Conflicts of interest: W.J. Niessen is cofounder, part-time Chief Scientific Officer, and stock holder of Quantib BV. Other authors had no conflicts of interest to declare.
Diagnostic classification of arterial spin labeling and structural MRI in presenile early stage dementia
Version of Record online: 3 APR 2014
Copyright © 2014 Wiley Periodicals, Inc.
Human Brain Mapping
Volume 35, Issue 9, pages 4916–4931, September 2014
How to Cite
Bron, E. E., Steketee, R. M.E., Houston, G. C., Oliver, R. A., Achterberg, H. C., Loog, M., van Swieten, J. C., Hammers, A., Niessen, W. J., Smits, M., Klein, S. and for the Alzheimer's Disease Neuroimaging Initiative (2014), Diagnostic classification of arterial spin labeling and structural MRI in presenile early stage dementia. Hum. Brain Mapp., 35: 4916–4931. doi: 10.1002/hbm.22522
Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.ucla.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.ucla.edu/wpcontent/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf
- Issue online: 18 JUL 2014
- Version of Record online: 3 APR 2014
- Manuscript Accepted: 24 MAR 2014
- Manuscript Revised: 14 MAR 2014
- Manuscript Received: 17 JUL 2013
- Erasmus MC grant
- European COST Action “Arterial spin labelling Initiative in Dementia (AID)”. Grant Number: BM1103
- Alzheimer's Disease Neuroimaging Initiative (ADNI; National Institutes of Health). Grant Number: U01 AG024904
- National Institute on Aging
- National Institute of Biomedical Imaging and Bioengineering
- Alzheimer's Association
- Alzheimer's Drug Discovery Foundation
- Amorfix Life Sciences
- Astra- Zeneca
- Bayer HealthCare
- Biogen Idec
- Bristol-Myers Squibb Company
- Elan Pharmaceuticals
- Eli Lilly and Company
- F. Hoffmann-La Roche
- GE Healthcare
- Innogenetics, N.V.
- Janssen Alzheimer Immunotherapy Research & Development, LLC
- Johnson & Johnson Pharmaceutical Research & Development LLC.
- Merck & Co.
- Meso Scale Diagnostics, LLC.
- Novartis Pharmaceuticals Corporation
- Takeda Pharmaceutical Company
- Canadian Institutes of Health Research, Canada
- National Institutes of Health (www.fnih.org)
- Alzheimer's disease;
- arterial spin labeling;
- diagnostic imaging;
- frontotemporal dementia;
- magnetic resonance imaging;
- presenile dementia;
- support vector machines
Because hypoperfusion of brain tissue precedes atrophy in dementia, the detection of dementia may be advanced by the use of perfusion information. Such information can be obtained noninvasively with arterial spin labeling (ASL), a relatively new MR technique quantifying cerebral blood flow (CBF). Using ASL and structural MRI, we evaluated diagnostic classification in 32 prospectively included presenile early stage dementia patients and 32 healthy controls. Patients were suspected of Alzheimer's disease (AD) or frontotemporal dementia. Classification was based on CBF as perfusion marker, gray matter (GM) volume as atrophy marker, and their combination. These markers were each examined using six feature extraction methods: a voxel-wise method and a region of interest (ROI)-wise approach using five ROI-sets in the GM. These ROI-sets ranged in number from 72 brain regions to a single ROI for the entire supratentorial brain. Classification was performed with a linear support vector machine classifier. For validation of the classification method on the basis of GM features, a reference dataset from the AD Neuroimaging Initiative database was used consisting of AD patients and healthy controls. In our early stage dementia population, the voxelwise feature-extraction approach achieved more accurate results (area under the curve (AUC) range = 86 − 91%) than all other approaches (AUC = 57 − 84%). Used in isolation, CBF quantified with ASL was a good diagnostic marker for dementia. However, our findings indicated only little added diagnostic value when combining ASL with the structural MRI data (AUC = 91%), which did not significantly improve over accuracy of structural MRI atrophy marker by itself. Hum Brain Mapp 35:4916–4931, 2014. © 2014 Wiley Periodicals, Inc.