Specific White Matter Tracts and Diffusion Properties Predict Conversion From Mild Cognitive Impairment to Alzheimer’s Disease
| Autor: | Christopher J Wertz, Sephira G Ryman, Alzheimer’s Disease Neuroimaging Initiative, David B. Stone, Alexandra P Hartman, Andrei A. Vakhtin |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
medicine.medical_specialty Aging Cognitive Neuroscience tractography Neurosciences. Biological psychiatry. Neuropsychiatry Disease behavioral disciplines and activities White matter 03 medical and health sciences 0302 clinical medicine mild cognitive impairment Internal medicine Fasciculus Medicine support vector machine Mild cognitive impairment (MCI) conversion Cognitive impairment Original Research biology business.industry Aging Neuroscience biology.organism_classification medicine.disease diffusion tensor imaging 030104 developmental biology medicine.anatomical_structure automated fiber quantification Cardiology Biomarker (medicine) biomarker business Alzheimer’s disease 030217 neurology & neurosurgery Tractography Diffusion MRI RC321-571 |
| Zdroj: | Frontiers in Aging Neuroscience Frontiers in Aging Neuroscience, Vol 13 (2021) |
| ISSN: | 1663-4365 |
| DOI: | 10.3389/fnagi.2021.711579 |
| Popis: | Identifying biomarkers that can assess the risk of developing Alzheimer’s Disease (AD) remains a significant challenge. In this study, we investigated the integrity levels of brain white matter in 34 patients with mild cognitive impairment (MCI) who later converted to AD and 53 stable MCI patients. We used diffusion tensor imaging (DTI) and automated fiber quantification to obtain the diffusion properties of 20 major white matter tracts. To identify which tracts and diffusion measures are most relevant to AD conversion, we used support vector machines (SVMs) to classify the AD conversion and non-conversion MCI patients based on the diffusion properties of each tract individually. We found that diffusivity measures from seven white matter tracts were predictive of AD conversion with axial diffusivity being the most predictive diffusion measure. Additional analyses revealed that white matter changes in the central and parahippocampal terminal regions of the right cingulate hippocampal bundle, central regions of the right inferior frontal occipital fasciculus, and posterior and anterior regions of the left inferior longitudinal fasciculus were the best predictors of conversion from MCI to AD. An SVM based on these white matter tract regions achieved an accuracy of 0.75. These findings provide additional potential biomarkers of AD risk in MCI patients. |
| Databáze: | OpenAIRE |
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