Prediction of Cognitive Recovery After Stroke: The Value of Diffusion-Weighted Imaging-Based Measures of Brain Connectivity

Epileptic brain network mechanisms and neuroimaging techniques for the brain network

Epilepsy can be defined as a dysfunction of the brain network, and each type of epilepsy involves different brain-network changes that are implicated differently in the control and propagation of interictal or ictal discharges. Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice. An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tractography, diffusion kurtosis imaging-based fiber tractography, fiber ball imaging-based tractography, electroencephalography, functional magnetic resonance imaging, magnetoencephalography, positron emission tomography, molecular imaging, and functional ultrasound imaging have been extensively used to delineate epileptic networks. In this review, we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy, and extensively analyze the imaging mechanisms, advantages, limitations, and clinical application ranges of each technique. A greater focus on emerging advanced technologies, new data analysis software, a combination of multiple techniques, and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.

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.

Structural brain networks correlating with poststroke cognition

Cognitive deficits are a common and debilitating consequence of stroke, yet our understanding of the structural neurobiological biomarkers predicting recovery of cognition after stroke remains limited. In this longitudinal observational study, we set out to investigate the effect of both focal lesions and structural connectivity on poststroke cognition. Sixty-two patients with stroke underwent advanced brain imaging and cognitive assessment, utilizing the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE), at 3-month and 12-month poststroke. We first evaluated the relationship between lesions and cognition at 3 months using voxel-based lesion-symptom mapping. Next, a novel correlational tractography approach, using multi-shell diffusion-weighted magnetic resonance imaging (MRI) data collected at both time points, was used to evaluate the relationship between the white matter connectome and cognition cross-sectionally at 3 months, and longitudinally (12 minus 3 months). Lesion-symptom mapping did not yield significant findings. In turn, correlational tractography analyses revealed positive associations between both MoCA and MMSE scores and bilateral cingulum and the corpus callosum, both cross-sectionally at the 3-month stage, and longitudinally. These results demonstrate that rather than focal neural structures, a consistent structural connectome underpins the performance of two frequently used cognitive screening tools, the MoCA and the MMSE, in people after stroke. This finding should encourage clinicians and researchers to not only suspect cognitive decline when lesions affect these tracts, but also to refine their investigation of novel approaches to differentially diagnosing pathology associated with cognitive decline, regardless of the aetiology.

Post-stroke cognitive impairment remains highly prevalent and disabling despite state-of-the-art stroke treatment

BACKGROUND

State-of-the-art stroke treatment significantly reduces lesion size and stroke severity, but it remains unclear whether these therapeutic advances have diminished the burden of post-stroke cognitive impairment (PSCI).

AIMS

In a cohort of patients receiving modern state-of-the-art stroke care including endovascular therapy, we assessed the frequency of PSCI and the pattern of domain-specific cognitive deficits, identified risk factors for PSCI, and determined the impact of acute PSCI on stroke outcome.

METHODS

In this prospective monocentric cohort study, we examined patients with first-ever anterior circulation ischemic stroke without pre-stroke cognitive decline, using a comprehensive neuropsychological assessment ⩽10 days after symptom onset. Normative data were stratified by demographic variables. We defined PSCI as at least moderate (<1.5 standard deviation) deficits in ⩾2 cognitive domains. Multivariable regression analysis was applied to define risk factors for PSCI.

RESULTS

We analyzed 329 non-aphasic patients admitted from December 2020 to July 2023 (67.2 ± 14.4 years old, 41.3% female, 13.1 ± 2.7 years of education). Although most patients had mild stroke (median National Institutes of Health Stroke Scale (NIHSS) 24 h = 1.00 (0.00; 3.00); 87.5% with NIHSS ⩽ 5), 69.3% of them presented with PSCI 2.7 ± 2.0 days post-stroke. The most severely and often affected cognitive domains were verbal learning, episodic memory, executive functions, selective attention, and constructive abilities (39.1%-51.2% of patients), whereas spatial neglect was less frequent (18.5%). The risk of PSCI was reduced with more years of education (odds ratio (OR) = 0.47, 95% confidence interval (CI) = 0.23-0.99) and right hemisphere lesions (OR = 0.47, 95% CI = 0.26-0.84), and increased with stroke severity (NIHSS 24 h, OR = 4.19, 95% CI = 2.72-6.45), presence of hyperlipidemia (OR = 1.93, 95% CI = 1.01-3.68), but was not influenced by age. After adjusting for stroke severity and depressive symptoms, acute PSCI was associated with poor functional outcome (modified Rankin Scale > 2, F = 13.695, p < 0.001) and worse global cognition (Montreal Cognitive Assessment (MoCA) score, F = 20.069, p < 0.001) at 3 months post-stroke.

CONCLUSION

Despite modern stroke therapy and many strokes having mild severity, PSCI in the acute stroke phase remains frequent and associated with worse outcome. The most prevalent were learning and memory deficits. Cognitive reserve operationalized as years of education independently protects post-stroke cognition.

Predictors of Cognitive Functions After Stroke Assessed Using the Wechsler Adult Intelligence Scale: A Retrospective Study

Background

The mechanism(s) of cognitive impairment remains complex, making it difficult to confirm the factors influencing poststroke cognitive impairment (PSCI).

Objective

This study quantitatively investigated the degree of influence and interactions of clinical indicators of PSCI.

Methods

Information from 270 patients with PSCI and their Wechsler Adult Intelligence Scale (WAIS-RC) scores, totaling 18 indicators, were retrospectively collected. Correlations between the indicators and WAIS scores were calculated. Multiple linear regression model(MLR), genetic algorithm modified Back-Propagation neural network(GA-BP), logistic regression model (LR), XGBoost model (XGB), and structural equation model were used to analyze the degree of influence of factors on the WAIS and their mediating effects.

Results

Seven indicators were significantly correlated with the WAIS scores: education, lesion side, aphasia, frontal lobe, temporal lobe, diffuse lesions, and disease course. The MLR showed significant effect of education, lesion side, aphasia, diffuse lesions, and frontal lobe on the WAIS. The GA-BP included five factors: education, aphasia, frontal lobe, temporal lobe, and diffuse lesions. LR predicted that the lesion side contributed more to mild cognitive impairment, while education, lesion side, aphasia, and course of the disease contributed more to severe cognitive impairment. XGB showed that education, side of the lesion, aphasia, and diffuse lesions contributed the most to PSCI. Aphasia plays a significant mediating role in patients with severe PSCI.

Conclusions

Education, lesion side, aphasia, frontal lobe, and diffuse lesions significantly affected PSCI. Aphasia is a mediating variable between clinical information and the WAIS in patients with severe PSCI.

Neuroimaging biomarkers of cognitive recovery after ischemic stroke

Post-stroke cognitive impairment affects more than one-third of patients after an ischemic stroke (IS). Identifying markers of potential cognitive recovery after ischemic stroke can guide patients' selection for treatments, enrollment in clinical trials, and cognitive rehabilitation methods to restore cognitive abilities in post-stroke patients. Despite the burden of post-stroke cognitive impairment, biomarkers of cognitive recovery are an understudied area of research. This narrative review summarizes and critically reviews the current literature on the use and utility of neuroimaging as a predictive biomarker of cognitive recovery after IS. Most studies included in this review utilized structural Magnetic Resonance Imaging (MRI) to predict cognitive recovery after IS; these studies highlighted baseline markers of cerebral small vessel disease and cortical atrophy as predictors of cognitive recovery. Functional Magnetic Resonance Imaging (fMRI) using resting-state functional connectivity and Diffusion Imaging are potential biomarkers of cognitive recovery after IS, although more precise predictive tools are needed. Comparison of these studies is limited by heterogeneity in cognitive assessments. For all modalities, current findings need replication in larger samples. Although no neuroimaging tool is ready for use as a biomarker at this stage, these studies suggest a clinically meaningful role for neuroimaging in predicting post-stroke cognitive recovery.

Cognitive recovery in patients with post-stroke subjective cognitive complaints

Background and purpose

The objective cognitive trajectory in patients with post-stroke subjective cognitive complaints (SCC) over time remained unknown. We investigated cognitive outcomes in patients with SCC within 1 year after stroke, and determined factors associated with cognitive recovery.

Methods

This study included 599 patients with a clinical diagnosis of post-stroke SCC and evidence of cognitive deficits including Clinical Dementia Rating Scale (CDR) = 0.5, Montreal Cognitive Assessment (MoCA) score <26, and Mini–Mental State Examination score >17 (illiterate) or >20 (primary school) or >24 (junior school or above). Neuropsychological assessment was performed at baseline (2 weeks to 6 months after stroke) and 6-month follow-up visit. Cognitive recovery was operationalized as unimpaired cognition (MoCA score ≥26 and CDR = 0) after 6 months. Factors associated with recovery were defined through logistic regression analysis.

Results

After 6 months, 583 patients completed the follow-up with 80 (13.72%) presenting cognitive recovery, among which, 22 (9.48%) cases reported SCC within 2 weeks after stroke, six (10%) at 15–30 days, 13 (15.12%) at 31–60 days, 10 (16.13%) at 61–90 days, five (10.42%) at 91–120 days, nine (23.08%) at 121–150 days, and 15 (26.79%) at 151–180 days. Compared to those reported cognitive complaints at 151–180 days after stroke, patients with early post-stroke SCC had poorer cognitive recovery, which was only significant in individuals with high level of education. Male sex, higher baseline MoCA scores, coffee intake and thalamus lesions were independently associated with high chance of cognitive recovery.

Conclusions

Although post-stroke SCC contributes to persisting objective cognitive deficits, some patients presented cognitive recovery within 1 year after stroke. Patients with a high education level reporting SCC at earlier stage after stroke had poorer cognitive recovery. Male, higher baseline MoCA scores, coffee intake and thalamus lesions appear to independently predict cognitive recovery.

Vascular Cognitive Impairment After Mild Stroke: Connectomic Insights, Neuroimaging, and Knowledge Translation

Contemporary stroke assessment protocols have a limited ability to detect vascular cognitive impairment (VCI), especially among those with subtle deficits. This lesser-involved categorization, termed mild stroke (MiS), can manifest compromised processing speed that negatively impacts cognition. From a neurorehabilitation perspective, research spanning neuroimaging, neuroinformatics, and cognitive neuroscience supports that processing speed is a valuable proxy for complex neurocognitive operations, insofar as inefficient neural network computation significantly affects daily task performance. This impact is particularly evident when high cognitive loads compromise network efficiency by challenging task speed, complexity, and duration. Screening for VCI using processing speed metrics can be more sensitive and specific. Further, they can inform rehabilitation approaches that enhance patient recovery, clarify the construct of MiS, support clinician-researcher symbiosis, and further clarify the occupational therapy role in targeting functional cognition. To this end, we review relationships between insult-derived connectome alterations and VCI, and discuss novel clinical approaches for identifying disruptions of neural networks and white matter connectivity. Furthermore, we will frame knowledge translation efforts to leverage insights from cutting-edge structural and functional connectomics research. Lastly, we highlight how occupational therapists can provide expertise as knowledge brokers acting within their established scope of practice to drive substantive clinical innovation.