Evidence map›Paper›PMID 28549448›Full record

ArticleBMC medical imaging2017

Statistical Permutation-based Artery Mapping (SPAM): a novel approach to evaluate imaging signals in the vessel wall.

Robert Seifert, Aaron Scherzinger, Friedemann Kiefer, Sven Hermann, Xiaoyi Jiang, Michael A Schäfers

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Article in BMC medical imaging, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Robert SeifertEuropean Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany. robert.seifert@uni-muenster.de.ORCID 0000-0001-5985-7701
Aaron ScherzingerDepartment of Mathematics and Computer Science, University of Münster, Münster, Germany.
Friedemann KieferMax Planck Institute for Molecular Biomedicine, Münster, Germany.
Sven HermannEuropean Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany.
Xiaoyi JiangEuropean Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany.
Michael A SchäfersEuropean Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCardiovascular 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.

methodsWe 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.

resultsWe 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.

conclusionsWe 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.

Indexed as

AnimalsAortaAtherosclerosisHumansMiceModels, AnimalModels, StatisticalMolecular ImagingOptical ImagingAtherosclerosisMolecular imagingPermutation testingThreshold free cluster enhancement (TFCE)

Identifiers

PMID28549448
PMCPMC5446712

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.