Cerebral Small Vessel Disease MRI Features Do Not Improve the Prediction of Stroke Outcome

Poststroke cognitive outcome is better accounted for by white matter abnormalities automated segmentation than visual analysis

BACKGROUND AND AIMS

The association between white matter abnormalities (WMA) and cognitive decline previously reported in poststroke patients has been mainly documented using visual scales. However, automated segmentation of WMA provides a precise determination of the volume of WMA. Nonetheless, it is rarely used in the stroke population and its potential advantage over visual scales is still unsettled. The objective of this study was to examine whether automated segmentation of WMA provides a better account than the visual Fazekas and Wahlund scales of the decline in executive functions and processing speed in stroke patients.

METHODS

The analyses were conducted on the 358 patients of the GRECogVASC cohort with an MRI performed at six months poststroke in the Amiens center. WMA were visually analyzed using the Fazekas (subcortical abnormalities) and Wahlund scales. Segmentation was performed using LST (3.0.3). Following preliminary studies to determine the optimal segmentation threshold, we examined the relationship between cognitive status and WMA volume computed at each threshold using receiver operating characteristic (ROC) curves. Finally, we assessed the ability of both Fazekas and Wahlund visual scores and WMA volume to account for cognitive scores by using a bivariate Pearson correlation analysis, comparing correlation coefficients with the Fisher transformation and repeating correlation analysis after adjustment for the lesion volume.

RESULTS

Increasing the threshold led to an underestimation of WMA (P=0.0001) (significant for a threshold ≥0.2) and an improvement in correct rejection of signal changes in the stroke cavity (P=0.02) (significant for a threshold ≤0.5), susceptibility artifacts (P=0.002) (significant for a threshold ≤0.6), and corticospinal degeneration (P=0.03) (significant for a threshold ≤0.5). WMA volume decreased with increasing threshold (P=0.0001). Areas under the curve (AUC) did not differ according to the threshold (processing speed: P=0.85, executive cognitive functions: P=0.7). Correlation coefficients between cognitive scores and WMA were higher for WMA volume than the Fazekas (processing speed: Z=-3.442, P=0.001; executive functions: Z=-2.751, P=0.006) and Wahlund scores (processing speed: Z=-3.615, P=0.0001; executive functions: Z=-2.769, P=0.006). Adjustment for lesion volume did not alter the correlations with WMA volume (processing speed: r=-0.327 [95%CI: -0.416; -0.223], P=0.0001; executive functions: r=-0.262 [95%CI: -0.363; -0.150], P=0.0001).

CONCLUSION

This study shows that WMA volume assessed by automated segmentation provides a better account of cognitive disorders than visual analysis. This should favor its wider use to refine imaging determinants of poststroke cognitive disorders.

The analysis of association between single features of small vessel disease and stroke outcome shows the independent impact of the number of microbleeds and presence of lacunes

The impact of small vessel disease (SVD) on stroke outcome was investigated either separately for its single features in isolation or for SVD sum score measuring a qualitative (binary) assessment of SVD-lesions. We aimed to investigate which SVD feature independently impacts the most on stroke outcome and to compare the continuous versus binary SVD assessment that reflects pronouncement and presence correspondingly. Patients with a first-ever anterior circulation ischemic stroke were retrospectively investigated. We performed an ordered logistic regression analysis to predict stroke outcome (mRS 3 months, 0-6) using age, stroke severity, and pre-stroke disability as baseline input variables and adding SVD-features (lacunes, microbleeds, enlarged perivascular spaces, white matter hyperintensities) assessed either continuously (model 1) or binary (model 2). The data of 873 patients (age 67.9 ± 15.4, NIHSS 24 h 4.1 ± 4.8) was analyzed. In model 1 with continuous SVD-features, the number of microbleeds was the only independent predictor of stroke outcome in addition to clinical parameters (OR 1.21; 95% CI 1.07-1.37). In model 2 with the binary SVD assessment, only the presence of lacunes independently improved the prediction of stroke outcome (OR 1.48, 1.1-1.99). In a post hoc analysis, both the continuous number of microbleeds and the presence of lacunes were independent significant predictors. Thus, the number of microbleeds evaluated continuously and the presence of lacunes are associated with stroke outcome independent from age, stroke severity, pre-stroke disability and other SVD-features. Whereas the presence of lacunes is adequately represented in SVD sum score, the microbleeds assessment might require another cutoff and/or gradual scoring, when prediction of stroke outcome is needed.

Adaptation of the Concept of Brain Reserve for the Prediction of Stroke Outcome: Proxies, Neural Mechanisms, and Significance for Research

The prediction of stroke outcome is challenging due to the high inter-individual variability in stroke patients. We recently suggested the adaptation of the concept of brain reserve (BR) to improve the prediction of stroke outcome. This concept was initially developed alongside the one for the cognitive reserve for neurodegeneration and forms a valuable theoretical framework to capture high inter-individual variability in stroke patients. In the present work, we suggest and discuss (i) BR-proxies-quantitative brain characteristics at the time stroke occurs (e.g., brain volume, hippocampus volume), and (ii) proxies of brain pathology reducing BR (e.g., brain atrophy, severity of white matter hyperintensities), parameters easily available from a routine MRI examination that might improve the prediction of stroke outcome. Though the influence of these parameters on stroke outcome has been partly reported individually, their independent and combined impact is yet to be determined. Conceptually, BR is a continuous measure determining the amount of brain structure available to mitigate and compensate for stroke damage, thus reflecting individual differences in neural resources and a capacity to maintain performance and recover after stroke. We suggest that stroke outcome might be defined as an interaction between BR at the time stroke occurs and lesion load. BR in stroke can potentially be influenced, e.g., by modifying cardiovascular risk factors. In addition to the potential power of the BR concept in a mechanistic understanding of inter-individual variability in stroke outcome and establishing individualized therapeutic approaches, it might help to strengthen the synergy of preventive measures in stroke, neurodegeneration, and healthy aging.

Small vessel disease burden predicts functional outcomes in patients with acute ischemic stroke using machine learning

AIMS

Our purpose is to assess the role of cerebral small vessel disease (SVD) in prediction models in patients with different subtypes of acute ischemic stroke (AIS).

METHODS

We enrolled 398 small-vessel occlusion (SVO) and 175 large artery atherosclerosis (LAA) AIS patients. Functional outcomes were assessed using the modified Rankin Scale (mRS) at 90 days. MRI was performed to assess white matter hyperintensity (WMH), perivascular space (PVS), lacune, and cerebral microbleed (CMB). Logistic regression (LR) and machine learning (ML) were used to develop predictive models to assess the influences of SVD on the prognosis.

RESULTS

In the feature evaluation of SVO-AIS for different outcomes, the modified total SVD score (Gain: 0.38, 0.28) has the maximum weight, and periventricular WMH (Gain: 0.07, 0.09) was more important than deep WMH (Gain: 0.01, 0.01) in prognosis. In SVO-AIS, SVD performed better than regular clinical data, which is the opposite of LAA-AIS. Among all models, eXtreme gradient boosting (XGBoost) method with optimal index (OI) has the best performance to predict excellent outcome in SVO-AIS. [0.91 (0.84-0.97)].

CONCLUSIONS

Our results revealed that different SVD markers had distinct prognostic weights in AIS patients, and SVD burden alone may accurately predict the SVO-AIS patients' prognosis.

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

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

The Clinical Utility of Leukoaraiosis as a Prognostic Indicator in Ischemic Stroke Patients

Stroke constitutes a major cause of functional disability with increasing prevalence among adult individuals. Thus, it is of great importance for both clinicians and stroke survivors to be provided with a timely and accurate prognostication of functional outcome. A great number of biomarkers capable of yielding useful information regarding stroke patients' recovery propensity have been evaluated so far with leukoaraiosis being among them. Literature research of two databases (MEDLINE and Scopus) was conducted to identify all relevant studies published between 1 January 2012 and 25 June 2022 that dealt with the clinical utility of a current leukoaraiosis as a prognostic indicator following stroke. Only full-text articles published in English language were included. Forty-nine articles have been traced and are included in the present review. Our findings highlight the prognostic value of leukoaraiosis in an acute stroke setting. The assessment of leukoaraiosis with visual rating scales in CT/MRI imaging appears to be able to reliably provide important insight into the recovery potential of stroke survivors, thus significantly enhancing stroke management. Yielding additional information regarding both short- and long-term functional outcome, motor recovery capacity, hemorrhagic transformation, as well as early neurological deterioration following stroke, leukoaraiosis may serve as a valuable prognostic marker poststroke. Thus, leukoaraiosis represents a powerful prognostic tool, the clinical implementation of which is expected to significantly facilitate the individualized management of stroke patients.

Predictors of post-stroke cognitive impairment using acute structural MRI neuroimaging: A systematic review and meta-analysis

BACKGROUND

Stroke survivors are at an increased risk of developing post-stroke cognitive impairment and post-stroke dementia; those at risk could be identified by brain imaging routinely performed at stroke onset.

AIM

This systematic review aimed to identify features which are associated with post-stroke cognitive impairment (including dementia) on magnetic resonance imaging (MRI) performed at stroke diagnosis.

SUMMARY OF REVIEW

We searched the literature from inception to January 2022 and identified 10,284 records. We included studies that performed MRI at the time of stroke (0-30 days after a stroke) and assessed cognitive outcome at least 3 months after stroke. We synthesized findings from 26 papers, comprising 27 stroke-populations (N = 13,114, average age range = 40-80 years, 19-62% female). When data were available, we pooled unadjusted (OR_u) and adjusted (OR_a) odds ratios.We found associations between cognitive outcomes and presence of cerebral atrophy (three studies, N = 453, OR_u = 2.48, 95% CI = 1.15-4.62), presence of microbleeds (two studies, N = 9151, OR_a = 1.36, 95% CI = 1.08-1.70), and increasing severity of white matter hyperintensities (three studies, N = 704, OR_a = 1.26, 95% CI = 1.06-1.49). Increasing cerebral small vessel disease score was associated with cognitive outcome following unadjusted analysis only (two studies, N = 499, OR_u = 1.34, 95%CI = 1.12-1.61; three studies, N = 950, OR_a = 1.23, 95% CI = 0.96-1.57). Associations remained after controlling for pre-stroke cognitive impairment. We did not find associations between other stroke features and cognitive outcome, or there were insufficient data.

CONCLUSION

Acute stroke MRI features may enable healthcare professionals to identify patients at risk of post-stroke cognitive problems. However, there is still substantial uncertainty about the prognostic utility of acute MRI for this.

Cerebral small vessel disease burden and cognitive and functional outcomes after stroke: A multicenter prospective cohort study

INTRODUCTION

It remains unknown whether the global small vessel disease (SVD) burden predicts post-stroke outcomes.

METHODS

In a prospective multicenter study of 666 ischemic and hemorrhagic stroke patients, we quantified magnetic resonance imaging (MRI)-based SVD markers (lacunes, white matter hyperintensities, microbleeds, perivascular spaces) and explored associations with 6- and 12-month cognitive (battery of 15 neuropsychological tests) and functional (modified Rankin scale) outcomes.

RESULTS

A global SVD score (range 0-4) was associated with cognitive impairment; worse performance in executive function, attention, language, and visuospatial ability; and worse functional outcome across a 12-month follow-up. Although the global SVD score did not improve prediction, individual SVD markers, assessed across their severity range, improved the calibration, discrimination, and reclassification of predictive models including demographic, clinical, and other imaging factors.

DISCUSSION

SVD presence and severity are associated with worse cognitive and functional outcomes 12 months after stroke. Assessing SVD severity may aid prognostication for stroke patients.

HIGHLIGHTS

In a multi-center cohort, we explored associations of small vessel disease (SVD) burden with stroke outcomes. SVD burden associates with post-stroke cognitive and functional outcomes. A currently used score of SVD burden does not improve the prediction of poor outcomes. Assessing the severity of SVD lesions adds predictive value beyond known predictors. To add predictive value in assessing SVD in stroke patients, SVD burden scores should integrate lesion severity.

Chronic cerebral infarctions and white matter lesions link to long-term survival after a first ischemic event: A cohort study

BACKGROUND AND PURPOSE

To investigate the association of different phenotypes, count, and locations of chronic covert brain infarctions (CBI) with long-term mortality in patients with first-ever manifest acute ischemic stroke (AIS) or transient ischemic attack (TIA). Additionally, to analyze their potential interaction with white matter hyperintensities (WMH) and predictive value in addition to established mortality scores.

METHODS

Single-center cohort study including consecutive patients with first-ever AIS or TIA with available MRI imaging from January 2015 to December 2017. Blinded raters adjudicated CBI phenotypes and WMH (age-related white matter changes score) according to established definitions. We compared Cox regression models including prespecified established predictors of mortality using Harrell's C and likelihood ratio tests.

RESULTS

A total of 2236 patients (median [interquartile range] age: 71 [59-80] years, 43% female, National Institutes of Health Stroke Scale: 2 [1-6], median follow-up: 1436 days, 21% death during follow-up) were included. Increasing WMH (per point adjusted Hazard Ratio [aHR] = 1.29 [1.14-1.45]), but not CBI (aHR = 1.21 [0.99-1.49]), were independently associated with mortality. Neither CBI phenotype, count, nor location was associated with mortality and there was no multiplicative interaction between CBI and WMH (p > .1). As compared to patients without CBI or WMH, patients with moderate or severe WMH and additional CBI had the highest hazards of death (aHR = 1.62 [1.23-2.13]). The Cox regression model including CBI and WMH had a small but significant increment in Harrell's C when compared to the model including 14 clinical variables (0.831 vs. 0.827, p < .001).

DISCUSSION

WMH represent a strong surrogate biomarker of long-term mortality in first-ever manifest AIS or TIA patients. CBI phenotypes, count, and location seem less relevant. Incorporation of CBI and WMH slightly improves predictive capacity of established risk scores.

Pathogeneses and Imaging Features of Cerebral White Matter Lesions of Vascular Origins

White matter lesion (WML), also known as white matter hyperintensities or leukoaraiosis, was first termed in 1986 to describe the hyperintense signals on T2-weighted imaging (T2WI) and fluid-attenuated inversion recovery (FLAIR) maps. Over the past decades, a growing body of pathophysiological findings regarding WMLs have been discovered and discussed. Currently, the generally accepted WML pathogeneses mainly include hypoxia-ischemia, endothelial dysfunction, blood-brain barrier disruption, and infiltration of inflammatory mediators or cytokines. However, none of them can explain the whole dynamics of WML formation. Herein, we primarily focus on the pathogeneses and neuroimaging features of vascular WMLs. To achieve this goal, we searched papers with any type published in PubMed from 1950 to 2020 and cross-referenced the keywords including “leukoencephalopathy”, “leukoaraiosis”, “white matter hyperintensity”, “white matter lesion”, “pathogenesis”, “pathology”, “pathophysiology”, and “neuroimaging”. Moreover, references of the selected articles were browsed and searched for additional pertinent articles. We believe this work will supply the robust references for clinicians to further understand the different WML patterns of varying vascular etiologies and thus make customized treatment.

Subclinical Vascular Brain Lesions in Young Adults With Acute Ischemic Stroke

BACKGROUND AND PURPOSE

Subclinical vascular brain lesions are highly prevalent in elderly patients with stroke. Little is known about predisposing factors and their impact on long-term outcome of patients with stroke at a young age.

METHODS

We quantified magnetic resonance-defined subclinical vascular brain lesions, including lacunes and white matter hyperintensities, perivascular spaces and cerebral microbleeds, and assessed total small-vessel disease (SVD) score in patients with first-ever acute ischemic stroke aged 18 to 45 years, and followed them up, as part of the multicentre Italian Project on Stroke in Young Adults. The primary end point was a composite of ischemic stroke, transient ischemic attack, myocardial infarction, or other arterial events. We assessed the predictive accuracy of magnetic resonance features and whether the addition of these markers improves outcome prediction over a validated clinical tool, such as the Italian Project on Stroke in Young Adults score.

RESULTS

Among 591 patients (males, 53.8%; mean age, 37.5±6.4 years), 117 (19.8%) had subclinical vascular brain lesions. Family history of stroke was associated with lacunes (odds ratio, 2.24 [95% CI, 1.30-3.84]) and total SVD score (odds ratio, 2.06 [95% CI, 1.20-3.53] for score≥1), hypertension with white matter hyperintensities (odds ratio, 2.29 [95% CI, 1.22-4.32]). After a median follow-up of 36.0 months (25th-75th percentile, 38.0), lacunes and total SVD score were associated with primary end point (hazard ratio, 2.13 [95% CI, 1.17-3.90] for lacunes; hazard ratio, 2.17 [95% CI, 1.20-3.90] for total SVD score ≥1), and the secondary end point brain ischemia (hazard ratio, 2.55 [95% CI, 1.36-4.75] for lacunes; hazard ratio, 2.61 [95% CI, 1.42-4.80] for total SVD score ≥1). The predictive performances of the models, including magnetic resonance features were comparable to those of the random model. Adding individual magnetic resonance features to the Italian Project on Stroke in Young Adults score did not improve model prediction.

CONCLUSIONS

Subclinical vascular brain lesions affect ≈2 in 10 young adults with ischemic stroke. Although lacunes and total SVD score are associated with thrombotic recurrence, they do not improve accuracy of outcome prediction over validated clinical predictors.