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Frontiers in Neurology
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three class differential diagnosis among alzheimer disease frontotemporal dementia and controls

Authors: Raamana, Pradeep Reddy; Rosen, Howard; Miller, Bruce; Weiner, Michael W; Wang, Lei; Beg, Mirza Faisal;

three class differential diagnosis among alzheimer disease frontotemporal dementia and controls

Abstract

Biomarkers derived from brain magnetic resonance (MR) imaging have promise in being able to assist in the clinical diagnosis of brain pathologies. These have been used in many studies in which the goal has been to distinguish between pathologies such as Alzheimer's disease and healthy aging. However, other dementias, in particular, frontotemporal dementia, also present overlapping pathological brain morphometry patterns. Hence, a classifier that can discriminate morphometric features from a brain MRI from the three classes of normal aging, Alzheimer's disease (AD), and frontotemporal dementia (FTD) would offer considerable utility in aiding in correct group identification. Compared to the conventional use of multiple pair-wise binary classifiers that learn to discriminate between two classes at each stage, we propose a single three-way classification system that can discriminate between three classes at the same time. We present a novel classifier that is able to perform a three-class discrimination test for discriminating among AD, FTD, and normal controls (NC) using volumes, shape invariants, and local displacements (three features) of hippocampi and lateral ventricles (two structures times two hemispheres individually) obtained from brain MR images. In order to quantify its utility in correct discrimination, we optimize the three-class classifier on a training set and evaluate its performance using a separate test set. This is a novel, first-of-its-kind comparative study of multiple individual biomarkers in a three-class setting. Our results demonstrate that local atrophy features in lateral ventricles offer the potential to be a biomarker in discriminating among AD, FTD, and NC in a three-class setting for individual patient classification.

Country
United States
Keywords

Aging, Clinical Sciences, Biological Psychology, 610, Clinical sciences, Neurodegenerative, Alzheimer's Disease, frontotemporal disease, Rare Diseases, Alzheimer Disease, Lateral Ventricles, differential diagnosis, Behavioral and Social Science, multi-class, Acquired Cognitive Impairment, Psychology, RC346-429, Alzheimer's Disease Related Dementias (ADRD), three class, screening and diagnosis, Biomedical and Clinical Sciences, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), ventricle, 4.1 Discovery and preclinical testing of markers and technologies, Brain Disorders, Detection, Frontotemporal Dementia (FTD), Frontotemporal Dementia, Neurological, Alzheimer, Biological psychology, Biomedical Imaging, Dementia, Neurology. Diseases of the nervous system, LDDMM, Neuroscience, 4.2 Evaluation of markers and technologies

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    47
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
47
Top 10%
Top 10%
Top 10%
Green
gold