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Abstract
Objective To determine whether functional MRI connectivity can predict long-term cognitive function 36 months after minor stroke.
Methods Seventy-two participants with first-ever stroke were included at baseline and followed up for 36 months. A ridge regression machine learning algorithm was developed and used to predict cognitive scores 36 months poststroke on the basis of the functional networks measured using MRI at 6 months (referred to here as the poststroke cognitive impairment [PSCI] network). The prediction accuracy was evaluated in 4 domains (memory, attention/executive, language, and visuospatial functions) and compared with clinical data and other functional networks. The models' statistical significance was probed with permutation tests. The potential involvement of cortical atrophy was assessed 6 months poststroke. A second, independent dataset (n = 40) was used to validate the results and assess their generalizability.
Results Based on the PSCI network, a machine learning model was able to predict memory, attention, visuospatial functions, and language functions 36 months poststroke (r2: 0.67, 0.73, 0.55, and 0.48, respectively). The PSCI-based model was at least as accurate as models based on other functional networks or clinical data. Specific patterns were demonstrated for the 4 cognitive domains, with involvement of the left superior frontal cortex for memory, attention, and visuospatial functions. The cortical thickness 6 months poststroke was not correlated with cognitive function 36 months poststroke. The independent validation dataset gave similar results.
Conclusions A machine learning model based on the PSCI network can predict long-term cognitive outcome after stroke.
Glossary
- DEDEMAS=
- Determinants of Dementia After Stroke;
- DWI=
- diffusion-weighted imaging;
- FLAIR=
- fluid-attenuated inversion recovery;
- IQCODE=
- Informant Questionnaire on Cognitive Decline in the Elderly;
- LOOCV=
- leave-one-out cross-validation;
- MNI=
- Montreal Neurological Institute;
- MSE=
- mean squared error;
- NIHSS=
- National Institute of Health Stroke Scale;
- PSCI=
- poststroke cognitive impairment;
- ROI=
- region of interest;
- rs-MRI=
- resting-state functional connectivity in MRI;
- STROKDEM=
- Study of Factors Influencing Poststroke Dementia;
- T1W=
- T1-weighted;
- VBM=
- voxel-based morphometry;
- WMH=
- white matter hyperintensity
Footnotes
Go to Neurology.org/N for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.
↵* These authors contributed equally to this work.
Editorial, page 355
- Received April 15, 2020.
- Accepted in final form October 12, 2020.
- © 2021 American Academy of Neurology
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