Comparison of Different Hypotheses Regarding the Spread of Alzheimer's Disease Using Markov Random Fields and Multimodal Imaging.
Alzheimer's disease (AD) is characterized by a cascade of pathological processes that can be assessed in vivo using different neuroimaging methods. Recent research suggests a systematic sequence of pathogenic events on a global biomarker level, but little is known about the associations and dependen...
| Publicado en: | Journal of Alzheimer's Disease Vol. 65; no. 3; pp. 731 - 747 |
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| Autores principales: | , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Sage Publications Inc.
2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=131737565&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 131737565 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13872877 FLR jtl: Journal of Alzheimer's Disease issn: 13872877 maglogo: N pubinfo: dt: 2018 vid: 65 iid: 3 pid: 20732 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 131737565 131737565 NLM28697557 131737565 10.3233/JAD-161197 NLM28697557 131737565 ppf: 731 ppct: 16 formats: tig: atl: Comparison of Different Hypotheses Regarding the Spread of Alzheimer's Disease Using Markov Random Fields and Multimodal Imaging. aug: au: Dyrba, Martin Grothe, Michel J. Mohammadi, Abdolreza Binder, Harald Kirste, Thomas Teipel, Stefan J. affil: German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Rostock, Germany sug: subj: Models, Statistical Diagnostic Imaging Alzheimer's Disease Alzheimer's Disease Physiopathology Models, Biological Magnetic Resonance Imaging Aged Brain Physiopathology Brain Tomography, Emission-Computed Male Probability Female Human Validation Studies Comparative Studies Evaluation Research Multicenter Studies Clinical Assessment Tools Scales Funding Source Aged: 65+ years Male Female ab: Alzheimer's disease (AD) is characterized by a cascade of pathological processes that can be assessed in vivo using different neuroimaging methods. Recent research suggests a systematic sequence of pathogenic events on a global biomarker level, but little is known about the associations and dependencies of distinct lesion patterns on a regional level. Markov random fields are a probabilistic graphical modeling approach that represent the interaction between individual random variables by an undirected graph. We propose the novel application of this approach to study the interregional associations and dependencies between multimodal imaging markers of AD pathology and to compare different hypotheses regarding the spread of the disease. We retrieved multimodal imaging data from 577 subjects enrolled in the Alzheimer's Disease Neuroimaging Initiative. Mean amyloid load (AV45-PET), glucose metabolism (FDG-PET), and gray matter volume (MRI) were calculated for the six principle nodes of the default mode network- a functional network of brain regions that appears to be preferentially targeted by AD. Multimodal Markov random field models were developed for three different hypotheses regarding the spread of the disease: the "intraregional evolution model", the "trans-neuronal spread" hypothesis, and the "wear-and-tear" hypothesis. The model likelihood to reflect the given data was evaluated using tenfold cross-validation with 1,000 repetitions. The most likely graph structure contained the posterior cingulate cortex as main hub region with edges to various other regions, in accordance with the "wear-and-tear" hypothesis of disease vulnerability. Probabilistic graphical models facilitate the analysis of interactions between several variables in a network model and therefore afford great potential to complement traditional multiple regression analyses in multimodal neuroimaging research. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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