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

Genevieve Richard*, Knut Kolskar, Kristine M. Ulrichsen, Tobias Kaufmann, Dag Alnaes, Anne-Marthe Sanders, Erlend S. Dorum, Jennifer Monereo Sanchez, Anders Petersen, Hege Ihle-Hansen, Jan Egil Nordvik, Lars T. Westlye*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

13 Citations (Web of Science)

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

Original languageEnglish
Article number102159
Number of pages11
JournalNeuroImage: Clinical
Volume25
DOIs
Publication statusPublished - 2020

Keywords

  • Computerized cognitive training
  • Transcranial direct current stimulation
  • Magnetic resonance imaging
  • Brain age prediction
  • Cerebral stroke, T1
  • QUALITY-OF-LIFE
  • GLOBAL BURDEN
  • IMPAIRMENT

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