Longitudinal brain age prediction and cognitive function after stroke

Aamodt, Eva Birgitte; Alnæs, Dag; Lange, Ann-Marie G. de; Aam, Stina; Schellhorn, Till; Saltvedt, Ingvild; Beyer, Mona K.

doi:10.1016/j.neurobiolaging.2022.10.007

Cited by 7 publications

(4 citation statements)

References 217 publications

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“…However, B-cell-deficient ischemic stroke mice did not show any improvement in neurological function, whereas B-cell overshoot attenuated the extent of cerebral infarction and improved neurological function, which may be related to the secretion of the anti-inflammatory cytokine IL-10. Eva et al found that a more youthful brain appearance was associated with a lower risk of post-stroke neurocognitive deficits (NCD), even in patients who did not show signs of injury within 3 months of stroke ( Aamodt et al, 2023 ). Delayed emergence of B-cell and T-cell clusters in the later stages of stroke injury is associated with cognitive decline and may indicate a deleterious adaptive immune response ( Tsai et al, 2019 ).…”

Section: The Role Of B-cells At the Chronic Phase After Strokementioning

confidence: 99%

Updates of the role of B-cells in ischemic stroke

Wu,

Tabassum,

Payne

et al. 2024

Front. Cell. Neurosci.

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Ischemic stroke is a major disease causing death and disability in the elderly and is one of the major diseases that seriously threaten human health and cause a great economic burden. In the early stage of ischemic stroke, neuronal structure is destroyed, resulting in death or damage, and the release of a variety of damage-associated pattern molecules induces an increase in neuroglial activation, peripheral immune response, and secretion of inflammatory mediators, which further exacerbates the damage to the blood–brain barrier, exacerbates cerebral edema, and microcirculatory impairment, triggering secondary brain injuries. After the acute phase of stroke, various immune cells initiate a protective effect, which is released step by step and contributes to the repair of neuronal cells through phenotypic changes. In addition, ischemic stroke induces Central Nervous System (CNS) immunosuppression, and the interaction between the two influences the outcome of stroke. Therefore, modulating the immune response of the CNS to reduce the inflammatory response and immune damage during stroke is important for the protection of brain function and long-term recovery after stroke, and modulating the immune function of the CNS is expected to be a novel therapeutic strategy. However, there are fewer studies on B-cells in brain function protection, which may play a dual role in the stroke process, and the understanding of this cell is still incomplete. We review the existing studies on the mechanisms of the role of B-cells, inflammatory response, and immune response in the development of ischemic stroke and provide a reference for the development of adjuvant therapeutic drugs for ischemic stroke targeting inflammatory injury.

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Section: The Role Of B-cells At the Chronic Phase After Strokementioning

confidence: 99%

Updates of the role of B-cells in ischemic stroke

Wu,

Tabassum,

Payne

et al. 2024

Front. Cell. Neurosci.

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“…The severity of cognitive impairment, often characterized by working memory and attentional control deficits as well as reduced processing speed (Barker‐Collo et al., 2010 ; Hochstenbach et al., 1998 ), may be dependent on the location and severity of the stroke (Sun et al., 2014 ). Importantly, cognitive deficits post‐stroke may also vary with age (Gorelick et al., 2011 ), education, occupation (Wu et al., 2013 ), vascular factors (Sahathevan et al., 2012 ), and overall brain health as indicated by brain age (Aamodt et al., 2023 ). Attentional control and working memory enable both the detection, filtering, and temporary storage of relevant information while using that information to perform a cognitive task (Baddeley, 1986 ), which are key functions to support daily activities (Ponsford et al., 2014 ).…”

Section: Introductionmentioning

confidence: 99%

Exploring the associations between physical activity level, cognitive performance, and response to computerized cognitive training among chronic stroke patients

Sanders,

Richard,

Kolskår

et al. 2024

Brain and Behavior

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BackgroundPost‐stroke attentional and working memory deficits are common and represent relevant predictors of long‐term functional recovery and outcome. The individual responses to cognitive rehabilitation and interventions vary between patients and are influenced by multiple factors. Recently, a link between the level of engagement in physical activities and cognitive rehabilitation has been suggested. However, few previous studies have tested the predictive value of physical activity on cognitive performance and response to cognitive training among chronic stroke patients. There is also a lack of knowledge concerning the prognostic value of index stroke characteristics on physical activity in chronic phase.MethodIn this cross‐sectional and longitudinal study, including stroke survivors suffering mild‐to‐moderate strokes (n = 52, mean age = 70 years), we used Bayesian regression to test the association between cognitive performance and response to a 3‐week intervention with a commonly used computerized cognitive training (CCT) system and baseline physical activity level measured with International Physical Activity Questionnaire. We also tested the association between physical activity level in chronic phase and stroke characteristics, including stroke severity (National Institutes of Health Stroke Scale), ischemic stroke etiology (Trial of Org 10172 in Acute Stroke Treatment), and stroke location (n = 66, mean age = 68 years). For descriptive purposes, we included 104 sex‐ and age‐matched healthy controls (mean age = 69 years).ResultsThe analyses revealed anecdotal evidence of a positive association between overall cognitive performance and daily minutes of sedentary behavior, indicating that better cognitive performance was associated with more daily hours of sitting still. We found no support for an association between cognitive performance and response to CCT with activity level. In addition, the analysis showed group differences in sedentary behavior between patients with small‐vessel disease (n = 20) and cardioembolism (n = 7), indicating more sedentary behavior in patients with small‐vessel disease. There was no further support for a predictive value of index stroke characteristics on physical activity level.ConclusionThe results do not support that baseline physical activity level is a relevant predictor of the overall performance or response to CCT in this sample of chronic stroke patients. Similarly, the analyses revealed little evidence for an association between index stroke characteristics and future activity level in patients surviving mild‐to‐moderate stroke.

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“…Ultimately, regions extending beyond the penumbra may reflect factors that influence perfusion and improve model predictions. Many of these have been associated with outcome in prior work and include location of injury (e.g., Hope et al, 2013), rate of atrophy after stroke (Seghier et al, 2014), rate of age-associated morphological changes (e.g., Aamodt et al, 2023; Kristinsson et al, 2022; Seghier et al, 2014), existing comorbidities like white matter hyperintensities (e.g., Sagnier et al, 2020) and microbleeds (e.g., Sheikj-Bahaei et al, 2019), and individual variability in functional anatomy (Crafton, Mark & Cramer, 2003).…”

Section: Introductionmentioning

confidence: 99%

Excellence is a habit: Enhancing predictions of language impairment by identifying stable features in clinical perfusion scans

Teghipco,

Kim,

Rorden

et al. 2023

Preprint

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Perfusion images guide acute stroke management, yet few studies have been able to systematically investigate CT perfusion collected during routine care because the measures are stored in proprietary formats incompatible with conventional research analysis pipelines. We illustrate the potential of harnessing granular data from these routine scans by using them to identify the association between specific areas of hypoperfusion and severity of object naming impairment in 43 acute stroke patients. Traditionally, similar analyses in such sample sizes face a dilemma:simple models risk being too constrained to make accurate predictions, while complex models risk overfitting and producing poor out-of-sample predictions. We demonstrate that evaluating the stability rather than out-of-sample predictive capacity of features in a nested cross-validation scheme can be an effective way of controlling model complexity and stabilizing model estimates across a variety of different regression techniques. Specifically, we show that introducing this step can determine model significance, even when the regression model already contains an embedded feature selection or dimensionality reduction step, or if a subset of features is manually selected prior to training based on expert knowledge. After improving model performance using more complex regression techniques, we discover that object naming performance relies on an extended language network encompassing regions thought to play a larger role in different naming tasks, right hemisphere regions distal to the site of injury, and regions and tracts that are less typically associated with language function. Our findings especially emphasize the role of the left superior temporal gyrus, uncinate fasciculus, and posterior insula in successful prediction of object naming impairment. Collectively, these results highlight the untapped potential of clinical CT perfusion images and demonstrate a flexible framework for enabling prediction in the limited sample sizes that currently dominate clinical neuroimaging.

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Longitudinal brain age prediction and cognitive function after stroke

Cited by 7 publications

References 217 publications

Updates of the role of B-cells in ischemic stroke

Updates of the role of B-cells in ischemic stroke

Exploring the associations between physical activity level, cognitive performance, and response to computerized cognitive training among chronic stroke patients

Excellence is a habit: Enhancing predictions of language impairment by identifying stable features in clinical perfusion scans

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