are 18-80 years of age. The target time from symptom onset to start of study infusion was ≤10 h. Subjects were randomized to RP-1127 (glyburide for injection) or placebo and treated with a continuous infusion for 72 h.

RESULTS

The primary efficacy outcome was a composite of the modified Rankin Scale and the incidence of decompressive craniectomy, assessed at 90 days. Safety outcomes were the frequency and severity of adverse events, with a focus on cardiac- and glucose-related serious adverse events.

CONCLUSIONS

GAMES-RP was designed to provide critical information regarding glyburide for injection in patients with large hemispheric stroke and will inform the design of future studies.

Management of Hemispheric Infarction and Ischemic Swelling

PURPOSE OF REVIEW

This article provides an overview of large territory hemispheric infarction, with an emphasis on recent developments and practical issues related to its evaluation, diagnosis, monitoring, and treatment. Swelling after large infarction results in severe morbidity and often death. Early vigilance for the development of swelling is critical to optimize patient outcome. Comprehensive management is highly dependent on a strong multidisciplinary, collaborative approach.

RECENT FINDINGS

Several advances in the last decade have led to an increasingly standardized approach to the patient with significant brain swelling after stroke. In particular, early identification of patients with large stroke at high risk for deterioration, and decompressive craniectomy as an important treatment option, are two significant advances.

SUMMARY

Effective management of hemispheric ischemic stroke and swelling requires a team skilled in the neurologic examination of critically ill patients and a broad understanding of the natural history of brain swelling after stroke.

A Quantitative Method Using Head Noncontrast CT Scans to Detect Hyperacute Nonvisible Ischemic Changes in Patients With Stroke

PURPOSE

Because clinical evaluation of noncontrast computed tomography (CT) has a poor sensitivity in the evaluation of acute ischemic stroke, computer-aided diagnosis may be able to facilitate the performance. Recently, we introduced a computational method for the detection and localization of visible infarcts. Herein, we aimed to evaluate and extend a previous method, the Stroke Imaging Marker (SIM), to localize nonvisible hyperacute ischemia.

MATERIALS AND METHODS

On the basis of the SIM and its components-the ratio of percentile differences in subranges of Hounsfield Unit (HU) distribution (P-ratio), ratio of voxels count in ranges of brain CT intensity, median HU attenuation value-the infarct localization was performed in 140 early and follow-up scans of 70 patients. In none of the early scans was the infarct visible to a radiologist or an experienced stroke neuroradiologist. The infarcted hemisphere detection rate (HDR) and sensitivity of infarct localization were measured by overlapping the region of detected tissue in the initial scan, with the gold standard set for the fully visible stroke in the follow-up scan.

RESULTS

The best performance of the algorithm was found for the P-ratio including seven percentile subranges within the range of 35th-75th percentile. The modified SIM provided a 76% ischemic HDR and 54% sensitivity in spatial localization of hyperacute ischemia (68% among properly detected infarct sides).

CONCLUSION

The improved SIM is a dedicated and potentially useful tool for hyperacute nonvisible brain infarct detection from CT scans and may contribute to reduction of image-to-needle time in patients eligible for revascularization therapy.

The association of insular stroke with lesion volume

The insula has been implicated in many sequelae of stroke. It is the area most commonly infarcted in people with post-stroke arrhythmias, loss of thermal sensation, hospital acquired pneumonia, and apraxia of speech. We hypothesized that some of these results reflect the fact that: (1) ischemic strokes that involve the insula are larger than strokes that exclude the insula (and therefore are associated with more common and persistent deficits); and (2) insular involvement is a marker of middle cerebral artery (MCA) occlusion. We analyzed MRI scans of 861 patients with acute ischemic hemispheric strokes unselected for functional deficits, and compared infarcts involving the insula to infarcts not involving the insula using t-tests for continuous variables and chi square tests for dichotomous variables. Mean infarct volume was larger for infarcts including the insula (n = 232) versus excluding the insula (n = 629): 65.8 ± 78.8 versus 10.2 ± 15.9 cm³ (p < 0.00001). Even when we removed lacunar infarcts, mean volume of non-lacunar infarcts that included insula (n = 775) were larger than non-lacunar infarcts (n = 227) that excluded insula: 67.0 cm³ ± 79.2 versus 11.5 cm³ ± 16.7 (p < 0.00001). Of infarcts in the 90th percentile for volume, 87% included the insula (χ² = 181.8; p < 0.00001). Furthermore, 79.0% infarcts due to MCA occlusion included the insula; 78.5% of infarcts without MCA occlusion excluded the insula (χ² = 93.1; p < 0.0001). The association between insular damage and acute or chronic sequelae likely often reflects the fact that insular infarct is a marker of large infarcts caused by occlusion of the MCA more than a specific role of the insula in a range of functions. Particularly in acute stroke, some deficits may also be due to ischemia of the MCA or ICA territory caused by large vessel occlusion.

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The insula is the most commonly infarcted area in patients with a wide range of deficits.

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In 861 acute ischemic hemispheric strokes, mean infarct volume was much larger when infarct included the insula (p < 0.00001).

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Of infarcts in the 90th percentile for volume, 87% included the insula (χ² = 181.8; p < 0.00001).

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Nearly 80% of infarcts due to MCA occlusion included the insula

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Identified associations between insular infarct and deficits should control for lesion volume.

Imaging acute ischemic stroke

Acute ischemic stroke is common and often treatable, but treatment requires reliable information on the state of the brain that may be provided by modern neuroimaging. Critical information includes: the presence of hemorrhage; the site of arterial occlusion; the size of the early infarct "core"; and the size of underperfused, potentially threatened brain parenchyma, commonly referred to as the "penumbra." In this chapter we review the major determinants of outcomes in ischemic stroke patients, and the clinical value of various advanced computed tomography and magnetic resonance imaging methods that may provide key physiologic information in these patients. The focus is on major strokes due to occlusions of large arteries of the anterior circulation, the most common cause of a severe stroke syndrome. The current evidence-based approach to imaging the acute stroke patient at the Massachusetts General Hospital is presented, which is applicable for all stroke types. We conclude with new information on time and stroke evolution that imaging has revealed, and how it may open the possibilities of treating many more patients.

The emerging age of endovascular treatment of acute ischaemic stroke and the role of CT angiography in patient work-up: a guide for the radiologist

Recent trial evidence suggests that for patients suffering large-vessel occlusive stroke, endovascular therapy based on the stent-retriever technique is associated with superior clinical outcomes when compared to intravenous thrombolysis alone. The challenge now is how this service is to be delivered. This may involve both centralisation of services around large cities and development of robust networks to receive patients from district general hospitals situated further afield. Both diagnostic and interventional neuroradiology will need to expand. Furthermore, we suggest that it would be advantageous for radiology departments in those hospitals receiving hyperacute stroke patients to perform computed tomography (CT) angiography in addition to non-contrast CT, which also has implications for service delivery in these units. This could swiftly aid identification of patients who might benefit from thrombectomy and improve decision-making through demonstration of occlusive thrombus and of collateral status.

Deep Learning of Tissue Fate Features in Acute Ischemic Stroke

In acute ischemic stroke treatment, prediction of tissue survival outcome plays a fundamental role in the clinical decision-making process, as it can be used to assess the balance of risk vs. possible benefit when considering endovascular clot-retrieval intervention. For the first time, we construct a deep learning model of tissue fate based on randomly sampled local patches from the hypoperfusion (Tmax) feature observed in MRI immediately after symptom onset. We evaluate the model with respect to the ground truth established by an expert neurologist four days after intervention. Experiments on 19 acute stroke patients evaluated the accuracy of the model in predicting tissue fate. Results show the superiority of the proposed regional learning framework versus a single-voxel-based regression model.

Physiologic imaging in acute stroke: Patient selection

Treatment of acute stroke is changing, as endovascular intervention becomes an important adjunct to tissue plasminogen activator. An increasing number of sophisticated physiologic imaging techniques have unique advantages and applications in the evaluation, diagnosis, and treatment-decision making of acute ischemic stroke. In this review, we first highlight the strengths, weaknesses, and possible indications for various stroke imaging techniques. How acute imaging findings in each modality have been used to predict functional outcome is discussed. Furthermore, there is an increasing emphasis on using these state-of-the-art imaging modalities to offer maximal patient benefit through IV therapy, endovascular thrombolytics, and clot retrieval. We review the burgeoning literature in the determination of stroke treatment based on acute, physiologic imaging findings.

Acute ischemic stroke treatment, part 1: patient selection "the 50% barrier and the capillary index score"

The current strategy for intra-arterial treatment (IAT) of acute ischemic stroke focuses on minimizing time from ictus to revascularization and maximizing revascularization. Employing this strategy has yet to lead to improved rates of successful outcomes. However, the collateral blood supply likely plays a significant role in maintaining viable brain tissue during ischemia. Based on our prior work, we believe that only approximately 50% of patients are genetically predisposed to have sufficient collaterals for a good outcome following treatment, a concept we call the 50% barrier. The Capillary Index Score (CIS) has been developed as a tool to identify patients with a sufficient collateral blood supply to maintain tissue viability prior to treatment. Patients with a favorable CIS (f CIS) may be able to achieve a good outcome with IAT beyond an arbitrary time window. The CIS is incorporated into a proposed patient treatment algorithm. For patients suffering from a large stroke without aphasia, a non-enhanced head CT should be followed by CT angiography (CTA). For patients without signs of stroke mimics or visible signs of structural changes due to large irreversible ischemia, CTA can help confirm the vascular occlusion and location. The CIS can be obtained from a diagnostic cerebral angiogram, with IAT offered to patients categorized as f CIS.

Pre-admission CHADS2, CHA2DS2-VASc, and R2CHADS2 Scores on Severity and Functional Outcome in Acute Ischemic Stroke with Atrial Fibrillation

BACKGROUND

We examined the association between pre-admission risk scores and severity on admission and functional outcome in acute ischemic stroke with atrial fibrillation (AF).

METHODS

Between September 2011 and April 2014, we retrospectively extracted consecutive ischemic stroke patients with AF whose pre-admission modified Rankin Scale (mRS) score was 2 or less from our prospective database. Pre-admission CHADS2, CHA2DS2-VASc, and R2CHADS2 scores were calculated in each patient, and their association with the National Institutes of Health Stroke Scale (NIHSS) score on admission or unfavorable outcome (mRS ≥ 3 at 3 months from the onset) was assessed.

RESULTS

A total of 344 patients (189 were men; age, 77.7 ± 10.0 years) were included in the analysis. The median pre-admission CHADS2, CHA2DS2-VASc, and R2CHADS2 scores were 2, 4, and 4, respectively. NIHSS score on admission was positively correlated with pre-admission CHADS2 (ρ = .116, P = .031), CHA2DS2-VASc (ρ = .166, P = .020), and R2CHADS2 scores (ρ = .106, P = .049). Receiver operating characteristic (ROC) curve analysis revealed that pre-admission CHADS2 score of 2 or more (sensitivity, 80%; specificity, 45%; area under the ROC curve [AUC], .654), CHA2DS2-VASc score of 3 or more (sensitivity, 86%; specificity, 44%; AUC, .683), and R2CHADS2 score of 4 or more (sensitivity, 61%; specificity, 62%; AUC, .657) were associated with unfavorable outcome. The pre-admission CHA2DS2-VASc score was better than the pre-admission CHADS2 score in estimating unfavorable outcome (P = .017). In multivariate analysis, cutoffs of these scores, female sex, higher NIHSS score, and internal carotid artery occlusion were associated with unfavorable outcome.

CONCLUSIONS

Pre-admission CHADS2, CHA2DS2-VASc, and R2CHADS2 scores were associated with onset severity and functional outcome in acute ischemic stroke with AF.

Imaging Patterns and Management Algorithms in Acute Stroke: An Update for the Emergency Radiologist

Neuroimaging plays a key role in the initial work-up of patients with symptoms of acute stroke. Understanding the advantages and limitations of available CT and MR imaging techniques and how to use them optimally in the emergency setting is crucial for accurately making the diagnosis of acute stroke and for rapidly determining appropriate treatment.

Data science of stroke imaging and enlightenment of the penumbra

Imaging protocols of acute ischemic stroke continue to hold significant uncertainties regarding patient selection for reperfusion therapy with thrombolysis and mechanical thrombectomy. Given that patient inclusion criteria can easily introduce biases that may be unaccounted for, the reproducibility and reliability of the patient screening method is of utmost importance in clinical trial design. The optimal imaging screening protocol for selection in targeted populations remains uncertain. Acute neuroimaging provides a snapshot in time of the brain parenchyma and vasculature. By identifying the at-risk but still viable penumbral tissue, imaging can help estimate the potential benefit of a reperfusion therapy in these patients. This paper provides a perspective about the assessment of the penumbral tissue in the context of acute stroke and reviews several neuroimaging models that have recently been developed to assess the penumbra in a more reliable fashion. The complexity and variability of imaging features and techniques used in stroke will ultimately require advanced data driven software tools to provide quantitative measures of risk/benefit of recanalization therapy and help aid in making the most favorable clinical decisions.

Multimodal imaging in acute ischemic stroke

OPINION STATEMENT

Recent years have seen the development of novel neuroimaging techniques whose roles in the management of acute stroke are sometimes confusing and controversial. This may be attributable in part to a focus on establishing simplified algorithms and terminology that omit consideration of the basic pathophysiology of cerebral ischemia and, consequently, of the full potential for optimizing patients' care based upon their individual imaging findings. This review begins by discussing cerebral hemodynamic physiology and of the effects of hemodynamic disturbances upon the brain. Particular attention will be paid to the hemodynamic measurements and markers of tissue injury that are provided by common clinical imaging techniques, with the goal of enabling greater confidence and flexibility in understanding the potential uses of these techniques in various clinical roles, which will be discussed in the remainder of the review.

Combining MRI with NIHSS thresholds to predict outcome in acute ischemic stroke: value for patient selection

BACKGROUND AND PURPOSE

Selecting acute ischemic stroke patients for reperfusion therapy on the basis of a diffusion-perfusion mismatch has not been uniformly proved to predict a beneficial treatment response. In a prior study, we have shown that combining clinical with MR imaging thresholds can predict clinical outcome with high positive predictive value. In this study, we sought to validate this predictive model in a larger patient cohort and evaluate the effects of reperfusion therapy and stroke side.

MATERIALS AND METHODS

One hundred twenty-three consecutive patients with anterior circulation acute ischemic stroke underwent MR imaging within 6 hours of stroke onset. DWI and PWI volumes were measured. Lesion volume and NIHSS score thresholds were used in models predicting good 3-month clinical outcome (mRS 0-2). Patients were stratified by treatment and stroke side.

RESULTS

Receiver operating characteristic analysis demonstrated 95.6% and 100% specificity for DWI > 70 mL and NIHSS score > 20 to predict poor outcome, and 92.7% and 91.3% specificity for PWI (mean transit time) < 50 mL and NIHSS score < 8 to predict good outcome. Combining clinical and imaging thresholds led to an 88.8% (71/80) positive predictive value with a 65.0% (80/123) prognostic yield. One hundred percent specific thresholds for DWI (103 versus 31 mL) and NIHSS score (20 versus 17) to predict poor outcome were significantly higher in treated (intravenous and/or intra-arterial) versus untreated patients. Prognostic yield was lower in right- versus left-sided strokes for all thresholds (10.4%-20.7% versus 16.9%-40.0%). Patients with right-sided strokes had higher 100% specific DWI (103.1 versus 74.8 mL) thresholds for poor outcome, and the positive predictive value was lower.

CONCLUSIONS

Our predictive model is validated in a much larger patient cohort. Outcome may be predicted in up to two-thirds of patients, and thresholds are affected by stroke side and reperfusion therapy.

Prediction of infarction and reperfusion in stroke by flow- and volume-weighted collateral signal in MR angiography

BACKGROUND AND PURPOSE

In proximal anterior circulation occlusive strokes, collateral flow is essential for good outcome. Collateralized vessel intensity in TOF- and contrast-enhanced MRA is variable due to different acquisition methods. Our purpose was to quantify collateral supply by using flow-weighted signal in TOF-MRA and blood volume-weighted signal in contrast-enhanced MRA to determine each predictive contribution to tissue infarction and reperfusion.

MATERIALS AND METHODS

Consecutively (2009-2013), 44 stroke patients with acute proximal anterior circulation occlusion met the inclusion criteria with TOF- and contrast-enhanced MRA and penumbral imaging. Collateralized vessels in the ischemic hemisphere were assessed by TOF- and contrast-enhanced MRA using 2 methods: 1) visual 3-point collateral scoring, and 2) collateral signal quantification by an arterial atlas-based collateral index. Collateral measures were tested by receiver operating characteristic curve and logistic regression against 2 imaging end points of tissue-outcome: final infarct volume and percentage of penumbra saved.

RESULTS

Visual collateral scores on contrast-enhanced MRA but not TOF were significantly higher in patients with good outcome. Visual collateral scoring on contrast-enhanced MRA was the best rater-based discriminator for final infarct volume < 90 mL (area under the curve, 0.81; P < .01) and percentage of penumbra saved >50% (area under the curve, 0.67; P = .04). Atlas-based collateral index of contrast-enhanced MRA was the overall best independent discriminator for final infarct volume of <90 mL (area under the curve, 0.94; P < .01). Atlas-based collateral index combining the signal of TOF- and contrast-enhanced MRA was the overall best discriminator for effective reperfusion (percentage of penumbra saved >50%; area under the curve, 0.89; P < .001).

CONCLUSIONS

Visual scoring of contrast-enhanced but not TOF-MRA is a reliable predictor of infarct outcome in stroke patients with proximal arterial occlusion. By atlas-based collateral assessment, TOF- and contrast-enhanced MRA both contain predictive signal information for penumbral reperfusion. This could improve risk stratification in further studies.

Percentage insula ribbon infarction of >50% identifies patients likely to have poor clinical outcome despite small DWI infarct volume

BACKGROUND AND PURPOSE

Large admission DWI infarct volume (>70 mL) is an established marker for poor clinical outcome in acute stroke. Outcome is more variable in patients with small infarcts (<70 mL). Percentage insula ribbon infarct correlates with infarct growth. We hypothesized that percentage insula ribbon infarct can help identify patients with stroke likely to have poor clinical outcome, despite small admission DWI lesion volumes.

MATERIALS AND METHODS

We analyzed the admission NCCT, CTP, and DWI scans of 55 patients with proximal anterior circulation occlusions on CTA. Percentage insula ribbon infarct (>50%, ≤50%) on DWI, NCCT, CT-CBF, and CT-MTT were recorded. DWI infarct volume, percentage DWI motor strip infarct, NCCT-ASPECTS, and CTA collateral score were also recorded. Statistical analyses were performed to determine accuracy in predicting poor outcome (mRS >2 at 90 days).

RESULTS

Admission DWI of >70 mL and DWI-percentage insula ribbon infarct of >50% were among significant univariate imaging markers of poor outcome (P < .001). In the multivariate analysis, DWI-percentage insula ribbon infarct of >50% (P = .045) and NIHSS score (P < .001) were the only independent predictors of poor outcome. In the subgroup with admission DWI infarct of <70 mL (n = 40), 90-day mRS was significantly worse in those with DWI-percentage insula ribbon infarct of >50% (n = 9, median mRS = 5, interquartile range = 2-5) compared with those with DWI-percentage insula ribbon infarct of ≤50% (n = 31, median mRS = 2, interquartile range = 0.25-4, P = .036). In patients with admission DWI infarct of >70 mL, DWI-percentage insula ribbon infarct did not have added predictive value for poor outcome (P = .931).

CONCLUSIONS

DWI-percentage insula ribbon infarct of >50% independently predicts poor clinical outcome and can help identify patients with stroke likely to have poor outcome despite small admission DWI lesion volumes.