Excessive White Matter Hyperintensity Increases Susceptibility to Poor Functional Outcomes After Acute Ischemic Stroke

White Matter Hyperintensities as a Predictor of Aphasia Recovery

OBJECTIVE

To examine the relation between baseline white matter hyperintensities (WMH) and change in naming, content production, and efficiency after treatment in subacute aphasia. We hypothesized that more severe baseline WMH would result in less improvement with treatment.

DESIGN

Retrospective analysis of a cohort from a double-blind randomized controlled trial (RCT).

SETTING

Outpatient clinical setting or participant home.

PARTICIPANTS

We retrospectively reviewed imaging and behavioral data for 52 participants with subacute aphasia due to left-hemisphere ischemic stroke enrolled in the RCT. RCT inclusion criteria: English proficiency, normal/corrected-to-normal hearing/vision, and no history of neurologic conditions other than the stroke resulting aphasia. One participant with a chronic right-hemisphere lesion was retained as she presented with no residual deficits on neurologic examination. Individuals with scalp sensitivities or on medications that lower seizure threshold or any N-methyl-D-aspartate (NMDA) antagonists were excluded. Of the 52 participants, for this analysis, 2 were excluded for not having a magnetic resonance imaging, and 7 were excluded for not participating in treatment or pre/post assessment for at least 1 outcome, resulting in final sample of 43 participants (20 women sex, M [SD] age=64.4 [11.9] and M [SD] education=14.9 [3.1] years).

INTERVENTIONS

Participants received 15 sessions (2-3 times/week) of computerized lexical-semantic (ie, verification) treatment with [sham/active] transcranial direct current stimulation (tDCS). Sessions were approximately 45 minutes each (tDCS for first 20 minutes).

MAIN OUTCOME MEASURES

Naming accuracy, content units (CUs, a measure of semantically accurate production), and efficiency (ie, syllables/CU) on a picture description task.

RESULTS

Periventricular WMH severity was independently associated with recovery in picture naming for the active tDCS group. Deep WMH severity was associated with recovery for CU production for the sham tDCS group.

CONCLUSION

Baseline periventricular and deep WMH, among other factors, may be an important consideration for prognosis and treatment planning, especially when considered in conjunction with tDCS treatment.

Aldosterone is Associated With New-onset Cerebrovascular Events in Patients With Hypertension and White Matter Lesions: A Cohort Study

OBJECTIVE

White matter lesions (WMLs) increase the risk of stroke, stroke recurrence, and death. Higher plasma aldosterone concentration (PAC) increases the risk of stroke, acute myocardial infarction, and hypertension. The objective is to evaluate the relationship between PAC and cerebrovascular events in patients with hypertension and WMLs.

METHODS

We conducted a retrospective cohort study that included 1041 participants hospitalized. The outcome was new-onset cerebrovascular events including intracerebral hemorrhage and stroke. A Cox regression model was used to evaluate the relationship between baseline PAC and the risk of cerebrovascular events.

RESULTS

The mean age of participants was 60.9 ± 10.2 years and 565 (53.4%) were males. The median follow-up duration was 42 months (interquartile range: 25-67), and 92 patients experienced new-onset cerebrovascular events. In a multivariate-adjusted model, with PAC as a continuous variable, higher PAC increased the risk of cerebrovascular events; patient risk increased per 1 (hazard ratio [HR: 1.03], 95% confidence interval [CI]: 1.01-1.06, P < .01), per 5 (HR: 1.17, 95% CI: 1.06-1.31, P < .01), and per 10 ng/dL (HR: 1.41, 95%: 1.14-1.75, P < .01) increase in PAC. When PAC was expressed as a categorical variable (quartile: Q1-Q4), patients in Q4 (HR: 2.12, 95% CI: 1.18-3.79, P < .05) exhibited an increased risk of cerebrovascular events compared to Q1. Restrictive spline regression showed a linear association between PAC and the risk of new-onset cerebrovascular events after adjusting for all possible variables.

CONCLUSIONS

Our study identified a linear association between PAC and the risk of new-onset cerebrovascular events in patients with hypertension and WMLs.

Dopaminergic mesolimbic structural reserve is positively linked to better outcome after severe stroke

The concept of brain reserve capacity has emerged in stroke recovery research in recent years. Imaging-based biomarkers of brain health have helped to better understand outcome variability in clinical cohorts. Still, outcome inferences are far from being satisfactory, particularly in patients with severe initial deficits. Neurorehabilitation after stroke is a complex process, comprising adaption and learning processes, which, on their part, are critically influenced by motivational and reward-related cognitive processes. Amongst others, dopaminergic neurotransmission is a key contributor to these mechanisms. The question arises, whether the amount of structural reserve capacity in the dopaminergic system might inform about outcome variability after severe stroke. For this purpose, this study analysed imaging and clinical data of 42 severely impaired acute stroke patients. Brain volumetry was performed within the first 2 weeks after the event using the Computational Anatomy Toolbox CAT12, grey matter volume estimates were collected for seven key areas of the human dopaminergic system along the mesocortical, mesolimbic and nigrostriatal pathways. Ordinal logistic regression models related regional volumes to the functional outcome, operationalized by the modified Rankin Scale, obtained 3-6 months after stroke. Models were adjusted for age, lesion volume and initial impairment. The main finding was that larger volumes of the amygdala and the nucleus accumbens at baseline were positively associated with a more favourable outcome. These data suggest a link between the structural state of mesolimbic key areas contributing to motor learning, motivational and reward-related brain networks and potentially the success of neurorehabilitation. They might also provide novel evidence to reconsider dopaminergic interventions particularly in severely impaired stroke patients to enhance recovery after stroke.

Prolonged myelin deficits contribute to neuron loss and functional impairments after ischaemic stroke

Ischaemic stroke causes neuron loss and long-term functional deficits. Unfortunately, effective approaches to preserving neurons and promoting functional recovery remain unavailable. Oligodendrocytes, the myelinating cells in the CNS, are susceptible to oxygen and nutrition deprivation and undergo degeneration after ischaemic stroke. Technically, new oligodendrocytes and myelin can be generated by the differentiation of oligodendrocyte precursor cells (OPCs). However, myelin dynamics and their functional significance after ischaemic stroke remain poorly understood. Here, we report numerous denuded axons accompanied by decreased neuron density in sections from ischaemic stroke lesions in human brain, suggesting that neuron loss correlates with myelin deficits in these lesions. To investigate the longitudinal changes in myelin dynamics after stroke, we labelled and traced pre-existing and newly-formed myelin, respectively, using cell-specific genetic approaches. Our results indicated massive oligodendrocyte death and myelin loss 2 weeks after stroke in the transient middle cerebral artery occlusion (tMCAO) mouse model. In contrast, myelin regeneration remained insufficient 4 and 8 weeks post-stroke. Notably, neuronal loss and functional impairments worsened in aged brains, and new myelin generation was diminished. To analyse the causal relationship between remyelination and neuron survival, we manipulated myelinogenesis by conditional deletion of Olig2 (a positive regulator) or muscarinic receptor 1 (M1R, a negative regulator) in OPCs. Deleting Olig2 inhibited remyelination, reducing neuron survival and functional recovery after tMCAO. Conversely, enhancing remyelination by M1R conditional knockout or treatment with the pro-myelination drug clemastine after tMCAO preserved white matter integrity and neuronal survival, accelerating functional recovery. Together, our findings demonstrate that enhancing myelinogenesis is a promising strategy to preserve neurons and promote functional recovery after ischaemic stroke.

Scaling behaviours of deep learning and linear algorithms for the prediction of stroke severity

Deep learning has allowed for remarkable progress in many medical scenarios. Deep learning prediction models often require 105-107 examples. It is currently unknown whether deep learning can also enhance predictions of symptoms post-stroke in real-world samples of stroke patients that are often several magnitudes smaller. Such stroke outcome predictions however could be particularly instrumental in guiding acute clinical and rehabilitation care decisions. We here compared the capacities of classically used linear and novel deep learning algorithms in their prediction of stroke severity. Our analyses relied on a total of 1430 patients assembled from the MRI-Genetics Interface Exploration collaboration and a Massachusetts General Hospital-based study. The outcome of interest was National Institutes of Health Stroke Scale-based stroke severity in the acute phase after ischaemic stroke onset, which we predict by means of MRI-derived lesion location. We automatically derived lesion segmentations from diffusion-weighted clinical MRI scans, performed spatial normalization and included a principal component analysis step, retaining 95% of the variance of the original data. We then repeatedly separated a train, validation and test set to investigate the effects of sample size; we subsampled the train set to 100, 300 and 900 and trained the algorithms to predict the stroke severity score for each sample size with regularized linear regression and an eight-layered neural network. We selected hyperparameters on the validation set. We evaluated model performance based on the explained variance (R2) in the test set. While linear regression performed significantly better for a sample size of 100 patients, deep learning started to significantly outperform linear regression when trained on 900 patients. Average prediction performance improved by ∼20% when increasing the sample size 9× [maximum for 100 patients: 0.279 ± 0.005 (R2, 95% confidence interval), 900 patients: 0.337 ± 0.006]. In summary, for sample sizes of 900 patients, deep learning showed a higher prediction performance than typically employed linear methods. These findings suggest the existence of non-linear relationships between lesion location and stroke severity that can be utilized for an improved prediction performance for larger sample sizes.

Neuroimaging markers of patient-reported outcome measures in acute ischemic stroke

Objectives

To determine the relationship between patient-reported outcome measures (PROMs) and volumetric imaging markers in acute ischemic stroke (AIS).

Patients and Methods

Patients presenting at Massachusetts General Hospital between February 14, 2017 and February 5, 2020 with a confirmed AIS by MRI were eligible and underwent a telephone interview including PROM-10 questionnaires 3-15 months after stroke. White matter hyperintensity (VWMH) and brain volumes (VBrain) were automatically determined using admission clinical MRI. Stroke lesions were manually segmented and volumes calculated (VLesion). Multivariable and ordinal regression analyses were performed to identify associations between global and PROM-10 subscores with brain volumetrics and clinical variables.

Results

Utilizing data from 167 patients (mean age: 64.7; 41.9% female), higher VWMH was associated with worse global physical (β=-0.6), global mental (β=-0.65), physical health (OR=0.68), social satisfaction (OR=0.66), fatigue (OR=0.69) and social activities (OR=0.59) scores. Higher VLesion was associated with poorer global mental (β=-0.79), mental health (OR=0.68), physical (OR=0.66) and social activities (OR=0.55), and emotional distress (OR=0.68) scores. Higher VBrain was linked to better global mental (β=0.93), global physical (β=0.79), mental health (OR=1.54) and physical activities (OR=1.72) scores.

Conclusions

Neuroimaging biomarkers were significantly associated with PROMs, where higher VWMH and VLesion led to worse outcome, while higher VBrain was protective. The inclusion of neuroimaging analyses and PROMs in routine assessment provides enhanced understanding of post-stroke outcomes.

Bystanders or not? Microglia and lymphocytes in aging and stroke

As the average age of the world population increases, more people will face debilitating aging-associated conditions, including dementia and stroke. Not only does the incidence of these conditions increase with age, but the recovery afterward is often worse in older patients. Researchers and health professionals must unveil and understand the factors behind age-associated diseases to develop a therapy for older patients. Aging causes profound changes in the immune system including the activation of microglia in the brain. Activated microglia promote T lymphocyte transmigration leading to an increase in neuroinflammation, white matter damage, and cognitive impairment in both older humans and rodents. The presence of T and B lymphocytes is observed in the aged brain and correlates with worse stroke outcomes. Preclinical strategies in stroke target either microglia or the lymphocytes or the communications between them to promote functional recovery in aged subjects. In this review, we examine the role of the microglia and T and B lymphocytes in aging and how they contribute to cognitive impairment. Additionally, we provide an important update on the contribution of these cells and their interactions in preclinical aged stroke.

Radiomics-Derived Brain Age Predicts Functional Outcome After Acute Ischemic Stroke

BACKGROUND AND OBJECTIVES

While chronological age is one of the most influential determinants of poststroke outcomes, little is known of the impact of neuroimaging-derived biological "brain age." We hypothesized that radiomics analyses of T2-FLAIR images texture would provide brain age estimates and that advanced brain age of patients with stroke will be associated with cardiovascular risk factors and worse functional outcomes.

METHODS

We extracted radiomics from T2-FLAIR images acquired during acute stroke clinical evaluation. Brain age was determined from brain parenchyma radiomics using an ElasticNet linear regression model. Subsequently, relative brain age (RBA), which expresses brain age in comparison with chronological age-matched peers, was estimated. Finally, we built a linear regression model of RBA using clinical cardiovascular characteristics as inputs and a logistic regression model of favorable functional outcomes taking RBA as input.

RESULTS

We reviewed 4,163 patients from a large multisite ischemic stroke cohort (mean age = 62.8 years, 42.0% female patients). T2-FLAIR radiomics predicted chronological ages (mean absolute error = 6.9 years, r = 0.81). After adjustment for covariates, RBA was higher and therefore described older-appearing brains in patients with hypertension, diabetes mellitus, a history of smoking, and a history of a prior stroke. In multivariate analyses, age, RBA, NIHSS, and a history of prior stroke were all significantly associated with functional outcome (respective adjusted odds ratios: 0.58, 0.76, 0.48, 0.55; all p-values < 0.001). Moreover, the negative effect of RBA on outcome was especially pronounced in minor strokes.

DISCUSSION

T2-FLAIR radiomics can be used to predict brain age and derive RBA. Older-appearing brains, characterized by a higher RBA, reflect cardiovascular risk factor accumulation and are linked to worse outcomes after stroke.

Prognostic Value of Combined Radiomic Features from Follow-Up DWI and T2-FLAIR in Acute Ischemic Stroke

The biological pathways involved in lesion formation after an acute ischemic stroke (AIS) are poorly understood. Despite successful reperfusion treatment, up to two thirds of patients with large vessel occlusion remain functionally dependent. Imaging characteristics extracted from DWI and T2-FLAIR follow-up MR sequences could aid in providing a better understanding of the lesion constituents. We built a fully automated pipeline based on a tree ensemble machine learning model to predict poor long-term functional outcome in patients from the MR CLEAN-NO IV trial. Several feature sets were compared, considering only imaging, only clinical, or both types of features. Nested cross-validation with grid search and a feature selection procedure based on SHapley Additive exPlanations (SHAP) was used to train and validate the models. Considering features from both imaging modalities in combination with clinical characteristics led to the best prognostic model (AUC = 0.85, 95%CI [0.81, 0.89]). Moreover, SHAP values showed that imaging features from both sequences have a relevant impact on the final classification, with texture heterogeneity being the most predictive imaging biomarker. This study suggests the prognostic value of both DWI and T2-FLAIR follow-up sequences for AIS patients. If combined with clinical characteristics, they could lead to better understanding of lesion pathophysiology and improved long-term functional outcome prediction.

Cortical thickness of contralesional cortices positively relates to future outcome after severe stroke

Imaging studies have evidenced that contralesional cortices are involved in recovery after motor stroke. Cortical thickness (CT) analysis has proven its potential to capture the changes of cortical anatomy, which have been related to recovery and treatment gains under therapy. An open question is whether CT obtained in the acute phase after stroke might inform correlational models to explain outcome variability. Data of 38 severely impaired (median NIH Stroke Scale 9, interquartile range: 6-13) acute stroke patients of 2 independent cohorts were reanalyzed. Structural imaging data were processed via the FreeSurfer pipeline to quantify regional CT of the contralesional hemisphere. Ordinal logistic regression models were fit to relate CT to modified Rankin Scale as an established measure of global disability after 3-6 months, adjusted for the initial deficit, lesion volume, and age. The data show that CT of contralesional cortices, such as the precentral gyrus, the superior frontal sulcus, and temporal and cingulate cortices, positively relates to the outcome after stroke. This work shows that the baseline cortical anatomy of selected contralesional cortices can explain the outcome variability after severe stroke, which further contributes to the concept of structural brain reserve with respect to contralesional cortices to promote recovery.

Association of Stroke Lesion Pattern and White Matter Hyperintensity Burden With Stroke Severity and Outcome

BACKGROUND AND OBJECTIVES

To examine whether high white matter hyperintensity (WMH) burden is associated with greater stroke severity and worse functional outcomes in lesion pattern-specific ways.

METHODS

MR neuroimaging and NIH Stroke Scale data at index stroke and the modified Rankin Scale (mRS) score at 3-6 months after stroke were obtained from the MRI-Genetics Interface Exploration study of patients with acute ischemic stroke (AIS). Individual WMH volume was automatically derived from fluid-attenuated inversion recovery images. Stroke lesions were automatically segmented from diffusion-weighted imaging (DWI) images, parcellated into atlas-defined brain regions and further condensed to 10 lesion patterns via machine learning-based dimensionality reduction. Stroke lesion effects on AIS severity and unfavorable outcomes (mRS score >2) were modeled within purpose-built Bayesian linear and logistic regression frameworks. Interaction effects between stroke lesions and a high vs low WMH burden were integrated via hierarchical model structures. Models were adjusted for age, age2, sex, total DWI lesion and WMH volumes, and comorbidities. Data were split into derivation and validation cohorts.

RESULTS

A total of 928 patients with AIS contributed to acute stroke severity analyses (age: 64.8 [14.5] years, 40% women) and 698 patients to long-term functional outcome analyses (age: 65.9 [14.7] years, 41% women). Stroke severity was mainly explained by lesions focused on bilateral subcortical and left hemispherically pronounced cortical regions across patients with both a high and low WMH burden. Lesions centered on left-hemispheric insular, opercular, and inferior frontal regions and lesions affecting right-hemispheric temporoparietal regions had more pronounced effects on stroke severity in case of high compared with low WMH burden. Unfavorable outcomes were predominantly explained by lesions in bilateral subcortical regions. In difference to the lesion location-specific WMH effects on stroke severity, higher WMH burden increased the odds of unfavorable outcomes independent of lesion location.

DISCUSSION

Higher WMH burden may be associated with an increased stroke severity in case of stroke lesions involving left-hemispheric insular, opercular, and inferior frontal regions (potentially linked to language functions) and right-hemispheric temporoparietal regions (potentially linked to attention). Our findings suggest that patients with specific constellations of WMH burden and lesion locations may have greater benefits from acute recanalization treatments. Future clinical studies are warranted to systematically assess this assumption and guide more tailored treatment decisions.

Structural cerebellar reserve positively influences outcome after severe stroke

The concept of brain reserve capacity positively influencing the process of recovery after stroke has been continuously developed in recent years. Global measures of brain health have been linked with a favourable outcome. Numerous studies have evidenced that the cerebellum is involved in recovery after stroke. However, it remains an open question whether characteristics of cerebellar anatomy, quantified directly after stroke, might have an impact on subsequent outcome after stroke. Thirty-nine first-ever ischaemic non-cerebellar stroke patients underwent MRI brain imaging early after stroke and longitudinal clinical follow-up. Structural images were used for volumetric analyses of distinct cerebellar regions. Ordinal logistic regression analyses were conducted to associate cerebellar volumes with functional outcome 3-6 months after stroke, operationalized by the modified Rankin Scale. Larger volumes of cerebellar lobules IV, VI, and VIIIB were positively correlated with favourable outcome, independent of the severity of initial impairment, age, and lesion volume (P < 0.01). The total cerebellar volume did not exhibit a significant structure-outcome association. The present study reveals that pre-stroke anatomy of distinct cerebellar lobules involved in motor and cognitive functioning might be linked to outcome after acute non-cerebellar stroke, thereby promoting the emerging concepts of structural brain reserve for recovery processes after stroke.