4.7 Article

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

Journal

SCIENTIFIC REPORTS
Volume 8, Issue -, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41598-018-29295-9

Keywords

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Funding

  1. European Union's Seventh Framework Programme [611005]
  2. Innovate UK [101685]
  3. ADNI (National Institutes of Health) [U01 AG024904]
  4. DOD ADNI (Department of Defense) [W81XWH-12-2-0012]
  5. National Institute on Aging
  6. National Institute of Biomedical Imaging and Bioengineering
  7. AbbVie
  8. Alzheimer's Association
  9. Alzheimer's Drug Discovery Foundation
  10. Araclon Biotech
  11. BioClinica, Inc.
  12. Biogen
  13. Bristol-Myers Squibb Company
  14. CereSpir, Inc.
  15. Cogstate
  16. Eisai Inc.
  17. Elan Pharmaceuticals, Inc.
  18. Eli Lilly and Company
  19. EuroImmun
  20. F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.
  21. Fujirebio
  22. GE Healthcare
  23. IXICO Ltd.
  24. Janssen Alzheimer Immunotherapy Research & Development, LLC.
  25. Johnson & Johnson Pharmaceutical Research & Development LLC.
  26. Lumosity
  27. Lundbeck
  28. Merck Co., Inc.
  29. Meso Scale Diagnostics, LLC.
  30. NeuroRx Research
  31. Neurotrack Technologies
  32. Novartis Pharmaceuticals Corporation
  33. Pfizer Inc.
  34. Piramal Imaging
  35. Servier
  36. Takeda Pharmaceutical Company
  37. Transition Therapeutics
  38. Canadian Institutes of Health Research
  39. Innovate UK [101685] Funding Source: UKRI

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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.

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