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Background and Objectives: The typical infarct volume trajectories in stroke patients, categorized as slow or fast progressors, remain largely unknown. This study aimed to reveal the characteristic spatiotemporal evolutions of infarct volumes caused by large vessel occlusion (LVO) and show that such growth charts help anticipate clinical outcomes., Methods: We conducted a secondary analysis from prospectively collected databases (FRAME, 2017-2019; ETIS, 2015-2022). We selected acute MRI data from anterior LVO stroke patients with witnessed onset, which were divided into training and independent validation datasets. In the training dataset, using Gaussian mixture analysis, we classified the patients into 3 growth groups based on their rate of infarct growth (diffusion volume/time-to-imaging). Subsequently, we extrapolated pseudo-longitudinal models of infarct growth for each group and generated sequential frequency maps to highlight the spatial distribution of infarct growth. We used these charts to attribute a growth group to the independent patients from the validation dataset. We compared their 3-month modified Rankin scale (mRS) with the predicted values based on a multivariable regression model from the training dataset that used growth group as an independent variable., Results: We included 804 patients (median age 73.0 years [interquartile range 61.2-82.0 years]; 409 men). The training dataset revealed nonsupervised clustering into 11% (74/703) slow, 62% (437/703) intermediate, and 27% (192/703) fast progressors. Infarct volume evolutions were best fitted with a linear ( r = 0.809; p < 0.001), cubic ( r = 0.471; p < 0.001), and power ( r = 0.63; p < 0.001) function for the slow, intermediate, and fast progressors, respectively. Notably, the deep nuclei and insular cortex were rapidly affected in the intermediate and fast groups with further cortical involvement in the fast group. The variable growth group significantly predicted the 3-month mRS (multivariate odds ratio 0.51; 95% CI 0.37-0.72, p < 0.0001) in the training dataset, yielding a mean area under the receiver operating characteristic curve of 0.78 (95% CI 0.66-0.88) in the independent validation dataset., Discussion: We revealed spatiotemporal archetype dynamic evolutions following LVO stroke according to 3 growth phenotypes called slow, intermediate, and fast progressors, providing insight into anticipating clinical outcome. We expect this could help in designing neuroprotective trials aiming at modulating infarct growth before EVT.

Microstructural changes after an ischemic stroke (IS) have mainly been described in white matter. Data evaluating microstructural changes in gray matter (GM) remain scarce. The aim of the present study was to evaluate the integrity of GM on longitudinal data using mean diffusivity (MD), and its influence on post-IS cognitive performances. A prospective study was conducted, including supra-tentorial IS patients without pre-stroke disability. A cognitive assessment was performed at baseline and 1 year, including a Montreal Cognitive Assessment, an Isaacs set test, and a Zazzo cancelation task (ZCT): completion time and number of errors. A 3-T brain MRI was performed at the same two time-points, including diffusion tensor imaging for the assessment of GM MD. GM volume was also computed, and changes in GM volume and GM MD were evaluated, followed by the assessment of the relationship between these structural changes and changes in cognitive performances. One hundred and four patients were included (age 68.5 ± 21.5, 38.5% female). While no GM volume loss was observed, GM MD increased between baseline and 1 year. The increase of GM MD in left fronto-temporal regions (dorsolateral prefrontal cortex, superior and medial temporal gyrus, p < 0.05, Threshold-Free Cluster Enhancement, 5000 permutations) was associated with an increase time to complete ZCT, regardless of demographic confounders, IS volume and location, GM, and white matter hyperintensity volume. GM integrity deterioration was thus associated with processing speed slowdown, and appears to be a biomarker of cognitive frailty. This broadens the knowledge of post-IS cognitive impairment mechanisms., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Normal-appearing white matter (NAWM) is a hub of plasticity, but data relating to its influence on post-ischemic stroke (IS) outcome remain scarce. The aim of this study was to evaluate the relationship between NAWM integrity and cognitive outcome after an IS. A longitudinal study was conducted including supra-tentorial IS patients. A 3-Tesla brain MRI was performed at baseline and 1 year, allowing the analyses of mean fractional anisotropy (FA) and mean diffusivity (MD) in NAWM masks, along with the volume of white matter hyperintensities (WMH) and IS. A Montreal Cognitive Assessment (MoCA), an Isaacs set test, and a Zazzo's cancellation task were performed at baseline, 3 months and 1 year. Mixed models were built, followed by Tract-based Spatial Statistics (TBSS) analyses. Ninety-five patients were included in the analyses (38% women, median age 69 ± 20). FA significantly decreased, and MD significantly increased between baseline and 1 year, while cognitive scores improved. Patients who decreased their NAWM FA more over the year had a slower cognitive improvement on MoCA (β =  - 0.11, p = 0.05). The TBSS analyses showed that patients who presented the highest decrease of FA in various tracts of white matter less improved their MoCA performances, regardless of WMH and IS volumes, demographic confounders, and clinical severity. NAWM integrity deteriorates over the year after an IS, and is associated with a cognitive recovery slowdown. The diffusion changes recorded here in patients starting with an early preserved white matter structure could have long term impact on cognition., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objective: The objective of this study was to evaluate the impact of radiological biomarkers suggestive of cerebral small vessel disease (SVD) on the evolution of cognitive performances after an ischemic stroke (IS)., Methods: We studied patients with a supratentorial IS recruited consecutively to a prospective monocentric longitudinal study. A cognitive assessment was performed at baseline, 3 months, and 1 year and was based on a Montreal Cognitive Assessment, an Isaacs set test of verbal fluency (IST), and a Zazzo's cancellation task (ZCT) for the evaluation of attentional functions and processing speed. The following cerebral SVD biomarkers were detected on a 3-T brain MRI performed at baseline: white matter hyperintensities (WMHs), deep and lobar microbleeds, enlarged perivascular spaces in basal ganglia and centrum semiovale, previous small deep infarcts, and cortical superficial siderosis (cSS). Generalized linear mixed models were used to evaluate the relationship between these biomarkers and changes in cognitive performances., Results: A total of 199 patients (65 ± 13 years, 68% male) were analyzed. Overall, the cognitive performances improved, more significantly in the first 3 months. Severe WMH was identified in 34% of the patients, and focal cSS in 3.5%. Patients with severe WMH and focal cSS had overall worse cognitive performances. Those with severe WMH had less improvement over time for IST (β = -0.16, p = 0.02) and the number of errors to ZCT (β = 0.19, p = 0.02), while those with focal cSS had less improvement over time for ZCT completion time (β = 0.14, p = 0.01) and number of errors (β = 0.17, p = 0.008), regardless of IS volume and location, gray matter volume, demographic confounders, and clinical and cardiovascular risk factors., Conclusion: The severity of SVD biomarkers, encompassing WMH and cSS, seems to reduce the magnitude of cognitive recovery after an IS. The detection of such SVD biomarkers early after stroke might help to identify patients with a cognitive vulnerability and a higher risk of poststroke cognitive impairment., (© 2021 S. Karger AG, Basel.)