Literature DB >> 25260848

Empowering imaging biomarkers of Alzheimer's disease.

Boris A Gutman1, Yalin Wang2, Igor Yanovsky3, Xue Hua1, Arthur W Toga4, Clifford R Jack5, Michael W Weiner6, Paul M Thompson7.   

Abstract

In a previous report, we proposed a method for combining multiple markers of atrophy caused by Alzheimer's disease into a single atrophy score that is more powerful than any one feature. We applied the method to expansion rates of the lateral ventricles, achieving the most powerful ventricular atrophy measure to date. Here, we expand our method's application to tensor-based morphometry measures. We also combine the volumetric tensor-based morphometry measures with previously computed ventricular surface measures into a combined atrophy score. We show that our atrophy scores are longitudinally unbiased with the intercept bias estimated at 2 orders of magnitude below the mean atrophy of control subjects at 1 year. Both approaches yield the most powerful biomarker of atrophy not only for ventricular measures but also for all published unbiased imaging measures to date. A 2-year trial using our measures requires only 31 (22, 43) Alzheimer's disease subjects or 56 (44, 64) subjects with mild cognitive impairment to detect 25% slowing in atrophy with 80% power and 95% confidence.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  ADNI; Alzheimer's disease; Biomarker; Drug trial; Lateral ventricles; Linear discriminant analysis; Machine learning; Mild cognitive impairment; Shape analysis; Tensor-based morphometry

Mesh:

Substances:

Year:  2014        PMID: 25260848      PMCID: PMC4268333          DOI: 10.1016/j.neurobiolaging.2014.05.038

Source DB:  PubMed          Journal:  Neurobiol Aging        ISSN: 0197-4580            Impact factor:   4.673


  50 in total

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3.  Morphometric analysis of lateral ventricles in schizophrenia and healthy controls regarding genetic and disease-specific factors.

Authors:  Martin Styner; Jeffrey A Lieberman; Robert K McClure; Daniel R Weinberger; Douglas W Jones; Guido Gerig
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4.  A nonparametric method for automatic correction of intensity nonuniformity in MRI data.

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Journal:  Neuroimage       Date:  2010-03-02       Impact factor: 6.556

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Review 1.  Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials.

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2.  Computing Univariate Neurodegenerative Biomarkers with Volumetric Optimal Transportation: A Pilot Study.

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Authors:  Clifford R Jack; Josephine Barnes; Matt A Bernstein; Bret J Borowski; James Brewer; Shona Clegg; Anders M Dale; Owen Carmichael; Christopher Ching; Charles DeCarli; Rahul S Desikan; Christine Fennema-Notestine; Anders M Fjell; Evan Fletcher; Nick C Fox; Jeff Gunter; Boris A Gutman; Dominic Holland; Xue Hua; Philip Insel; Kejal Kantarci; Ron J Killiany; Gunnar Krueger; Kelvin K Leung; Scott Mackin; Pauline Maillard; Ian B Malone; Niklas Mattsson; Linda McEvoy; Marc Modat; Susanne Mueller; Rachel Nosheny; Sebastien Ourselin; Norbert Schuff; Matthew L Senjem; Alix Simonson; Paul M Thompson; Dan Rettmann; Prashanthi Vemuri; Kristine Walhovd; Yansong Zhao; Samantha Zuk; Michael Weiner
Journal:  Alzheimers Dement       Date:  2015-07       Impact factor: 21.566

4.  Prospective longitudinal atrophy in Alzheimer's disease correlates with the intensity and topography of baseline tau-PET.

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7.  Spatial patterns of progressive brain volume loss after moderate-severe traumatic brain injury.

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8.  Group Guided Fused Laplacian Sparse Group Lasso for Modeling Alzheimer's Disease Progression.

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9.  Boosting brain connectome classification accuracy in Alzheimer's disease using higher-order singular value decomposition.

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10.  MRI-based brain atrophy rates in ADNI phase 2: acceleration and enrichment considerations for clinical trials.

Authors:  Xue Hua; Christopher R K Ching; Adam Mezher; Boris A Gutman; Derrek P Hibar; Priya Bhatt; Alex D Leow; Clifford R Jack; Matt A Bernstein; Michael W Weiner; Paul M Thompson
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  10 in total

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