The Additional Contribution of White Matter Hyperintensity Location to Post-stroke Cognitive Impairment: Insights From a Multiple-Lesion Symptom Mapping Study
| Autor: | Lei Zhao, Adrian Wong, Yishan Luo, Wenyan Liu, Winnie W. C. Chu, Jill M. Abrigo, Ryan K. L. Lee, Vincent Mok, Lin Shi |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
medicine.medical_specialty
Corpus callosum behavioral disciplines and activities multiple-lesion symptom mapping 050105 experimental psychology Lateralization of brain function lcsh:RC321-571 Lesion 03 medical and health sciences 0302 clinical medicine Physical medicine and rehabilitation mental disorders ischemic stroke medicine 0501 psychology and cognitive sciences support vector regression Cognitive impairment lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry Stroke Original Research cognitive impairment business.industry General Neuroscience white matter hyperintensity 05 social sciences Montreal Cognitive Assessment Cognition medicine.disease Hyperintensity lesion location medicine.symptom business 030217 neurology & neurosurgery Neuroscience |
| Zdroj: | Frontiers in Neuroscience, Vol 12 (2018) Frontiers in Neuroscience |
| ISSN: | 1662-453X |
| Popis: | White matter hyperintensities (WMH) are common in acute ischemic stroke patients. Although WMH volume has been reported to influence post-stroke cognition, it is still not clear whether WMH location, independent of acute ischemic lesion (AIL) volume and location, contributes to cognitive impairment after stroke. Here, we proposed a multiple-lesion symptom mapping model that considers both the presence of WMH and AIL to measure the additional contribution of WMH locations to post-stroke cognitive impairment. Seventy-six first-ever stroke patients with AILs in the left hemisphere were examined by Montreal Cognitive Assessment (MoCA) at baseline and 1 year after stroke. The association between the location of AIL and WMH and global cognition was investigated by a multiple-lesion symptom mapping (MLSM) model based on support vector regression (SVR). To explore the relative merits of MLSM over the existing lesion-symptom mapping approaches with only AIL considered (mass-univariate VLSM and SVR-LSM), we measured the contribution of the significant AIL and/or WMH clusters from these models to post-stroke cognitive impairment. In addition, we compared the significant WMH locations identified by the optimal SVR-MLSM model for cognitive impairment at baseline and 1 year post stroke. The identified strategic locations of WMH significantly contributed to the prediction of MoCA at baseline (short-term) and 1 year (long-term) after stroke independent of the strategic locations of AIL. The significant clusters of WMH for short-term and long-term post-stroke cognitive impairment were mainly in the corpus callosum, corona radiata, and posterior thalamic radiation. We noted that in some regions, the AIL clusters that were significant for short-term outcome were no longer significant for long-term outcome, and interestingly more WMH clusters in these regions became significant for long-term outcome compared to short-term outcome. This indicated that there are some regions where local WMH burden has larger impact than AIL burden on the long-term post-stroke cognitive impairment. In consequence, SVR-MLSM was effective in identifying the WMH locations that have additional impact on post-stroke cognition on top of AIL locations. Such a method can also be applied to other lesion-behavior studies where multiple types of lesions may have potential contributions to a specific behavior. |
| Databáze: | OpenAIRE |
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