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

BMC Medical Imaging

Research Article

Aaron Scherzinger¹  Robert Seifert²  Sven Hermann³  Michael A. Schäfers⁴  Xiaoyi Jiang⁵  Friedemann Kiefer⁶ 

[1] Department of Mathematics and Computer Science, University of Münster, Münster, Germany;European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany;European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany;DFG Cluster of Excellence 1003 ’CiM - Cells in Motion’, Münster, Germany;European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany;DFG Cluster of Excellence 1003 ’CiM - Cells in Motion’, Münster, Germany;Department of Nuclear Medicine, University Hospital Münster, Münster, Germany;European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany;Department of Mathematics and Computer Science, University of Münster, Münster, Germany;DFG Cluster of Excellence 1003 ’CiM - Cells in Motion’, Münster, Germany;Max Planck Institute for Molecular Biomedicine, Münster, Germany;DFG Cluster of Excellence 1003 ’CiM - Cells in Motion’, Münster, Germany;

关键词: Atherosclerosis;    Molecular imaging;    Permutation testing;    Threshold free cluster enhancement (TFCE);   

DOI  :  10.1186/s12880-017-0207-7

 received in 2016-12-21, accepted in 2017-05-09,  发布年份 2017

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY   
© The Author(s) 2017

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