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          Institute: MPI für molekulare Biomedizin     Collection: Jahrbuch 2018 (publ. 2017, arch)     Display Documents



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ID: 744105.0, MPI für molekulare Biomedizin / Jahrbuch 2018 (publ. 2017, arch)
Statistical Permutation-based Artery Mapping (SPAM): a novel approach to evaluate imaging signals in the vessel wall
Authors:Seifert, R.; Scherzinger, A.; Kiefer, F.; Hermann, S.; Jiang, X.; Schafers, M. A.
Date of Publication (YYYY-MM-DD):2017-05-26
Title of Journal:BMC Med Imaging
Volume:17
Issue / Number:1
Start Page:36
Review Status:Internal review
Audience:Not Specified
Abstract / Description:BACKGROUND: Cardiovascular diseases are the leading cause of death worldwide. A prominent cause of cardiovascular events is atherosclerosis, a chronic inflammation of the arterial wall that leads to the formation of so called atherosclerotic plaques. There is a strong clinical need to develop new, non-invasive vascular imaging techniques in order to identify high-risk plaques, which might escape detection using conventional methods based on the assessment of the luminal narrowing. In this context, molecular imaging strategies based on fluorescent tracers and fluorescence reflectance imaging (FRI) seem well suited to assess molecular and cellular activity. However, such an analysis demands a precise and standardized analysis method, which is orientated on reproducible anatomical landmarks, ensuring to compare equivalent regions across different subjects. METHODS: We propose a novel method, Statistical Permutation-based Artery Mapping (SPAM). Our approach is especially useful for the understanding of complex and heterogeneous regional processes during the course of atherosclerosis. Our method involves three steps, which are (I) standardisation with an additional intensity normalization, (II) permutation testing, and (III) cluster-enhancement. Although permutation testing and cluster enhancement are already well-established in functional magnetic resonance imaging, to the best of our knowledge these strategies have so far not been applied in cardiovascular molecular imaging. RESULTS: We tested our method using FRI images of murine aortic vessels in order to find recurring patterns in atherosclerotic plaques across multiple subjects. We demonstrate that our pixel-wise and cluster-enhanced testing approach is feasible and useful to analyse tracer distributions in FRI data sets of aortic vessels. CONCLUSIONS: We expect our method to be a useful tool within the field of molecular imaging of atherosclerotic plaques since cluster-enhanced permutation testing is a powerful approach for finding significant differences of tracer distributions in inflamed atherosclerotic vessels.
Free Keywords:Atherosclerosis; Molecular imaging; Permutation testing; Threshold free cluster enhancement (TFCE)
External Publication Status:published
Document Type:Article
Communicated by:MPI für molekulare Biomedizin
Affiliations:MPI für molekulare Biomedizin
External Affiliations:Department of Mathematics and Computer Science, University of Munster, Munster, Germany. Max Planck Institute for Molecular Biomedicine, Munster, Germany. DFG Cluster of Excellence 1003 'CiM - Cells in Motion', Munster, Germany. European Institute for Molecular Imaging (EIMI), University of Munster, Munster, Germany. Department of Nuclear Medicine, University Hospital Munster, Munster, Germany.
Identifiers:ISSN:1471-2342 (Electronic) 1471-2342 (Linking) %R 10.1... [ID No:1]
URL:https://www.ncbi.nlm.nih.gov/pubmed/28549448 [ID No:2]
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