Journal
JOURNAL OF INTERNAL MEDICINE
Volume 273, Issue 4, Pages 396-409Publisher
WILEY
DOI: 10.1111/joim.12028
Keywords
AD; MCI; MRI; multivariate analysis; progression to AD
Categories
Funding
- InnoMed (Innovative Medicines in Europe), an Integrated Project
- European Union of the Sixth Framework programme priority, Life Sciences, Genomics and Biotechnology for Health [FP6-2004-LIFESCIHEALTH-5]
- Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health) [U01 AG024904]
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Abbott
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Alzheimer's Association
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Alzheimer's Drug Discovery Foundation
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Amorfix Life Sciences Ltd.
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Astra-Zeneca
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Bayer HealthCare
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through BioClinica, Inc.
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Biogen Idec Inc.
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Bristol-Myers Squibb Company
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Eisai Inc.
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Elan Pharmaceuticals Inc.
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Eli Lilly and Company
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through F. Hoffmann-La Roche Ltd
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through company Genentech, Inc.
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through GE Healthcare
- Innogenetics, N.V.
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Janssen Alzheimer Immunotherapy Research & Development, LLC.
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Johnson & Johnson Pharmaceutical Research & Development LLC.
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Merck Co., Inc.
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Meso Scale Diagnostics, LLC.
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Novartis Pharmaceuticals Corporation
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Pfizer Inc.
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Servier
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Synarc Inc.
- National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering through Takeda Pharmaceutical Company
- Canadian Institutes of Health Research
- NIH [30 AG010129, K01 AG030514]
- Dana Foundation
- Kuopio University Hospital
- Stockholm Medical Image Laboratory and Education (SMILE)
- NIHR Biomedical Research Centre for Mental Health at the South London
- Maudsley NHS Foundation Trust
- Institute of Psychiatry, Kings College London
- Alzheimers Research UK [ARUK-EXT2013-4] Funding Source: researchfish
- National Institute for Health Research [NF-SI-0512-10053] Funding Source: researchfish
Ask authors/readers for more resources
Spulber G, Simmons A, Muehlboeck J-S, Mecocci P, Vellas B, Tsolaki M, Kloszewska I, Soininen H, Spenger C, Lovestone S, Wahlund L-O, Westman E (University Hospital of Kuopio, Kuopio, Finland; Karolinska Institutet, Stockholm, Sweden; Institute of Psychiatry, London, UK; NIHR Biomedical Research Centre for Mental Health, London, UK; University of Perugia, Perugia, Italy; University of Toulouse, Toulouse, France; Aristotle University of Thessaloniki, Thessaloniki, Greece; Medical University of Lodz, Lodz, Poland; Karolinska Institutet, Stockholm, Sweden). An MRI-based index to measure the severity of Alzheimer's disease-like structural pattern in subjects with mild cognitive impairment. J Intern Med 2013; 273: 396-409. Background Structural magnetic resonance imaging (MRI) is sensitive to neurodegeneration and can be used to estimate the risk of converting to Alzheimer's disease (AD) in individuals with mild cognitive impairment (MCI). Brain changes in AD and prodromal AD involve a pattern of widespread atrophy. The use of multivariate analysis algorithms could enable the development of diagnostic tools based on structural MRI data. In this study, we investigated the possibility of combining multiple MRI features in the form of a severity index. Methods We used baseline MRI scans from two large multicentre cohorts (AddNeuroMed and ADNI). On the basis of volumetric and cortical thickness measures at baseline with AD cases and healthy control (CTL) subjects as training sets, we generated an MRI-based severity index using the method of orthogonal projection to latent structures (OPLS). The severity index tends to be close to 1 for AD patients and 0 for CTL subjects. Values above 0.5 indicate a more AD-like pattern. The index was then estimated for subjects with MCI, and the accuracy of classification was investigated. Results Based on the data at follow-up, 173 subjects converted to AD, of whom 112 (64.7%) were classified as AD-like and 61 (35.3%) as CTL-like. Conclusion We found that joint evaluation of multiple brain regions provided accurate discrimination between progressive and stable MCI, with better performance than hippocampal volume alone, or a limited set of features. A major challenge is still to determine optimal cut-off points for such parameters and to compare their relative reliability.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available