Association of Neuroimaging Markers on Clinical CT Scans With Domain-Specific Cognitive Impairment in the Early and Later Poststroke Stages

Infarct volume as a predictor and therapeutic target in post-stroke cognitive impairment

Post-stroke cognitive impairment is one of the most common consequences of stroke, affecting more than half of stroke patients, especially in the geriatric population. Post-ischemic stroke cognitive impairment (PISCI) is particularly detrimental, as it can exacerbate a patient's disability. Given that the severe consequences of adverse life outcomes are major contributors to disability and death among survivors of ischemic stroke, preventing stroke and PISCI remains a fundamental strategy for maintaining optimal brain health. Recent studies have extensively investigated the epidemiology, diagnosis, and management of PISCI. Nevertheless, significant gaps persist in our understanding of its pathophysiological mechanisms and potential therapeutic targets, which warrants further research. Factors such as baseline brain health, cerebral small vessel disease, and stroke characteristics (e.g., infarct location, severity, and morphology) have been associated with PISCI. However, its pathophysiology remains inadequately understood. Recent research suggests that infarct volume may serve as a novel indicator for predicting and managing PISCI. Thus, this review aims to expand our understanding of factors influencing PISCI and to elucidate its pathophysiological mechanisms. In particular, infarct volume has been proposed as a potential target and may play a critical role in predicting and managing PISCI. We advocate for improved and timely predictions of PISCI to enhance the quality of life for patients and reduce the economic and emotional burden on caregivers.

Multivariate and network lesion mapping reveals distinct architectures of domain-specific post-stroke cognitive impairments

BACKGROUND

The purpose of this study was to identify patterns of structural disconnection and multivariate lesion-behaviour relationships associated with post-stroke deficits across six commonly impacted cognitive domains: executive function, language, memory, numerical processing, praxis, and visuospatial attention.

METHODS

Stroke survivors (n = 593) completed a brief domain-specific cognitive assessment (the Oxford Cognitive Screen (OCS)) during acute hospitalisation. Network-level and multivariate (sparce canonical correlation) lesion mapping analyses were conducted to identify focal neural correlates and distributed patterns of structural disconnection associated with impairment on each of the 16 OCS measures.

RESULTS

Network-level and multivariate lesion mapping analyses identified significant correlates for 12/16 and 10/16 OCS measures, respectively which were largely consistent with correlates reported in past work. Language impairments were reliably localised to network- and voxel-level correlates centred in left fronto-temporal regions. Memory impairments were associated with disconnection in a large network of left hemisphere regions. Number processing deficits were associated with damage to voxels centred in the left insular/opercular cortex, as well as disconnection within the surrounding white matter tracts. Within the domain of attention, different subtypes of visuospatial neglect were linked to distinct but partially overlapping patterns of disconnection and voxel-level damage. Praxis impairment was not linked to any voxel-level regions but was significantly associated with disconnection within the left hemisphere dorsal attention network.

CONCLUSION

These results highlight the utility of routine, domain-specific cognitive assessment and imaging data for theoretically-driven lesion mapping analyses, while providing novel insight into the complex anatomical correlates of common and debilitating post-stroke cognitive impairments.

Innovations and challenges in predicting cognitive trajectories after stroke

This scientific commentary refers to 'Deep learning disconnectomes to accelerate and improve long-term predictions for post-stroke symptoms', by Matsulevits et al. (https://doi.org/10.1093/braincomms/fcae338).

White matter integrity and functional connectivity of the default mode network in acute stroke are associated with cognitive outcome three months post-stroke

BACKGROUND

Knowledge about factors that are associated with post-stroke cognitive outcome is important to identify patients with high risk for impairment. We therefore investigated the associations of white matter integrity and functional connectivity (FC) within the brain's default-mode network (DMN) in acute stroke patients with cognitive outcome three months post-stroke.

METHODS

Patients aged between 18 and 85 years with an acute symptomatic MRI-proven unilateral ischemic middle cerebral artery infarction, who had received reperfusion therapy, were invited to participate in this longitudinal study. All patients underwent brain MRI within 24-72 h after symptom onset, and participated in a neuropsychological assessment three months post-stroke. We performed hierarchical regression analyses to explore the incremental value of baseline white matter integrity and FC beyond demographic, clinical, and macrostructural information for cognitive outcome.

RESULTS

The study cohort comprised 34 patients (mean age: 64 ± 12 years, 35% female). The initial median National Institutes of Health Stroke Scale (NIHSS) score was 10, and significantly improved three months post-stroke to a median NIHSS = 1 (p < .001). Nonetheless, 50% of patients showed cognitive impairment three months post-stroke. FC of the non-lesioned anterior cingulate cortex of the affected hemisphere explained 15% of incremental variance for processing speed (p = .007), and fractional anisotropy of the non-lesioned cingulum of the affected hemisphere explained 13% of incremental variance for cognitive flexibility (p = .033).

CONCLUSIONS

White matter integrity and functional MRI markers of the DMN in acute stroke explain incremental variance for post-stroke cognitive outcome beyond demographic, clinical, and macrostructural information.

Cognitive trajectory in the first year after first-ever ischaemic stroke in young adults: the ODYSSEY study

BACKGROUND

Limited data exists on cognitive recovery in young stroke patients. We aimed to investigate the longitudinal course of cognitive performance during the first year after stroke at young age and identify predictors for cognitive recovery.

METHODS

We conducted a multicentre prospective cohort study between 2013 and 2021, enrolling patients aged 18-49 years with first-ever ischaemic stroke. Cognitive assessments were performed within 6 months and after 1 year following the index event, covering seven cognitive domains. Composite Z-scores using normative data determined cognitive impairment (Z-score<-1.5). A Reliable Change Index (RCI) assessed cognitive recovery (RCI>1.96) or decline (RCI<-1.96).

RESULTS

393 patients (median age 44.3 years, IQR 38.4-47.2) completed cognitive assessments with a median time interval of 403 days (IQR 364-474) between assessments. Based on RCI, a similar proportion of patients showed improvement and decline in each cognitive domain, while the majority exhibited no cognitive change. Among cognitively impaired patients at baseline, improvements were observed in processing speed (23.1%), visuoconstruction (40.1%) and executive functioning (20.0%). Younger age was associated with better cognitive recovery in visuoconstruction, and larger lesion volume was related to cognitive recovery in processing speed. No other predictors for cognitive recovery were identified.

CONCLUSIONS

Cognitive impairment remains prevalent in young stroke even 1 year after the event. Most patients showed no cognitive change, however, recovery may have occurred in the early weeks after stroke, which was not assessed in our study. Among initially cognitively impaired patients, cognitive recovery is observed in processing speed, visuoconstruction and executive functioning. It is still not possible to predict cognitive recovery in individual patients.