Literature DB >> 25318546

Baseline shape diffeomorphometry patterns of subcortical and ventricular structures in predicting conversion of mild cognitive impairment to Alzheimer's disease.

Xiaoying Tang1, Dominic Holland2, Anders M Dale3, Laurent Younes4, Michael I Miller5.   

Abstract

In this paper, we propose a novel predictor for the conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD). This predictor is based on the shape diffeomorphometry patterns of subcortical and ventricular structures (left and right amygdala, hippocampus, thalamus, caudate, putamen, globus pallidus, and lateral ventricle) of 607 baseline scans from the Alzheimer's Disease Neuroimaging Initiative database, including a total of 210 healthy control subjects, 222 MCI subjects, and 175 AD subjects. The optimal predictor is obtained via a feature selection procedure applied to all of the 14 sets of shape features via linear discriminant analysis, resulting in a combination of the shape diffeomorphometry patterns of the left hippocampus, the left lateral ventricle, the right thalamus, the right caudate, and the bilateral putamen. Via 10-fold cross-validation, we substantiate our method by successfully differentiating 77.04% (104/135) of the MCI subjects who converted to AD within 36 months and 71.26% (62/87) of the non-converters. To be specific, for the MCI-converters, we are capable of correctly predicting 82.35% (14/17) of subjects converting in 6 months, 77.5% (31/40) of subjects converting in 12 months, 74.07% (20/27) of subjects converting in 18 months, 78.13% (25/32) of subjects converting in 24 months, and 73.68% (14/19) of subject converting in 36 months. Statistically significant correlation maps were observed between the shape diffeomorphometry features of each of the 14 structures, especially the bilateral amygdala, hippocampus, lateral ventricle, and two neuropsychological test scores--the Alzheimer's Disease Assessment Scale-Cognitive Behavior Section and the Mini-Mental State Examination.

Entities:  

Keywords:  Alzheimer's disease; lateral ventricles; linear discriminant analysis; mild cognitive impairment; prediction; principal component analysis; shape diffeomorphometry; subcortical structures

Mesh:

Year:  2015        PMID: 25318546      PMCID: PMC4474004          DOI: 10.3233/JAD-141605

Source DB:  PubMed          Journal:  J Alzheimers Dis        ISSN: 1387-2877            Impact factor:   4.472


  55 in total

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4.  Increasing power to predict mild cognitive impairment conversion to Alzheimer's disease using hippocampal atrophy rate and statistical shape models.

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5.  Multi-template tensor-based morphometry: application to analysis of Alzheimer's disease.

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Journal:  Neuroimage       Date:  2010-12-10       Impact factor: 6.556

8.  Genetic, structural and functional imaging biomarkers for early detection of conversion from MCI to AD.

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9.  Automated hippocampal shape analysis predicts the onset of dementia in mild cognitive impairment.

Authors:  Sergi G Costafreda; Ivo D Dinov; Zhuowen Tu; Yonggang Shi; Cheng-Yi Liu; Iwona Kloszewska; Patrizia Mecocci; Hilkka Soininen; Magda Tsolaki; Bruno Vellas; Lars-Olof Wahlund; Christian Spenger; Arthur W Toga; Simon Lovestone; Andrew Simmons
Journal:  Neuroimage       Date:  2011-01-25       Impact factor: 6.556

10.  Robust Diffeomorphic Mapping via Geodesically Controlled Active Shapes.

Authors:  Daniel J Tward; Jun Ma; Michael I Miller; Laurent Younes
Journal:  Int J Biomed Imaging       Date:  2013-04-03
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  18 in total

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2.  Engagement in Enriching Early-Life Activities Is Associated With Larger Hippocampal and Amygdala Volumes in Community-Dwelling Older Adults.

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Authors:  Xiaoying Tang; Vijay R Varma; Michael I Miller; Michelle C Carlson
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Review 4.  A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages.

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5.  APOE Affects the Volume and Shape of the Amygdala and the Hippocampus in Mild Cognitive Impairment and Alzheimer's Disease: Age Matters.

Authors:  Xiaoying Tang; Dominic Holland; Anders M Dale; Michael I Miller
Journal:  J Alzheimers Dis       Date:  2015       Impact factor: 4.472

6.  Predicting Imminent Progression to Clinically Significant Memory Decline Using Volumetric MRI and FDG PET.

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7.  Arterial spin labeling imaging reveals widespread and Aβ-independent reductions in cerebral blood flow in elderly apolipoprotein epsilon-4 carriers.

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8.  Regional subcortical shape analysis in premanifest Huntington's disease.

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9.  Shape and diffusion tensor imaging based integrative analysis of the hippocampus and the amygdala in Alzheimer's disease.

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Review 10.  Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.

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