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Assessment of Alzheimer's Disease Based on Texture Analysis of the Entorhinal Cortex

Leandrou, S., Lamnisos, D., Mamais, I., Kyriacou, P. A. ORCID: 0000-0002-2868-485X, Pattichis, C. S. and Alzheimer’s Disease and Neuroimaging Initiative, (2020). Assessment of Alzheimer's Disease Based on Texture Analysis of the Entorhinal Cortex. Frontiers in Aging Neuroscience, 12, 176.. doi: 10.3389/fnagi.2020.00176

Abstract

Alzheimer's disease (AD) brain magnetic resonance imaging (MRI) biomarkers based on larger-scale tissue neurodegeneration changes, such as atrophy, are currently widely used. Texture analysis evaluates the statistical properties of the tissue image quantitatively; therefore, it could detect smaller-scale changes of neurodegeneration. Entorhinal cortex is the first region affected, and no study has investigated texture analysis on this region before. This study aims to differentiate AD patients from Normal Control (NC) and Mild Cognitive Impairment (MCI) subjects using entorhinal cortex texture features. Furthermore, it was evaluated whether texture has association to MCI beyond that of volume, to evaluate if atrophy development may precede. Texture features were extracted from 194 NC, 200 MCI, 84 MCI who converted to AD (MCIc), and 130 AD subjects. Receiving operating characteristic curves determined the performance of the various features in discriminating the groups, and a predictive model was used to predict conversion of MCIc subjects to AD. An area under the curve (AUC) of 0.872, 0.710, 0.730, and 0.764 was seen between NC vs. AD, NC vs. MCI, MCI vs. MCIc, and MCI vs. AD subjects, respectively. Including entorhinal cortex volume improved the AUCs to 0.914, 0.740, 0.756, and 0.780, respectively. For the disease prediction, binary logistic regression was applied on five randomly selected test groups and achieved on average AUC's of 0.760 and 0.764 on the training and validation cohorts, respectively. Entorhinal cortex texture features were significantly different between the four groups and in many cases provided better results compared to other methods such as volumetry.

Publication Type: Article
Additional Information: Copyright © 2020 Leandrou, Lamnisos, Mamais, Kyriacou and Pattichis. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Publisher Keywords: Alzheimer’s disease, mild cognitive impairment, entorhinal cortex, magnetic resonance imaging, texture
Subjects: B Philosophy. Psychology. Religion > BF Psychology
R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Departments: School of Mathematics, Computer Science & Engineering > Engineering > Electrical & Electronic Engineering
Date Deposited: 05 Aug 2020 12:42
URI: https://openaccess.city.ac.uk/id/eprint/24638
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