Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Authors

Ines Mahjoub, University of Dundee
Mohamed Ali Mahjoub, Université de Sousse
Islem Rekik, University of Dundee
Michael Weiner, University of California, San Francisco
Paul Aisen, UC San Diego School of Medicine
Ronald Petersen, Mayo Clinic
Cliford Jack, Mayo Clinic in Rochester, Minnesota
William Jagust, University of California, Berkeley
John Trojanowki, University of Pennsylvania
Arthur Toga, University of Southern California
Laurel Beckett, University of California, Davis
Robert Green, Brigham and Women's Hospital
Andrew Saykin, Indiana University Bloomington
John Morris, Washington University in St. Louis
Leslie Shaw, Washington University in St. Louis
Jefrey Kaye, Oregon Health & Science University
Joseph Quinn, Oregon Health & Science University
Lisa Silbert, Oregon Health & Science University
Betty Lind, Oregon Health & Science University
Raina Carter, Oregon Health & Science University
Sara Dolen, Oregon Health & Science University
Lon Schneider, Oregon Health & Science University
Sonia Pawluczyk, University of Southern California
Mauricio Beccera, University of Southern California
Liberty Teodoro, University of Southern California
Bryan Spann, University of Southern California
James Brewer, University of California, San Diego
Helen Vanderswag, University of California, San Diego
Adam Fleisher, University of California, San Diego
Judith Heidebrink, University of Michigan, Ann Arbor
Joanne Lord, University of Michigan, Ann Arbor
Sara Mason, Mayo Clinic in Rochester, Minnesota

Document Type

Article

Publication Date

12-1-2018

Journal

Scientific Reports

Volume

8

Issue

1

URL with Digital Object Identifier

10.1038/s41598-018-21568-7

Abstract

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer's disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, 'shape connections' between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus.

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