Cargando…
Structural brain imaging in Alzheimer’s disease and mild cognitive impairment: biomarker analysis and shared morphometry database
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. Specifi...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6062561/ https://www.ncbi.nlm.nih.gov/pubmed/30050078 http://dx.doi.org/10.1038/s41598-018-29295-9 |
_version_ | 1783342395009531904 |
---|---|
author | Ledig, Christian Schuh, Andreas Guerrero, Ricardo Heckemann, Rolf A. Rueckert, Daniel |
author_facet | Ledig, Christian Schuh, Andreas Guerrero, Ricardo Heckemann, Rolf A. Rueckert, Daniel |
author_sort | Ledig, Christian |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6062561 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-60625612018-07-31 Structural brain imaging in Alzheimer’s disease and mild cognitive impairment: biomarker analysis and shared morphometry database Ledig, Christian Schuh, Andreas Guerrero, Ricardo Heckemann, Rolf A. Rueckert, Daniel Sci Rep Article 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. Nature Publishing Group UK 2018-07-26 /pmc/articles/PMC6062561/ /pubmed/30050078 http://dx.doi.org/10.1038/s41598-018-29295-9 Text en © The Author(s) 2018 Open Access 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/. |
spellingShingle | Article Ledig, Christian Schuh, Andreas Guerrero, Ricardo Heckemann, Rolf A. Rueckert, Daniel Structural brain imaging in Alzheimer’s disease and mild cognitive impairment: biomarker analysis and shared morphometry database |
title | Structural brain imaging in Alzheimer’s disease and mild cognitive impairment: biomarker analysis and shared morphometry database |
title_full | Structural brain imaging in Alzheimer’s disease and mild cognitive impairment: biomarker analysis and shared morphometry database |
title_fullStr | Structural brain imaging in Alzheimer’s disease and mild cognitive impairment: biomarker analysis and shared morphometry database |
title_full_unstemmed | Structural brain imaging in Alzheimer’s disease and mild cognitive impairment: biomarker analysis and shared morphometry database |
title_short | Structural brain imaging in Alzheimer’s disease and mild cognitive impairment: biomarker analysis and shared morphometry database |
title_sort | structural brain imaging in alzheimer’s disease and mild cognitive impairment: biomarker analysis and shared morphometry database |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6062561/ https://www.ncbi.nlm.nih.gov/pubmed/30050078 http://dx.doi.org/10.1038/s41598-018-29295-9 |
work_keys_str_mv | AT ledigchristian structuralbrainimaginginalzheimersdiseaseandmildcognitiveimpairmentbiomarkeranalysisandsharedmorphometrydatabase AT schuhandreas structuralbrainimaginginalzheimersdiseaseandmildcognitiveimpairmentbiomarkeranalysisandsharedmorphometrydatabase AT guerreroricardo structuralbrainimaginginalzheimersdiseaseandmildcognitiveimpairmentbiomarkeranalysisandsharedmorphometrydatabase AT heckemannrolfa structuralbrainimaginginalzheimersdiseaseandmildcognitiveimpairmentbiomarkeranalysisandsharedmorphometrydatabase AT rueckertdaniel structuralbrainimaginginalzheimersdiseaseandmildcognitiveimpairmentbiomarkeranalysisandsharedmorphometrydatabase |