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  Combined evaluation of FDG-PET and MRI improves detection and differentiation of dementia

Dukart, J., Müller, K., Horstmann, A., Barthel, H., Möller, H. E., Villringer, A., et al. (2011). Combined evaluation of FDG-PET and MRI improves detection and differentiation of dementia. PLoS One, 6(3): e18111. doi:10.1371/journal.pone.0018111.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0011-59AE-2 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002B-C577-7
Genre: Journal Article

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Dukart_CombinedEvaluation.pdf (Publisher version), 658KB
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Dukart_CombinedEvaluation.pdf
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2011
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© 2011 Dukart et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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 Creators:
Dukart, Jürgen1, Author              
Müller, Karsten1, Author              
Horstmann, Annette2, Author              
Barthel, Henryk, Author
Möller, Harald E.1, Author              
Villringer, Arno2, Author              
Sabri, Osama, Author
Schroeter, Matthias L.2, Author              
Affiliations:
1Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634558              
2Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              

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 Abstract: Introduction. Various biomarkers have been reported in recent literature regarding imaging abnormalities in different types of dementia. These biomarkers have helped to significantly improve early detection and also differentiation of various dementia syndromes. In this study, we systematically applied whole-brain and region-of-interest (ROI) based support vector machine classification separately and on combined information from different imaging modalities to improve the detection and differentiation of different types of dementia. Methods. Patients with clinically diagnosed Alzheimer's disease (AD: n = 21), with frontotemporal lobar degeneration (FTLD: n = 14) and control subjects (n = 13) underwent both [F18]fluorodeoxyglucose positron emission tomography (FDG-PET) scanning and magnetic resonance imaging (MRI), together with clinical and behavioral assessment. FDG-PET and MRI data were commonly processed to get a precise overlap of all regions in both modalities. Support vector machine classification was applied with varying parameters separately for both modalities and to combined information obtained from MR and FDG-PET images. ROIs were extracted from comprehensive systematic and quantitative meta-analyses investigating both disorders. Results. Using single-modality whole-brain and ROI information FDG-PET provided highest accuracy rates for both, detection and differentiation of AD and FTLD compared to structural information from MRI. The ROI-based multimodal classification, combining FDG-PET and MRI information, was highly superior to the unimodal approach and to the whole-brain pattern classification. With this method, accuracy rate of up to 92% for the differentiation of the three groups and an accuracy of 94% for the differentiation of AD and FTLD patients was obtained. Conclusion. Accuracy rate obtained using combined information from both imaging modalities is the highest reported up to now for differentiation of both types of dementia. Our results indicate a substantial gain in accuracy using combined FDG-PET and MRI information and suggest the incorporation of such approaches to clinical diagnosis and to differential diagnostic procedures of neurodegenerative disorders.

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Language(s): eng - English
 Dates: 2011-02-252011-03-23
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Method: -
 Identifiers: eDoc: 563090
Other: P11806
DOI: 10.1371/journal.pone.0018111
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Title: PLoS One
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Sciene
Pages: - Volume / Issue: 6 (3) Sequence Number: e18111 Start / End Page: - Identifier: ISSN: 1932-6203
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000277850