Predictive value of ischemic lesion volume assessed with magnetic resonance imaging for neurological deficits and functional outcome poststroke: A critical review of the literature

Follow-up infarct volume on fluid attenuated inversion recovery (FLAIR) imaging in distal medium vessel occlusions: the role of cerebral blood volume index

BACKGROUND

Distal medium vessel occlusions (DMVOs) contribute substantially to the incidence of acute ischemic strokes (AIS) and pose distinct challenges in clinical management and prognosis. Neuroimaging techniques, such as Fluid Attenuation Inversion Recovery (FLAIR) imaging and cerebral blood volume (CBV) index derived from perfusion imaging, have significantly improved our ability to assess the impact of strokes and predict their outcomes. The primary objective of this study was to investigate relationship between follow-up infarct volume (FIV) as assessed by FLAIR imaging in patients with DMVOs.

METHODS

This prospectively collected, retrospective reviewed cohort study included patients from two comprehensive stroke centers within the Johns Hopkins Medical Enterprise, spanning August 2018-October 2022. The cohort consisted of adults with AIS attributable to DMVO. Detailed imaging analyses were conducted, encompassing non-contrast CT, CT angiography (CTA), CT perfusion (CTP), and FLAIR imaging. Univariable and multivariable linear regression models were employed to assess the association between different factors and FIV.

RESULTS

The study included 79 patients with DMVO stroke with a median age of 69 years (IQR, 62-77 years), and 57% (n = 45) were female. There was a negative correlation between the CBV index and FIV in a univariable linear regression analysis (Beta =  - 16; 95% CI,  - 23 to  - 8.3; p < 0.001) and a multivariable linear regression model (Beta =  - 9.1 per 0.1 change; 95% CI,  - 15 to  - 2.7; p = 0.006). Diabetes was independently associated with larger FIV (Beta = 46; 95% CI, 16 to 75; p = 0.003). Additionally, a higher baseline ASPECTS was associated with lower FIV (Beta =  - 30; 95% CI,  - 41 to  - 20; p < 0.001).

CONCLUSION

Our findings underscore the CBV index as an independent association with FIV in DMVOs, which highlights the critical role of collateral circulation in determining stroke outcomes in this patient population. In addition, our study confirms a negative association of ASPECTS with FLAIR FIV and identifies diabetes as independent factor associated with larger FIV. These insights pave the way for further large-scale, prospective studies to corroborate these findings, thereby refining the strategies for stroke prognostication and management.

Biomarkers for prognostic functional recovery poststroke: A narrative review

Background and objective: Prediction of poststroke recovery can be expressed by prognostic biomarkers that are related to the pathophysiology of stroke at the cellular and molecular level as well as to the brain structural and functional reserve after stroke at the systems neuroscience level. This study aimed to review potential biomarkers that can predict poststroke functional recovery. Methods: A narrative review was conducted to qualitatively summarize the current evidence on biomarkers used to predict poststroke functional recovery. Results: Neurophysiological measurements and neuroimaging of the brain and a wide diversity of molecules had been used as prognostic biomarkers to predict stroke recovery. Neurophysiological studies using resting-state electroencephalography (EEG) revealed an interhemispheric asymmetry, driven by an increase in low-frequency oscillation and a decrease in high-frequency oscillation in the ipsilesional hemisphere relative to the contralesional side, which was indicative of individual recovery potential. The magnitude of somatosensory evoked potentials and event-related desynchronization elicited by movement in task-related EEG was positively associated with the quantity of recovery. Besides, transcranial magnetic stimulation (TMS) studies revealed the potential values of using motor-evoked potentials (MEP) and TMS-evoked EEG potentials from the ipsilesional motor cortex as prognostic biomarkers. Brain structures measured using magnetic resonance imaging (MRI) have been implicated in stroke outcome prediction. Specifically, the damage to the corticospinal tract (CST) and anatomical motor connections disrupted by stroke lesion predicted motor recovery. In addition, a wide variety of molecular, genetic, and epigenetic biomarkers, including hemostasis, inflammation, tissue remodeling, apoptosis, oxidative stress, infection, metabolism, brain-derived, neuroendocrine, and cardiac biomarkers, etc., were associated with poor functional outcomes after stroke. However, challenges such as mixed evidence and analytical concerns such as specificity and sensitivity have to be addressed before including molecular biomarkers in routine clinical practice. Conclusion: Potential biomarkers with prognostic values for the prediction of functional recovery after stroke have been identified; however, a multimodal approach of biomarkers for prognostic prediction has rarely been studied in the literature. Future studies may incorporate a combination of multiple biomarkers from big data and develop algorithms using data mining methods to predict the recovery potential of patients after stroke in a more precise way.

Tanshinone IIA-Loaded Nanoparticle and Neural Stem Cell Therapy Enhances Recovery in a Pig Ischemic Stroke Model

Induced pluripotent stem cell-derived neural stem cells (iNSCs) are a multimodal stroke therapeutic that possess neuroprotective, regenerative, and cell replacement capabilities post-ischemia. However, long-term engraftment and efficacy of iNSCs is limited by the cytotoxic microenvironment post-stroke. Tanshinone IIA (Tan IIA) is a therapeutic that demonstrates anti-inflammatory and antioxidative effects in rodent ischemic stroke models and stroke patients. Therefore, pretreatment with Tan IIA may create a microenvironment that is more conducive to the long-term survival of iNSCs. In this study, we evaluated the potential of Tan IIA drug-loaded nanoparticles (Tan IIA-NPs) to improve iNSC engraftment and efficacy, thus potentially leading to enhanced cellular, tissue, and functional recovery in a translational pig ischemic stroke model. Twenty-two pigs underwent middle cerebral artery occlusion (MCAO) and were randomly assigned to a PBS + PBS, PBS + iNSC, or Tan IIA-NP + iNSC treatment group. Magnetic resonance imaging (MRI), modified Rankin Scale neurological evaluation, and immunohistochemistry were performed over a 12-week study period. Immunohistochemistry indicated pretreatment with Tan IIA-NPs increased iNSC survivability. Furthermore, Tan IIA-NPs increased iNSC neuronal differentiation and decreased iNSC reactive astrocyte differentiation. Tan IIA-NP + iNSC treatment enhanced endogenous neuroprotective and regenerative activities by decreasing the intracerebral cellular immune response, preserving endogenous neurons, and increasing neuroblast formation. MRI assessments revealed Tan IIA-NP + iNSC treatment reduced lesion volumes and midline shift. Tissue preservation and recovery corresponded with significant improvements in neurological recovery. This study demonstrated pretreatment with Tan IIA-NPs increased iNSC engraftment, enhanced cellular and tissue recovery, and improved neurological function in a translational pig stroke model.

Duration of Ischemia Affects Outcomes Independent of Infarct Size in Stroke

BACKGROUND

Delays in endovascular reperfusion for patients with large vessel occlusion stroke are known to worsen outcomes, and the mechanism is believed to be time-dependent expansion of the ischemic infarction. In this study, we hypothesize that delays in onset to reperfusion (OTR) assert an effect on outcomes independent of effects of final infarct (FI).

METHODS

We performed a subgroup analysis from the prospective multicenter COMPLETE (International Acute Ischemic Stroke Registry With the Penumbra System Aspiration Including the 3D Revascularization Device; Penumbra, Inc) registry for 257 patients with anterior circulation large vessel occlusion who underwent endovascular therapy with successful reperfusion (modified treatment in cerebral infarction score 2b/3). FI was measured by Alberta Stroke Program Early CT score and volume on 24- to 48-hour computed tomography or magnetic resonance imaging. The likelihood of 90-day good functional outcome (modified Rankin scale 0-2) was assessed by OTR and absolute risk difference (ARD) was estimated using multivariable logistic regressions adjusting for patient characteristics including FI.

RESULTS

In univariable analysis, longer OTR was associated with a decreased likelihood of good functional outcome (ARD -3% [95% CI -4.5 to -1.0]/h delay). In multivariable analysis accounting for FI, the association between OTR and functional outcome remained significant (ARD -2% [95% CI -3.5 to -0.4]/h delay) with similar ARD. This finding was maintained in the subset of patients with FI imaging using CT only, using Alberta Stroke Program Early CT Score or volumetric FI measurements, and also in patients with larger versus smaller FIs.

CONCLUSIONS

The impact of OTR on outcomes appears to be mostly through a mechanism that is independent of FI. Our findings suggest that although the field has moved toward imaging infarct core definitions of eligibility for endovascular treatment, time remains an important predictor of outcome, independent of infarct core.

The Comparison and Interpretation of Machine-Learning Models in Post-Stroke Functional Outcome Prediction

Prediction of post-stroke functional outcomes is crucial for allocating medical resources. In this study, a total of 577 patients were enrolled in the Post-Acute Care-Cerebrovascular Disease (PAC-CVD) program, and 77 predictors were collected at admission. The outcome was whether a patient could achieve a Barthel Index (BI) score of >60 upon discharge. Eight machine-learning (ML) methods were applied, and their results were integrated by stacking method. The area under the curve (AUC) of the eight ML models ranged from 0.83 to 0.887, with random forest, stacking, logistic regression, and support vector machine demonstrating superior performance. The feature importance analysis indicated that the initial Berg Balance Test (BBS-I), initial BI (BI-I), and initial Concise Chinese Aphasia Test (CCAT-I) were the top three predictors of BI scores at discharge. The partial dependence plot (PDP) and individual conditional expectation (ICE) plot indicated that the predictors’ ability to predict outcomes was the most pronounced within a specific value range (e.g., BBS-I < 40 and BI-I < 60). BI at discharge could be predicted by information collected at admission with the aid of various ML models, and the PDP and ICE plots indicated that the predictors could predict outcomes at a certain value range.

Prognostic Utility of Serum Biomarkers in Intracerebral Hemorrhage: A Systematic Review

Background. Intracerebral hemorrhage (ICH) accounts for 10-20% of all strokes and is associated with high morbidity and mortality. Recent studies have identified serum biomarkers as a means to improve outcome prognostication in poor grade ICH patients. Poor prognosis of ICH patients and complex pathophysiology of the disease necessitate prognostic serum biomarkers to help guide treatment recommendations. Objective. The objective is to systematically review all biomarkers used to predict long-term functional outcome in patients with spontaneous intracerebral hemorrhage. Results. We identified 36 studies investigating the predictive utility of 50 discrete biomarkers. Data from 4865 ICH patients were reviewed. Inflammatory biomarkers (11/50) were most often studied, followed by oxidative (8/50), then neuron and astrocyte-specific (7/50). S100 calcium binding protein B, white blood cell count, and copeptin were the most often studied individual biomarkers. The prognostic utility of 23 biomarkers was analyzed using receiver operating characteristic curves. Area under the curve (AUC) values for all available biomarkers except neutrophil/lymphocyte ratio were acceptable. Twenty of the 23 biomarkers were characterized by at least one excellent AUC value. Vascular endothelial growth factor, glial fibrillary astrocyte protein, and S100 calcium binding protein B were characterized by outstanding AUC. Conclusions. We identified the inflammatory and neuron and astrocyte-specific biomarker categories as having the greatest number of significant individual biomarker predictors of long-term outcome. Further investigation utilizing cross-validation of prediction models in a second independent group and blinded assessment of outcomes for the predictive utility of biomarkers in patients with ICH is warranted.

A systematic review of the usefulness of magnetic resonance imaging in predicting the gait ability of stroke patients

The usefulness of magnetic resonance imaging (MRI) in predicting gait ability in stroke patients remains unclear. Therefore, MRI evaluations have not yet been standardized in stroke rehabilitation. We performed a systematic review to consolidate evidence regarding the use of MRIs in predicting gait ability of stroke patients. The Medline, Cumulative Index to Nursing and Allied Health Literature, and SCOPUS databases were comprehensively searched. We included all literature published from each source’s earliest date to August 2020. We included 19 studies: 8 were classified as structure- or function-based MRI studies and 11 as neural tract integrity-based MRI studies. Most structure- or function-based MRI studies indicated that damage to motor-related areas (primary motor cortex, corona radiata, internal capsule, and basal ganglia) or insula was related to poor gait recovery. In neural tract integrity-based MRI studies, integrity of the corticospinal tract was related to gait ability. Some studies reported predictive value of the corticoreticular pathway. All included studies had some concerns, at least one, based on the Cochrane risk of bias instrument. This review suggests that MRIs are useful in predicting gait ability of stroke patients. However, we cannot make definitive conclusion regarding the predictive value, due to the lack of quantitative evaluations.

Prognostic role of neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and systemic immune inflammation index in acute ischemic stroke: A STROBE-compliant retrospective study

The acute ischemic stroke (AIS) is a devastating disease and remains the leading cause of death and disability. This study aims to evaluate the role of hematological inflammatory markers (neutrophil-to-lymphocyte ratio [NLR], platelet-to-lymphocyte ratio [PLR], and systemic immune inflammation index [SII]) in predicting the neurological recovery in acute cerebrovascular events over 1-year follow-up.Adult patients diagnosed with AIS within 3 hours from January 2016 to December 2018 were recruited retrospectively. The modified Rankin Scale (mRS) was recorded upon admission to the emergency department (ED) and 1, 3, 6, and 12 months after a stroke. The primary outcome measure was the neurological recovery. The neurological recovery was defined as an improvement in mRS score ≥ 1 compared with that at the ED admission baseline.A total of 277 consecutive adult patients with AIS within 3 hours were enrolled. The initial average of the National Institute of Health Stroke Scale was 9.2 ± 7.8, and 90.3% of patients had an mRS ≥ 2 at ED admission baseline. The overall neurological recovery rates of 48.7%, 53.7%, 59.2%, and 55.9% were observed at 1, 3, 6, and 12 months follow-up, respectively. The multivariate analysis revealed that the baseline NLR value was a significant predictor of neurological recovery at 3 months after a stroke (adjusted odds ratio = 0.89, 95% confidence interval = 0.80-0.99, P = .035).A low NLR at ED admission could be useful marker for predicting neurological recovery at 3 months after stroke.

Modeling and simulation to predict the degree of disability over time in acute ischemic stroke patients

Disability in patients with acute stroke varies over time, with the prediction of outcomes being critical for proper management. This study aimed to develop a model to predict the cumulative probability of each modified Rankin Scale (mRS) score over time with inclusion of significant covariates. Longitudinal data obtained from 193 patients, 1–24 months after onset of acute ischemic stroke, were included for a modeling analysis using nonlinear mixed‐effect modeling (NONMEM). After selecting a model that best described the time course of the probability of different mRS scores, potential covariates were tested. Visual predicted check plots, parameter estimates, and decreases in minimum objective function values were used for model evaluation. The inclusion of disease progression (DP) in the baseline proportional odds cumulative logit model significantly improved the model compared to the baseline model without DP. An inhibitory maximum effect (E_max) model was determined to be the best DP model for describing the probability of specific mRS scores over time. In the final model, DP was multiplied with the baseline cumulative logit probability with a baseline adjustment. In addition to differences in lesion volume (DLV), the final model included comorbid diabetes mellitus (DM) and baseline National Institutes of Health Stroke Scale (NIHSS) scores on E_max as statistically significant covariates. This study developed a model including DLV, NIHSS score, and comorbid DM for predicting the disability time course in patients with acute ischemic stroke. This model may help to predict disease outcomes and to develop more appropriate management plans for patients with acute stroke.

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.

Actigraphic Measurement of the Upper Limbs for the Prediction of Ischemic Stroke Prognosis: An Observational Study

Background: It is often challenging to formulate a reliable prognosis for patients with acute ischemic stroke. The most accepted prognostic factors may not be sufficient to predict the recovery process. In this view, describing the evolution of motor deficits over time via sensors might be useful for strengthening the prognostic model. Our aim was to assess whether an actigraphic-based parameter (Asymmetry Rate Index for the 24 h period (AR2_24 h)) obtained in the acute stroke phase could be a predictor of a 90 d prognosis. Methods: In this observational study, we recorded and analyzed the 24 h upper limb movement asymmetry of 20 consecutive patients with acute ischemic stroke during their stay in a stroke unit. We recorded the motor activity of both arms using two programmable actigraphic systems positioned on patients’ wrists. We clinically evaluated the stroke patients by NIHSS in the acute phase and then assessed them across 90 days using the modified Rankin Scale (mRS). Results: We found that the AR2_24 h parameter positively correlates with the 90 d mRS (r = 0.69, p < 0.001). Moreover, we found that an AR2_24 h > 32% predicts a poorer outcome (90 d mRS > 2), with sensitivity = 100% and specificity = 89%. Conclusions: Sensor-based parameters might provide useful information for predicting ischemic stroke prognosis in the acute phase.

Lesion Size- and Location-Dependent Recruitment of Contralesional Thalamus and Motor Cortex Facilitates Recovery after Stroke in Mice

Brain lesions caused by cerebral ischemia or hemorrhage lead to a local breakdown of energy homeostasis followed by irreversible cell death and long-term impairment. Importantly, local brain lesions also generate remote functional and structural disturbances, which contribute to the behavioral deficit but also impact the recovery of function. While spontaneous recovery has been associated with endogenous repair mechanisms at the vascular, neural, and immune cell levels, the impact of structural plasticity on sensory-motor dysfunction and recovery thereof remains to be elucidated by longitudinal imaging in a mouse model. Here, we applied behavioral assessments, in vivo fiber tracking, and histological validation in a photothrombotic stroke mouse model. Atlas-based whole-brain structural connectivity analysis and ex vivo histology revealed secondary neurodegeneration in the ipsilesional brain areas, mostly in the dorsal sensorimotor area of the thalamus. Furthermore, we describe for the first time a lesion size-dependent increase in structural connectivity between the contralesional primary motor cortex and thalamus with the ipsilesional cortex. The involvement of the contralesional hemisphere was associated with improved functional recovery relative to lesion size. This study highlights the importance of in vivo fiber tracking and the role of the contralesional hemisphere during spontaneous functional improvement as a potential novel stroke biomarker and therapeutic targets.

Functional Recovery Patterns of Hemorrhagic and Ischemic Stroke Patients Under Post-Acute Care Rehabilitation Program

BACKGROUND

Tailored rehabilitation programs for stroke patients cannot be made without knowledge of their recovery potential. The aim of this study is to characterize the functional recovery patterns of ischemic stroke (IS) and intracerebral hemorrhage (ICH) patients under post-acute care stroke rehabilitation.

METHODS

This retrospective study analyzed the data of patients enrolled in the Post-Acute Care-Cerebrovascular Disease (PAC-CVD) rehabilitation program, which provides an individualized 1- to 3-hour intensive physical, occupational, and speech and language therapy for post-acute stroke patients in Taoyuan Chang Gung Memorial hospital in Taiwan. Our primary endpoint measure was Barthel Index (BI), and secondary endpoint measures included other 12 functional measures.

RESULTS

A total of 489 patients were included for analysis. Patients with stroke history had less BI improvement than those who suffered their first-ever stroke. In first-ever stroke patients who had completed 6 to 12 weeks of PAC-CVD program, subcortical ICH patients had greater BI, quality of life, sensation, and balance improvements, and had greater late-phase recovery than their IS counterparts. In IS patients, those with age >75 had less BI improvement; those with National Institute of Health Stroke Scale (NIHSS) score 1-5 had greater Motor Activity Log quality of use (MAL-quality) improvement than those with NIHSS score >5; those with Mini-Mental State Examination (MMSE) score ≥24 had greater BI and instrumental activities of daily living (IADL) improvement. Using the general linear model, previous stroke (ß: -6.148, p=0.01) and subcortical ICH (ß: 5.04, p=0.03) were factors associated with BI improvement.

CONCLUSION

Subcortical ICH patients have greater functional improvement and greater late-phase recovery than their IS counterparts following PAC rehabilitation. More studies are needed to validate our findings and unravel the underlying mechanisms of stroke recovery to optimize the treatment strategy following a stroke.

Neural Stem Cell Extracellular Vesicles Disrupt Midline Shift Predictive Outcomes in Porcine Ischemic Stroke Model

Magnetic resonance imaging (MRI) is a clinically relevant non-invasive imaging tool commonly utilized to assess stroke progression in real time. This study investigated the utility of MRI as a predictive measure of clinical and functional outcomes when a stroke intervention is withheld or provided, in order to identify biomarkers for stroke functional outcome under these conditions. Fifteen MRI and ninety functional parameters were measured in a middle cerebral artery occlusion (MCAO) porcine ischemic stroke model. Multiparametric analysis of correlations between MRI measurements and functional outcome was conducted. Acute axial and coronal midline shift (MLS) at 24 h post-stroke were associated with decreased survival and recovery measured by modified Rankin scale (mRS) and were significantly correlated with 52 measured acute (day 1 post) and chronic (day 84 post) gait and behavior impairments in non-treated stroked animals. These results suggest that MLS may be an important non-invasive biomarker that can be used to predict patient outcomes and prognosis as well as guide therapeutic intervention and rehabilitation in non-treated animals and potentially human patients that do not receive interventional treatments. Neural stem cell–derived extracellular vesicle (NSC EV) was a disruptive therapy because NSC EV administration post-stroke disrupted MLS correlations observed in non-treated stroked animals. MLS was not associated with survival and functional outcomes in NSC EV–treated animals. In contrast to untreated animals, NSC EVs improved stroked animal outcomes regardless of MLS severity.

Wake-up stroke: thrombolysis reduces ischemic lesion volume and neurological deficit

BACKGROUNDS

Wake-Up Stroke (WUS) patients are generally excluded from thrombolytic therapy (rTPA) due to the unknown time of stroke onset. This study aimed to investigate the effects of rTPA in WUS patients during every day clinical scenarios, by measuring ischemic lesion volume and functional outcomes compared to non-treated WUS patients.

METHODS

We retrospectively analyzed clinical and imaging data of 149 (75 rTPA; 74 non-rTPA) patients with acute ischemic WUS. Ischemic volume was calculated on follow-up CT and functional outcomes were the NIHSS and mRS comparing rTPA and non-rTPA WUS. Patients were selected using ASPECTS > 6 on CT and/or ischemic penumbra > 50% of hypoperfused tissue on CTP.

RESULTS

A reduced volume was measured on the follow-up CT for rTPA (1 mL, 0-8) compared to the non-rTPA patients (10 mL, 0-40; p = 0.000). NIHSS at 7 days from admission was significantly lower in the rTPA (1, 0-4) compared to non-rTPA group (3, 1-9; p = 0.015), as was the percentage of improvement (ΔNIHSS) (70% vs 50%; p = 0.002). A higher prevalence of mRS 0-2 was observed in the rTPA compared to the non-rTPA (54% vs 39%; p = 0.060). Multivariate analysis showed that NIHSS at baseline and rTPA treatment are significant predictors of good outcome both in terms of NIHSS at 7 days and ischemic lesion volume on follow-up CT (p < 0.05).

CONCLUSIONS

rTPA in WUS patients selected with CT and/or CTP resulted in reduced ischemic infarct volume on follow-up CT and better functional outcome without increment of intracranial hemorrhages and in-hospital mortality.

Differential Impact of Acute Lesions Versus White Matter Hyperintensities on Stroke Recovery

Background

Understanding how the size of acute lesions and white matter hyperintensities (WMH) impact stroke recovery can improve our ability to predict outcomes and tailor treatments. The aim of this exploratory study was to investigate the role of acute lesion volume and WMH volume on longitudinal recovery of specific sensory, motor, and cognitive impairments after stroke using robotic and clinical measures.

Methods and Results

Eighty‐two individuals were assessed at 1, 6, 12, and 26 weeks poststroke with robotic tasks and commonly used clinical measures. The volumes of acute lesions and WMH were measured on fluid‐attenuated inversion recovery images. Linear mixed models were used to investigate the role of acute lesions and WMH on parameters derived from the robotic tasks and clinical measures. Regression analysis determined the added value of acute lesion and WMH volumes along with measures of initial performance to predict outcomes at 6 months. Acute lesion volume has widespread effects on sensory, motor, and overall functional recovery poststroke. The impact of WMH was specific to cognitive impairments. Apart from the robotic position sense task, neither lesion volume nor WMH measure had significant ability to predict outcomes at 6 months over using initial impairment as measured by robotic assessments alone.

Conclusions

While acute lesion volume and WMH may impact different impairments poststroke, their clinical utility in predicting outcomes at 6 months poststroke is limited.

Prediction of the Lethal Outcome of Acute Recurrent Cerebral Ischemic Hemispheric Stroke

Background and objectives. Stroke-induced mortality is the third most common cause of death in developed countries. Intense interest has focused on the recurrent ischemic stroke, which rate makes up 30% during first 5 years after first-ever stroke. This work aims to develop criteria for the prediction of acute recurrent cerebral ischemic hemispheric stroke (RCIHS) outcome on the basis of comprehensive baseline clinical, laboratory, and neuroimaging examinations. Materials and Methods. One hundred thirty-six patients (71 males and 65 females, median age 74 (65; 78)) with acute RCIHS were enrolled in the study. All patients underwent a detailed clinical and neurological examination using National Institutes of Health Stroke Scale (NIHSS), computed tomography of the brain, hematological, and biochemical investigations. In order to detect the dependent and independent risk factors of the lethal outcome of the acute period of RCIHS, univariable and multivariable regression analysis were conducted. A receiver operating characteristic (ROC) analysis with the calculation of sensitivity and specificity was performed to determine the prediction variables. Results. Twenty-five patients died. The independent predictors of the lethal outcome of acute RCIHS were: Baseline NIHSS score (OR 95% CІ 1.33 (1.08-1.64), p = 0.0003), septum pellucidum displacement (OR 95% CI 1.53 (1.17-2.00), p = 0.0021), glucose serum level (OR 95% CI 1.28 (1.09-1.50), p = 0.0022), neutrophil-to-lymphocyte ratio (OR 95% CI 1.11 (1.00-1.21), p = 0.0303). The mathematical model, which included these variables was developed and it could determine the prognosis of lethal outcome of the acute RCIHS with an accuracy of 86.8% (AUC = 0.88 ± 0.04 (0.88-0.93), p < 0.0001).

Ischemic Stroke in Pontine and Corona Radiata: Location Specific Impairment of Neural Network Investigated With Resting State fMRI

Objective: This study aims to investigate location-specific functional remodeling following ischemic stroke in pons and corona radiata.

Methods: This study was approved by the local Institutional Review Board. Written consent was obtained from each of the participants prior to the MRI examination. Thirty six subjects with first ever acute ischemic stroke in pons (PS, n = 15, aged 62.8 ± 11.01 years) or corona radiata (CRS, n = 21, aged 59.33 ± 13.84 years) as well as 30 age and sex matched healthy controls (HC, n = 30, aged 60 ± 6.43 years) were examined with resting state functional magnetic resonance imaging (rs-fMRI). Regional homogeneity (ReHo) and degree centrality (DC) were calculated using a voxel-based approach. Intergroup differences in ReHo and DC were explored using a permutation test with a threshold-free cluster enhancement (PT TFCE, number of permutations = 1,000, family-wise error rate (FWER) < 0.05).

Results: ReHo and DC alterations were identified in distributed anatomies for both PS and CRS groups. DC mainly increased in the bilateral anterior and posterior cingulate cortex, the inferior frontal-orbital gyrus, and decreased in the bilateral cuneus, calcarine, and the precuneus, while ReHo mainly decreased in the precentral and the postcentral gyri, inferior parietal lobules, precuneus, posterior cingulate cortex, and the superior occipital gyrus. PS and CRS groups were not significantly different in ReHo or DC (FWER > 0.05).

Conclusions: Focal ischemic stroke in pons or corona radiata leads to extensive alterations in the functional network centrality. IS-induced network remodeling is more anatomy-specific than pathway-specific, which may underpin the clinicotopographical profiles during the disease dynamic. Approaches targeting neural pathway and functional connectivity may shed light on a better characterization and management innovation of ischemic stroke.

Nucleic Acid Therapies for Ischemic Stroke

Stroke remains a leading cause of disability and death worldwide despite significant scientific and therapeutic advances. Therefore, there is a critical need to improve stroke prevention and treatment. In this review, we describe several examples that leverage nucleic acid therapeutics to improve stroke care through prevention, acute treatment, and recovery. Aptamer systems are under development to increase the safety and efficacy of antithrombotic and thrombolytic treatment, which represent the mainstay of medical stroke therapy. Antisense oligonucleotide therapy has shown some promise in treating stroke causes that are genetically determined and resistant to classic prevention approaches such as elevated lipoprotein (a) and cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). Targeting microRNAs may be attractive because they regulate factors involved in neuronal cell death and reperfusion-associated injury, as well as neurorestorative pathways. Lastly, microRNAs may aid reliable etiologic classification of stroke subtypes, which is important for effective secondary stroke prevention.

The effect of repeated remote ischemic postconditioning on infarct size in patients with an ischemic stroke (REPOST): study protocol for a randomized clinical trial

Background

Remote ischemic postconditioning (rIPostC) refers to the observation that repeated, short periods of ischemia protect remote areas against tissue damage during and after prolonged ischemia. Based on previous observations of a potential neuroprotective effect of rIPostC, the aim of this study is to evaluate whether repeated rIPostC after an ischemic stroke can reduce infarct size, which could be translated to an improvement in clinical outcomes.

Methods/design

We will enroll 200 ischemic stroke patients to daily rIPostC or sham conditioning during hospitalization into a randomized single-blind placebo-controlled trial. The intervention consists of twice daily exposure to four cycles of 5-min cuff inflation around the upper arm to > 20 mmHg above systolic blood pressure (i.e., rIPostC) or 50 mmHg (i.e., control), followed by 5 minutes of deflation. The primary outcome is infarct size, measured using an MRI diffusion-weighted image at the end of hospitalization. Secondary outcomes include the Modified Rankin Scale, National Institutes of Health Stroke Scale, quality of life, and cardiovascular and cerebrovascular morbidity and mortality. To explore possible underlying mechanisms of rIPostC, venous blood will be sampled to assess biomarkers of inflammation and vascular health.

Discussion

Previous studies in animals and humans, using a single bout of remote ischemic conditioning, report a potential effect of rIPostC in attenuating neural damage. Although repeated rIPostC has been investigated for cardiovascular disease patients and preclinical stroke models, no previous study has explored the potential physiological and clinical effects of repeatedly applying rIPostC during the hospitalization phase after a stroke.

Trial registration

Netherlands Trial Register, NTR6880. Registered on 8 December 2017.

Electronic supplementary material

The online version of this article (10.1186/s13063-019-3264-0) contains supplementary material, which is available to authorized users.

Stroke Longitudinal Volumetric Measures Correlate with the Behavioral Score in Non-Human Primates

Stroke is the second leading cause of death worldwide. Brain imaging data from experimental rodent stroke models suggest that size and location of the ischemic lesion relate to behavioral outcome. However, such a relationship between these two variables has not been established in Non-Human Primate (NHP) models. Thus, we aimed to evaluate whether size, location, and severity of stroke following controlled Middle Cerebral Artery Occlusion (MCAO) in NHP model correlated to neurological outcome. Forty cynomolgus macaques underwent MCAO, after four mortalities, thirty-six subjects were followed up during the longitudinal study. Structural T2 scans were obtained by magnetic resonance imaging (MRI) prior to, 48 h, and 30 days post-MCAO. Neurological function was assessed with the Non-human Primate Stroke Scale (NHPSS). T2 whole lesion volume was calculated per subject. At chronic stages, remaining brain volume was computed, and the affected hemisphere parceled into 50 regions of interest (ROIs). Whole and parceled volumetric measures were analyzed in relation to the NHPSS score. The longitudinal lesion volume evaluation showed a positive correlation with the NHPSS score, whereas the remaining brain volume negatively correlated with the NHPSS. Following ROI parcellation, NHPSS outcome correlated with frontal, temporal, occipital, and middle white matter, as well as the internal capsule, and the superior temporal and middle temporal gyri, and the caudate nucleus. These results represent an important step in stroke translational research by demonstrating close similarities between the NHP stroke model and the clinical characteristics following a human stroke and illustrating significant areas that could represent targets for novel neuroprotective strategies.

Human Neural Stem Cell Extracellular Vesicles Improve Recovery in a Porcine Model of Ischemic Stroke

BACKGROUND AND PURPOSE

Recent work from our group suggests that human neural stem cell-derived extracellular vesicle (NSC EV) treatment improves both tissue and sensorimotor function in a preclinical thromboembolic mouse model of stroke. In this study, NSC EVs were evaluated in a pig ischemic stroke model, where clinically relevant end points were used to assess recovery in a more translational large animal model.

METHODS

Ischemic stroke was induced by permanent middle cerebral artery occlusion (MCAO), and either NSC EV or PBS treatment was administered intravenously at 2, 14, and 24 hours post-MCAO. NSC EV effects on tissue level recovery were evaluated via magnetic resonance imaging at 1 and 84 days post-MCAO. Effects on functional recovery were also assessed through longitudinal behavior and gait analysis testing.

RESULTS

NSC EV treatment was neuroprotective and led to significant improvements at the tissue and functional levels in stroked pigs. NSC EV treatment eliminated intracranial hemorrhage in ischemic lesions in NSC EV pigs (0 of 7) versus control pigs (7 of 8). NSC EV-treated pigs exhibited a significant decrease in cerebral lesion volume and decreased brain swelling relative to control pigs 1-day post-MCAO. NSC EVs significantly reduced edema in treated pigs relative to control pigs, as assessed by improved diffusivity through apparent diffusion coefficient maps. NSC EVs preserved white matter integrity with increased corpus callosum fractional anisotropy values 84 days post-MCAO. Behavior and mobility improvements paralleled structural changes as NSC EV-treated pigs exhibited improved outcomes, including increased exploratory behavior and faster restoration of spatiotemporal gait parameters.

CONCLUSIONS

This study demonstrated for the first time that in a large animal model novel NSC EVs significantly improved neural tissue preservation and functional levels post-MCAO, suggesting NSC EVs may be a paradigm changing stroke therapeutic.

Predicting the pattern and severity of chronic post-stroke language deficits from functionally-partitioned structural lesions

There is an ever-increasing wealth of knowledge arising from basic cognitive and clinical neuroscience on how speech and language capabilities are organised in the brain. It is, therefore, timely to use this accumulated knowledge and expertise to address critical research challenges, including the ability to predict the pattern and level of language deficits found in aphasic patients (a third of all stroke cases). Previous studies have mainly focused on discriminating between broad aphasia dichotomies from purely anatomically-defined lesion information. In the current study, we developed and assessed a novel approach in which core language areas were mapped using principal component analysis in combination with correlational lesion mapping and the resultant ‘functionally-partitioned’ lesion maps were used to predict a battery of 21 individual test scores as well as aphasia subtype for 70 patients with chronic post-stroke aphasia. Specifically, we used lesion information to predict behavioural scores in regression models (cross-validated using 5-folds). The winning model was identified through the adjusted R² (model fit to data) and performance in predicting holdout folds (generalisation to new cases). We also used logistic regression to predict fluent/non-fluent status and aphasia subtype. Functionally-partitioned models generally outperformed other models at predicting individual tests, fluency status and aphasia subtype.

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Predict the pattern and level of language deficits found in chronic aphasic patients

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Use principal component analysis to identify functional lesion maps

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Functionally-partitioned lesion maps used as predictor variables instead of lesion volume

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Functionally-partitioned lesion model plus age produced the best regression model

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Model can successfully predict fluent/non-fluent types and aphasia classification

Cortical disconnection of the ipsilesional primary motor cortex is associated with gait speed and upper extremity motor impairment in chronic left hemispheric stroke

Advances in neuroimaging have enabled the mapping of white matter connections across the entire brain, allowing for a more thorough examination of the extent of white matter disconnection after stroke. To assess how cortical disconnection contributes to motor impairments, we examined the relationship between structural brain connectivity and upper and lower extremity motor function in individuals with chronic stroke. Forty-three participants [mean age: 59.7 (±11.2) years; time poststroke: 64.4 (±58.8) months] underwent clinical motor assessments and MRI scanning. Nonparametric correlation analyses were performed to examine the relationship between structural connectivity amid a subsection of the motor network and upper/lower extremity motor function. Standard multiple linear regression analyses were performed to examine the relationship between cortical necrosis and disconnection of three main cortical areas of motor control [primary motor cortex (M1), premotor cortex (PMC), and supplementary motor area (SMA)] and motor function. Anatomical connectivity between ipsilesional M1/SMA and the (1) cerebral peduncle, (2) thalamus, and (3) red nucleus were significantly correlated with upper and lower extremity motor performance (P ≤ 0.003). M1-M1 interhemispheric connectivity was also significantly correlated with gross manual dexterity of the affected upper extremity (P = 0.001). Regression models with M1 lesion load and M1 disconnection (adjusted for time poststroke) explained a significant amount of variance in upper extremity motor performance (R²  = 0.36-0.46) and gait speed (R²  = 0.46), with M1 disconnection an independent predictor of motor performance. Cortical disconnection, especially of ipsilesional M1, could significantly contribute to variability seen in locomotor and upper extremity motor function and recovery in chronic stroke. Hum Brain Mapp 39:120-132, 2018. © 2017 Wiley Periodicals, Inc.

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.

Predicting Domain-Specific Health-Related Quality of Life Using Acute Infarct Volume

BACKGROUND AND PURPOSE

Limited data exist on the relationship between acute infarct volume and health-related quality of life (HRQOL) measures after ischemic stroke. We evaluated whether acute infarct volume predicts domain-specific Neuro-Quality of Life scores at 3 months after stroke.

METHODS

Between 2012 and 2014, we prospectively enrolled consecutive patients with ischemic stroke and calculated infarct volume. Outcome scores at 3 months included modified Rankin Scale and Neuro-Quality of Life T scores. We evaluated whether volume organized by quartiles predicted modified Rankin Scale and HRQOL scores at 3 months using logistic and linear regression as appropriate, adjusting for relevant covariates. We calculated variance accounted for (R²) overall and by volume for each domain of HRQOL.

RESULTS

Among 490 patients (mean age 64.2±15.86 years; 51.2% male; 63.3% White) included for analysis, 58 (11.8%) were disabled (modified Rankin Scale score of >2) at 3 months. In unadjusted analysis, the highest volume quartile remained a significant predictor of 1 HRQOL domain, applied cognition-general concerns (R²=0.06; P<0.001). Our fully adjusted prediction model explained 32% to 51% of the variance in HRQOL: upper extremity (R²=0.32), lower extremity (R²=0.51), executive function (R²=0.45), and general concerns (R²=0.34).

CONCLUSIONS

Acute infarct volume is a poor predictor of HRQOL domains after ischemic stroke, with the exception of the cognitive domain. Overall, clinical and imaging variables explained <50% of the variance in HRQOL outcomes at 3 months. Our data imply that a broad range of factors, some known and others undiscovered, may better predict poststroke HRQOL than what is currently available.

Risk Factors, Vascular Lesion Distribution, Outcome and Recurrence of Strokes Due to Intracranial Atherosclerosis: One Year Data from Hyderabad Stroke Registry

Background:

Intracranial atherosclerotic stenosis (ICAS) is a common cause of ischemic stroke in Asian countries and probably in India.

Aim:

The aim of this study was to describe the risk factors, distribution of vascular lesions, recurrence and outcome of stroke due to ICAS.

Methodology:

A total of 100 consecutive patients of ischemic stroke due to ICAS were enrolled prospectively from January 1, 2015, to December 31, 2015, and followed for 1 year for treatment compliance and recurrence. The details about demographics, risk factors, and vascular lesions were noted.

Results:

There were 68 males and 32 females. Hypertension (HTN), diabetes, alcohol, smoking, hyperlipidemia, and hyperhomocysteinemia was present in 82%, 52%, 34%, 33%, 28%, and 23%, respectively. The number of arteries involved were middle cerebral artery, 53 (37.3%); posterior cerebral artery, 24 (16.9%); internal cerebral artery, 21 (14.8%); vertebral artery, 18 (12.7%); basilar artery, 6 (4.2%); and anterior cerebral artery, 6 (4.2%). Seventeen (17%) patients had a recurrent stroke during 1 year follow-up. The presence of uncontrolled HTN and diabetes mellitus after discharge were significantly associated with stroke recurrence (P < 0.05). The use of dual antiplatelet agents and statins was found to have a significant effect in the prevention of recurrent stroke (P < 0.05). Severe stroke at presentation and presence of hemiparesis were the predictors for unfavorable outcome at 3 months (P < 0.05).

Conclusion:

Risk factors, distribution of vascular lesions and high recurrence of stroke due to ICAS in this study is similar to that reported from other Asian countries. Aggressive medical management and risk factor control remains the best strategy for preventing recurrence.

MRI based thrombolysis for FLAIR-negative stroke patients within 4.5-6h after symptom onset

To investigate the feasibility of DWI-FLAIR mismatch in identifying patients who might benefit from thrombolytic therapy within 4.5-6h, we analyzed the data of 105 ischemic stroke patients with known time of symptom onset who underwent MRI within 6h of stroke and thrombolysis between December 2006 and December 2013. They were divided into three groups: symptom onset within 4.5h (n=66); 4.5-6h and FLAIR images negative (n=9); and 4.5-6h and FLAIR images positive (n=30). Outcome of thrombolysis was assessed for each group by recanalization rate, National Institutes of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS) scores. The results showed that mismatch between positive DWI and negative FLAIR images identified patients within 4.5h of symptom onset with sensitivity, specificity, positive predictive value and negative predictive value of 40.9%, 76.9%, and 75% and 43.5%. Recanalization rate, NIHSS score and mRS score were all better in both the 0-4.5h and 4.5-6h FLAIR-negative groups than in the 4.5-6h FLAIR-positive group (p<0.05). These data demonstrate that within 4.5-6h of symptom onset, patients with negative FLAIR images may benefit from thrombolysis therapy.

Lesion Topography and Microscopic White Matter Tract Damage Contribute to Cognitive Impairment in Symptomatic Carotid Artery Disease

Subcortical disconnection of cognitive neural networks is a key mechanism of cognitive impairment in patients with probable vascular cognitive disorder.

Purpose

To investigate associations between neuroimaging markers of cerebrovascular disease, including lesion topography and extent and severity of strategic and global cerebral tissue injury, and cognition in carotid artery disease (CAD).

Materials and Methods

All participants gave written informed consent to undergo brain magnetic resonance imaging and the Addenbrooke’s Cognitive Examination–Revised. One hundred eight patients with symptomatic CAD but no dementia were included, and a score less than 82 represented cognitive impairment. Group comparison and interrelations between global cognitive and fluency performance, lesion topography, and ultrastructural damage were assessed with voxel-based statistics. Associations between cognition, medial temporal lobe atrophy (MTA), lesion volumes, and global white matter ultrastructural damage indexed as increased mean diffusivity were tested with regression analysis by controlling for age. Diagnostic accuracy of imaging markers selected from a multivariate prediction model was tested with receiver operating characteristic analysis.

Results

Cognitively impaired patients (n = 53 [49.1%], classified as having probable vascular cognitive disorder) were older than nonimpaired patients (P = .027) and had more frequent MTA (P < .001), more cortical infarctions (P = .016), and larger volumes of acute (P = .028) and chronic (P = .009) subcortical ischemic lesions. Lesion volumes did not correlate with global cognitive performance (lacunar infarctions, P = .060; acute lesions, P = .088; chronic subcortical ischemic lesions, P = .085). In contrast, cognitive performance correlated with presence of chronic ischemic lesions within the interhemispheric tracts and thalamic radiation (P < .05, false discovery rate corrected). Skeleton mean diffusivity showed the closest correlation with cognition (R² = 0.311, P < .001) and promising diagnostic accuracy for vascular cognitive disorder (area under the curve, 0.82 [95% confidence interval: 0.75, 0.90]). Findings were confirmed in subjects with a low risk of preclinical Alzheimer disease indexed by the absence of MTA (n = 85).

Conclusion

Subcortical white matter ischemic lesion locations and severity of ultrastructural tract damage contribute to cognitive impairment in symptomatic CAD, which suggests that subcortical disconnection within large-scale cognitive neural networks is a key mechanism of vascular cognitive disorder.

Online supplemental material is available for this article.

Can Neurological Biomarkers of Brain Impairment Be Used to Predict Poststroke Motor Recovery? A Systematic Review

Background There is growing interest to establish recovery biomarkers, especially neurological biomarkers, in order to develop new therapies and prediction models for the promotion of stroke rehabilitation and recovery. However, there is no consensus among the neurorehabilitation community about which biomarker(s) have the highest predictive value for motor recovery. Objective To review the evidence and determine which neurological biomarker(s) meet the high evidence quality criteria for use in predicting motor recovery. Methods We searched databases for prognostic neuroimaging/neurophysiological studies. Methodological quality of each study was assessed using a previously employed comprehensive 15-item rating system. Furthermore, we used the GRADE approach and ranked the overall evidence quality for each category of neurologic biomarker. Results Seventy-one articles met our inclusion criteria; 5 categories of neurologic biomarkers were identified: diffusion tensor imaging (DTI), transcranial magnetic stimulation (TMS), functional magnetic resonance imaging (fMRI), conventional structural MRI (sMRI), and a combination of these biomarkers. Most studies were conducted with individuals after ischemic stroke in the acute and/or subacute stage (~70%). Less than one-third of the studies (21/71) were assessed with satisfactory methodological quality (80% or more of total quality score). Conventional structural MRI and the combination biomarker categories ranked "high" in overall evidence quality. Conclusions There were 3 prevalent methodological limitations: (a) lack of cross-validation, (b) lack of minimal clinically important difference (MCID) for motor outcomes, and (c) small sample size. More high-quality studies are needed to establish which neurological biomarkers are the best predictors of motor recovery after stroke. Finally, the quarter-century old methodological quality tool used here should be updated by inclusion of more contemporary methods and statistical approaches.

Individual prediction of chronic motor outcome in the acute post-stroke stage: Behavioral parameters versus functional imaging

Several neurobiological factors have been found to correlate with functional recovery after brain lesions. However, predicting the individual potential of recovery remains difficult. Here we used multivariate support vector machine (SVM) classification to explore the prognostic value of functional magnetic resonance imaging (fMRI) to predict individual motor outcome at 4-6 months post-stroke. To this end, 21 first-ever stroke patients with hand motor deficits participated in an fMRI hand motor task in the first few days post-stroke. Motor impairment was quantified assessing grip force and the Action Research Arm Test. Linear SVM classifiers were trained to predict good versus poor motor outcome of unseen new patients. We found that fMRI activity acquired in the first week post-stroke correctly predicted the outcome for 86% of all patients. In contrast, the concurrent assessment of motor function provided 76% accuracy with low sensitivity (<60%). Furthermore, the outcome of patients with initially moderate impairment and high outcome variability could not be predicted based on motor tests. In contrast, fMRI provided 87.5% prediction accuracy in these patients. Classifications were driven by activity in ipsilesional motor areas and contralesional cerebellum. The accuracy of subacute fMRI data (two weeks post-stroke), age, time post-stroke, lesion volume, and location were at 50%-chance-level. In conclusion, multivariate decoding of fMRI data with SVM early after stroke enables a robust prediction of motor recovery. The potential for recovery is influenced by the initial dysfunction of the active motor system, particularly in those patients whose outcome cannot be predicted by behavioral tests.

Multiclass Support Vector Machine-Based Lesion Mapping Predicts Functional Outcome in Ischemic Stroke Patients

PURPOSE

The aim of this study was to investigate if ischemic stroke final infarction volume and location can be used to predict the associated functional outcome using a multi-class support vector machine (SVM).

MATERIAL AND METHODS

Sixty-eight follow-up MR FLAIR datasets of ischemic stroke patients with known modified Rankin Scale (mRS) functional outcome after 30 days were used. The infarct regions were segmented and used to calculate the percentage of lesioned voxels in the predefined MNI, Harvard-Oxford cortical and subcortical atlas regions as well as using four problem-specific VOIs, which were identified from the database using voxel-based lesion symptom mapping. An overall of 12 SVM classification models for predicting the corresponding mRS score were generated using the lesion overlap values from the different brain region definitions, stroke laterality information, and the optional parameters infarct volume, admission NIHSS, and patient age.

RESULTS

Leave-one-out cross validations revealed that including information about the stroke location in terms of lesion overlap measurements led to improved mRS prediction results compared to classification models not utilizing the stroke location information. Furthermore, integration of the optional features led to improved mRS prediction results in all cases tested. The problem-specific brain regions and additional integration of the optional features led to the best mRS predictions with a precise multi-value mRS prediction accuracy of 56%, sliding window multi-value mRS prediction accuracy (mRS±1) of 82%, and binary mRS (0-2 vs. 3-5) prediction accuracy of 85%.

CONCLUSION

Therefore, a graded SVM-based functional stroke outcome prediction using the problem-specific brain regions for lesion overlap quantification leads to promising results but needs to be further validated using an independent database to rule out a potential methodical bias and overfitting effects. The prediction of the graded mRS functional outcome could be a valuable tool if combined with voxel-wise tissue outcome predictions based on multi-parametric datasets acquired at the acute phase.

Contribution and additional impact of imaging to the SPAN-100 score

BACKGROUND AND PURPOSE

Stroke Prognostication by Using Age and NIHSS score (SPAN-100 index) facilitates stroke outcomes. We assessed imaging markers associated with the SPAN-100 index and their additional impact on outcome determination.

MATERIALS AND METHODS

Of 273 consecutive patients with acute ischemic stroke (<4.5 hours), 55 were characterized as SPAN-100-positive (age +NIHSS score ≥ 100). A comprehensive imaging review evaluated differences, using the presence of the hyperattenuated vessel sign, ASPECTS, clot burden score, collateral score, CBV, CBF, and MTT. The primary outcome assessed was favorable outcome (mRS ≤ 2). Secondary outcomes included recanalization, lack of neurologic improvement, and hemorrhagic transformation. Uni- and multivariate analyses assessed factors associated with favorable outcome. Area under the curve evaluated predictors of favorable clinical outcome.

RESULTS

Compared with the SPAN-100-negative group, the SPAN-100-positive group (55/273; 20%) demonstrated larger CBVs (<0.001), poorer collaterals (P < .001), and increased hemorrhagic transformation rates (56.0% versus 36%, P = .02) despite earlier time to rtPA (P = .03). Favorable outcome was less common among patients with SPAN-100-positive compared with SPAN-100-negative (10.9% versus 42.2%; P < .001). Multivariate regression revealed poorer outcome for SPAN-100-positive (OR = 0.17; 95% CI, 0.06-0.38; P = .001), clot burden score (OR = 1.14; 95% CI, 1.05-1.25; P < .001), and CBV (OR = 0.58; 95% CI, 0.46-0.72; P = .001). The addition of the clot burden score and CBV improved the predictive value of SPAN-100 alone for favorable outcome from 60% to 68% and 74%, respectively.

CONCLUSIONS

SPAN-100-positivity predicts a lower likelihood of favorable outcome and increased hemorrhagic transformation. CBV and clot burden score contribute to poorer outcomes among high-risk patients and improve stroke-outcome prediction.

Automated detection of brain abnormalities in neonatal hypoxia ischemic injury from MR images

We compared the efficacy of three automated brain injury detection methods, namely symmetry-integrated region growing (SIRG), hierarchical region splitting (HRS) and modified watershed segmentation (MWS) in human and animal magnetic resonance imaging (MRI) datasets for the detection of hypoxic ischemic injuries (HIIs). Diffusion weighted imaging (DWI, 1.5T) data from neonatal arterial ischemic stroke (AIS) patients, as well as T2-weighted imaging (T2WI, 11.7T, 4.7T) at seven different time-points (1, 4, 7, 10, 17, 24 and 31 days post HII) in rat-pup model of hypoxic ischemic injury were used to assess the temporal efficacy of our computational approaches. Sensitivity, specificity, and similarity were used as performance metrics based on manual ('gold standard') injury detection to quantify comparisons. When compared to the manual gold standard, automated injury location results from SIRG performed the best in 62% of the data, while 29% for HRS and 9% for MWS. Injury severity detection revealed that SIRG performed the best in 67% cases while 33% for HRS. Prior information is required by HRS and MWS, but not by SIRG. However, SIRG is sensitive to parameter-tuning, while HRS and MWS are not. Among these methods, SIRG performs the best in detecting lesion volumes; HRS is the most robust, while MWS lags behind in both respects.

A multimodal approach to understanding motor impairment and disability after stroke

Many different measures have been found to be related to behavioral outcome after stroke. Preclinical studies emphasize the importance of brain injury and neural function. However, the measures most important to human outcomes remain uncertain, in part because studies often examine one measure at a time or enroll only mildly impaired patients. The current study addressed this by performing multimodal evaluation in a heterogeneous population. Patients (n = 36) with stable arm paresis 3-6 months post-stroke were assessed across 6 categories of measures related to stroke outcome: demographics/medical history, cognitive/mood status, genetics, neurophysiology, brain injury, and cortical function. Multivariate modeling identified measures independently related to an impairment-based outcome (arm Fugl-Meyer motor score). Analyses were repeated (1) identifying measures related to disability (modified Rankin Scale score), describing independence in daily functions and (2) using only patients with mild deficits. Across patients, greater impairment was related to measures of injury (reduced corticospinal tract integrity) and neurophysiology (absence of motor evoked potential). In contrast, (1) greater disability was related to greater injury and poorer cognitive status (MMSE score) and (2) among patients with mild deficits, greater impairment was related to cortical function (greater contralesional motor/premotor cortex activation). Impairment after stroke is most related to injury and neurophysiology, consistent with preclinical studies. These relationships vary according to the patient subgroup or the behavioral endpoint studied. One potential implication of these results is that choice of biomarker or stratifying variable in a clinical stroke study might vary according to patient characteristics.

Connectivity-based approaches in stroke and recovery of function

After focal damage, cerebral networks reorganise their structural and functional anatomy to compensate for both the lesion itself and remote effects. Novel developments in the analysis of functional neuroimaging data enable us to assess in vivo the specific contributions of individual brain areas to recovery of function and the effect of treatment on cortical reorganisation. Connectivity analyses can be used to investigate the effect of stroke on cerebral networks, and help us to understand why some patients make a better recovery than others. This systems-level view also provides insights into how neuromodulatory interventions might target pathological network configurations associated with incomplete recovery. In the future, such analyses of connectivity could help to optimise treatment regimens based on the individual network pathology underlying a particular neurological deficit, thereby opening the way for stratification of patients based on the possible response to an intervention.

Leukoaraiosis predicts cortical infarct volume after distal middle cerebral artery occlusion

BACKGROUND AND PURPOSE

Leukoaraiosis (LA) predominantly affects the subcortical white matter, but mounting evidence suggests an association with cortical microvascular dysfunction and potentially decreased cortical ischemic tolerance. Thus, we sought to assess whether preexisting LA is predictive of the cortical infarct volume after middle cerebral artery branch occlusion and whether it relates to a worse outcome.

METHODS

We analyzed data from 117 consecutive patients with middle cerebral artery branch occlusion as documented by admission computed tomography angiography. Baseline clinical, laboratory, and outcome data, as well as final cortical infarct volumes, were retrospectively analyzed from a prospectively collected database. LA severity was assessed on admission computed tomography using the van Swieten scale grading the supratentorial white matter hypoattenuation. Infarct volume predicting a favorable 90-day outcome (modified Rankin Scale score≤2) was determined by receiver operating characteristic curves. Multivariable linear and logistic regression analyses were used to identify independent predictors of the final infarct volume and outcome.

RESULTS

Receiver operating characteristic curve analyses indicated that a final infarct volume of ≤27 mL best predicted a favorable 90-day outcome. Severe LA (odds ratio, 11.231; 95% confidence interval, 2.526-49.926; P=0.001) was independently associated with infarct volume>27 mL. Severe LA (odds ratio, 3.074; 95% confidence interval, 1.055-8.961; P=0.040) and infarct volume>27 mL (odds ratio, 9.156; 95% confidence interval, 3.191-26.270; P<0.001) were independent predictors of a poor 90-day outcome (modified Rankin Scale, 3-6).

CONCLUSIONS

The presence of severe, subcortical LA contributes to larger cortical infarct volumes and worse functional outcomes adding to the notion that the brain is negatively affected beyond LA's macroscopic boundaries.

[Multimodal imaging protocols and their predictive role in acute stroke functional outcome]

Brain imaging plays a central role in the assessment of patients with acute ischemic stroke. Within a few minutes, modern multimodal imaging protocols can provide one with comprehensive information about prognosis, management, and outcome of the disease, and may detect changes in the intracranial structures reflecting severity of the ischemic injury depicted by four Ps: parenchyma (of the brain), pipes (i.e., the cerebral blood vessels), penumbra, and permeability (of the blood brain barrier). In this article, we have reviewed neuroradiological predictors of stroke functional outcome in the light of the aforementioned four Ps.

How Useful is Imaging in Predicting Outcomes in Stroke Rehabilitation?

Neuroimaging plays an important role In acute stroke diagnosis and management, but It Is not routinely used In rehabilitation settings. Incorporating Imaging Information In rehabilitation planning may eventually translate to better outcomes after stroke. Here we review the prediction of outcomes after stroke using magnetic resonance imaging. There are clear and specific relationships between the anatomy of the stroke lesion and impairments at the time of scanning, and at later time points in recovery. However, most studies demonstrate these relationships in groups of patients at the chronic stage. In order to be useful for rehabilitation, neuroimaging needs to provide prognostic information for individual patients at a much earlier stage. Recent studies have used diffusion tensor imaging and functional neuroimaging to address this, with promising results. Combining neuroimaging with clinical and neurophysiological assessments may also be useful. Future work in this area may support the tailoring of rehabilitation for individual patients based on their capacity for neural reorganization and recovery.

Predicting Activities after Stroke: What is Clinically Relevant?

Knowledge about factors that determine the final outcome after stroke is important for early stroke management, rehabilitation goals, and discharge planning. This narrative review provides an overview of current knowledge about the prediction of activities after stroke. We reviewed the pattern of stroke recovery for functions and activities, the impact of spontaneous recovery on activities, and the measurement of improvement in general. We explored the activities profiles during the chronic phase and predictors for activities of daily living independence after stroke, and finally, we discussed where to from here? Mathematical regularities explain the nonlinear patterns of recovery, making the outcome of activities of daily living highly predictable. Initial severity of disability and extent of improvement observed within the first weeks poststroke are important indicators of the outcome at six-months. The sequence of progress in activities is almost fixed in time. Studies showed that most motor recovery is almost completed within 10 weeks poststroke. On average, stroke recovery plateaus three- to six-months after onset. Strong evidence was found that age and scores on scales assessing severity of neurological deficits in the early poststroke phase are strongly associated with the final basic activities of daily living outcome after three-months poststroke. The validated prediction models using simple algorithms, such as National Institutes of Health Stroke Scale or Barthel Index, need to be implemented in rehabilitation services and used for stratifying stroke patients in trials. Future studies should investigate the accuracy of dynamic models that includes time poststroke to optimize the application of prediction rules in individuals with stroke.

Clinical-radiological severity mismatch phenomenon: patients with severe neurological deficits without matching infarction on computed tomographic scan

OBJECTIVE

The objective was to determine the long-term outcome of patients with severe persistent neurological deficits without a large infarction on computed tomographic (CT) scan.

METHODS

We analyzed the prospectively collected data as part of the randomized, placebo controlled trial in patients with ischemic stroke presenting within 3 hours of symptom onset. Volume of infarction was measured from CT scan acquired at 3 months. Favorable outcome defined by no significant or slight disability on a modified Rankin scale at 12 months. We determined the outcome of patients with National Institutes of Health Stroke Scale score (NIHSS score) ≥ 10 at 24 hours.

RESULTS

Of the 277 patients with NIHSS score ≥ 10 at 24 hours, 88 (32%) met the criteria of clinical-radiological severity mismatch. Compared with patients with NIHSS score ≥ 10 with infarct volume ≥ 20 cc, the patients with NIHSS score ≥ 10 and infarct volume <20 cc were older but there were no differences in the gender, race or vascular risk factors. Patients with clinical-radiological severity mismatch were more likely to have a favorable outcome at 12 months compared with those without mismatch (odd ratio 4.3, 95% confidence interval 1.5-12.6, P = .0063) after adjusting for potential confounders.

CONCLUSIONS

We observed that approximately one-fourth of patients with severe neurological deficits have clinical-radiological severity mismatch. Such patients appear to have a high rate of favorable outcomes at 1 year.

Automated core-penumbra quantification in neonatal ischemic brain injury

Neonatal hypoxic-ischemic brain injury (HII) and arterial ischemic stroke (AIS) result in irreversibly injured (core) and salvageable (penumbral) tissue regions. Identification and reliable quantification of salvageable tissue is pivotal to any effective and safe intervention. Magnetic resonance imaging (MRI) is the current standard to distinguish core from penumbra using diffusion-perfusion mismatch (DPM). However, subtle MR signal variations between core-penumbral regions make their visual delineation difficult. We hypothesized that computational analysis of MRI data provides a more accurate assessment of core and penumbral tissue evolution in HII/AIS. We used two neonatal rat-pup models of HII/AIS (unilateral and global hypoxic-ischemia) and clinical data sets from neonates with AIS to test our noninvasive, automated computational approach, Hierarchical Region Splitting (HRS), to detect and quantify ischemic core-penumbra using only a single MRI modality (T2- or diffusion-weighted imaging, T2WI/DWI). We also validated our approach by comparing core-penumbral images (from HRS) to DPM with immunohistochemical validation of HII tissues. Our translational and clinical data results showed that HRS could accurately and reliably distinguish the ischemic core from penumbra and their spatiotemporal evolution, which may aid in the vetting and execution of effective therapeutic interventions as well as patient selection.