Structural brain imaging in Alzheimer’s disease and mild cognitive impairment: biomarker analysis and shared morphometry database

File Description SizeFormat 
s41598-018-29295-9.pdfPublished version2.61 MBAdobe PDFDownload
Title: Structural brain imaging in Alzheimer’s disease and mild cognitive impairment: biomarker analysis and shared morphometry database
Author(s): Ledig, C
Schuh, A
Guerrero
Heckemann, RA
Rueckert, D
Item Type: Journal Article
Abstract: Magnetic resonance (MR) imaging is a powerful technique for non-invasive in-vivo imaging of the human brain. We employed a recently validated method for robust cross-sectional and longitudinal segmentation of MR brain images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Specifically, we segmented 5074 MR brain images into 138 anatomical regions and extracted time-point specific structural volumes and volume change during follow-up intervals of 12 or 24 months. We assessed the extracted biomarkers by determining their power to predict diagnostic classification and by comparing atrophy rates to published meta-studies. The approach enables comprehensive analysis of structural changes within the whole brain. The discriminative power of individual biomarkers (volumes/atrophy rates) is on par with results published by other groups. We publish all quality-checked brain masks, structural segmentations, and extracted biomarkers along with this article. We further share the methodology for brain extraction (pincram) and segmentation (MALPEM, MALPEM4D) as open source projects with the community. The identified biomarkers hold great potential for deeper analysis, and the validated methodology can readily be applied to other imaging cohorts.
Publication Date: 26-Jul-2018
Date of Acceptance: 6-Jul-2018
URI: http://hdl.handle.net/10044/1/62172
DOI: https://dx.doi.org/10.1038/s41598-018-29295-9
ISSN: 2045-2322
Publisher: Nature Publishing Group
Journal / Book Title: Scientific Reports
Volume: 8
Sponsor/Funder: Commission of the European Communities
Funder's Grant Number: 611005
Copyright Statement: © 2018 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Keywords: Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
MAGNETIC-RESONANCE IMAGES
HIPPOCAMPAL ATROPHY
MR-IMAGES
SEGMENTATION APPLICATION
CLASSIFICATION
DEMENTIA
PREDICTION
ADNI
TIME
DIAGNOSIS
Publication Status: Published
Article Number: 11258
Appears in Collections:Faculty of Engineering
Computing
Department of Medicine
Faculty of Medicine



Items in Spiral are protected by copyright, with all rights reserved, unless otherwise indicated.

Creative Commons