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Brain age prediction in stroke patients: Highly reliable but limited sensitivity to cognitive performance and response to cognitive training.

ABSTRACT: Cognitive deficits are important predictors for outcome, independence and quality of life after stroke, but often remain unnoticed and unattended because other impairments are more evident. Computerized cognitive training (CCT) is among the candidate interventions that may alleviate cognitive difficulties, but the evidence supporting its feasibility and effectiveness is scarce, partly due to the lack of tools for outcome prediction and monitoring. Magnetic resonance imaging (MRI) provides candidate markers for disease monitoring and outcome prediction. By integrating information not only about lesion extent and localization, but also regarding the integrity of the unaffected parts of the brain, advanced MRI provides relevant information for developing better prediction models in order to tailor cognitive intervention for patients, especially in a chronic phase. Using brain age prediction based on MRI based brain morphometry and machine learning, we tested the hypotheses that stroke patients with a younger-appearing brain relative to their chronological age perform better on cognitive tests and benefit more from cognitive training compared to patients with an older-appearing brain. In this randomized double-blind study, 54 patients who suffered mild stroke (>6 months since hospital admission, NIHSS≤7 at hospital discharge) underwent 3-weeks CCT and MRI before and after the intervention. In addition, patients were randomized to one of two groups receiving either active or sham transcranial direct current stimulation (tDCS). We tested for main effects of brain age gap (estimated age - chronological age) on cognitive performance, and associations between brain age gap and task improvement. Finally, we tested if longitudinal changes in brain age gap during the intervention were sensitive to treatment response. Briefly, our results suggest that longitudinal brain age prediction based on automated brain morphometry is feasible and reliable in stroke patients. However, no significant association between brain age and both performance and response to cognitive training were found.

SUBMITTER: Richard G

PROVIDER: S-EPMC6953960 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundStrokes are becoming less severe due to increased numbers of intensive care units and improved treatments. As patients survive longer, post-stroke cognitive impairment (PSCI) has become a major health public issue. Diabetes has been identified as an independent predictive factor for PSCI. Here, we characterized a clinically relevant mouse model of PSCI, induced by permanent cerebral artery occlusion in diabetic mice, and investigated whether a reliable biomarker of PSCI may emerge from the kynurenine pathway which has been linked to inflammatory processes.MethodsCortical infarct was induced by permanent middle cerebral artery occlusion in male diabetic mice (streptozotocin IP). Six weeks later, cognitive assessment was performed using the Barnes maze, hippocampi long-term potentiation using microelectrodes array recordings, and neuronal death, white matter rarefaction and microglia/macrophages density assessed in both hemispheres using imunohistochemistry. Brain and serum metabolites of the kynurenin pathway were measured using HPLC and mass fragmentography. At last, these same metabolites were measured in the patient's serum, at the acute phase of stroke, to determine if they could predict PSCI 3 months later.ResultsWe found long-term spatial memory was impaired in diabetic mice 6 weeks after stroke induction. Synaptic plasticity was completely suppressed in both hippocampi along with increased neuronal death, white matter rarefaction in both striatum, and increased microglial/macrophage density in the ipsilateral hemisphere. Brain and serum quinolinic acid concentrations and quinolinic acid over kynurenic acid ratios were significantly increased compared to control, diabetic and non-diabetic ischemic mice, where PSCI was absent. These putative serum biomarkers were strongly correlated with degradation of long-term memory, neuronal death, microglia/macrophage infiltration and white matter rarefaction. Moreover, we identified these same serum biomarkers as potential predictors of PSCI in a pilot study of stroke patients.Conclusionswe have established and characterized a new model of PSCI, functionally and structurally, and we have shown that the QUIN/KYNA ratio could be used as a surrogate biomarker of PSCI, which may now be tested in large prospective studies of stroke patients.

Project description:BackgroundCognitive training is effective for improving cognitive performance among people with schizophrenia. An individual's perception of their own cognition is dissociable from performance on objective cognitive tests. Since subjective cognitive benefit may impact engagement, motivation, and satisfaction with time-intensive cognitive interventions, this study aimed to determine whether subjective cognitive difficulties improve in conjunction with cognitive gains following 30 h of cognitive training.MethodsPatients with schizophrenia or schizoaffective disorder (N = 46) were randomized to treatment as usual (TAU) or TAU augmented with auditory-targeted cognitive training (TCT). All participants completed assessment batteries at baseline and follow-up. As previously reported, the TCT group showed significant improvements in verbal learning and memory and reductions in auditory hallucinations relative to the TAU group.ResultsSubjective cognitive difficulties did not significantly improve following TCT, even among TCT participants who showed improvements in cognitive performance (all ps > 0.05). Subjective cognitive difficulties were significantly associated with severity of depressive symptoms and hallucinations (r = 0.48 and r = 0.28, p < 0.001), but not global or specific domains of cognition (all rs < 0.1) at baseline. There were no significant relationships between change in subjective cognitive difficulties and change in cognitive or clinical variables (all ps > 0.05).DiscussionPatients with schizophrenia do not detect change in their cognition following cognitive training, even among those who showed robust gains in cognitive performance. Failure to detect improvement may undermine treatment engagement, motivation, and satisfaction. Translating score improvements on the cognitive exercises into tangible metrics, and providing ongoing, clinician-delivered feedback on performance may facilitate patient ability to detect improvements and improve motivation to engage with cognitive training interventions.

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Brain age prediction in stroke patients: Highly reliable but limited sensitivity to cognitive performance and response to cognitive training.

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