Dataset Information

New methods to image unstable atherosclerotic plaques.

ABSTRACT: Atherosclerotic plaque rupture is the primary mechanism responsible for myocardial infarction and stroke, the top two killers worldwide. Despite being potentially fatal, the ubiquitous prevalence of atherosclerosis amongst the middle aged and elderly renders individual events relatively rare. This makes the accurate prediction of MI and stroke challenging. Advances in imaging techniques now allow detailed assessments of plaque morphology and disease activity. Both CT and MR can identify certain unstable plaque characteristics thought to be associated with an increased risk of rupture and events. PET imaging allows the activity of distinct pathological processes associated with atherosclerosis to be measured, differentiating patients with inactive and active disease states. Hybrid integration of PET with CT or MR now allows for an accurate assessment of not only plaque burden and morphology but plaque biology too. In this review, we discuss how these advanced imaging techniques hold promise in redefining our understanding of stable and unstable coronary artery disease beyond symptomatic status, and how they may refine patient risk-prediction and the rationing of expensive novel therapies.

SUBMITTER: Andrews JPM

PROVIDER: S-EPMC6463488 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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New methods to image unstable atherosclerotic plaques.

Andrews Jack P M JPM Fayad Zahi A ZA Dweck Marc R MR

Atherosclerosis 20180314

Atherosclerotic plaque rupture is the primary mechanism responsible for myocardial infarction and stroke, the top two killers worldwide. Despite being potentially fatal, the ubiquitous prevalence of atherosclerosis amongst the middle aged and elderly renders individual events relatively rare. This makes the accurate prediction of MI and stroke challenging. Advances in imaging techniques now allow detailed assessments of plaque morphology and disease activity. Both CT and MR can identify certain ...[more]

PMID: 29602139

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Project description:Atherosclerosis is a chronic inflammatory disease with high prevalence and mortality. The rupture of atherosclerotic plaque is the main reason for the clinical events caused by atherosclerosis. Making clear the transcriptomic and proteomic profiles between the stabe and unstable atherosclerotic plaques is crucial to prevent the clinical manifestations. In the present study, 5 stable and 5 unstable human carotid atherosclerotic plaques were obtained by carotid endarterectomy. The samples were used for the whole transcriptome sequencing (RNA-Seq) by the Next-Generation Sequencing using the Illumina HiSeq, and for proteome analysis by HPLC-MS/MS. The lncRNA-targeted genes and circRNA-originated genes were identified by analyzing their location and sequence. Gene Ontology and KEGG enrichment was carried out to analyze the functions of differentially expressed RNAs and proteins. The protein-protein interactions (PPI) network was constructed by the online tool STRING. The consistency of transcriptome and proteome were analyzed, and the lncRNA/circRNA-miRNA-mRNA interactions were predicted. As a result, 202 mRNAs, 488 lncRNAs, 91 circRNAs, and 293 proteins were identified to be differentially expressed between stable and unstable atherosclerotic plaques. The 488 lncRNAs might target 381 protein-coding genes by cis-acting mechanisms. Sequence analysis indicated the 91 differentially expressed circRNAs were originated from 97 protein-coding genes. These differentially expressed RNAs and proteins were mainly enriched in the terms of the cellular response to stress or stimulus, the regulation of gene transcription, the immune response, the nervous system functions, the hematologic activities, and the endocrine system. These results were consistent with the previous reported data in the dataset GSE41571. Further analysis identified CD5L, S100A12, CKB (target gene of lncRNA MSTRG.11455.17), CEMIP (target gene of lncRNA MSTRG.12845), and SH3GLB1 (originated gene of hsacirc_000411) to be critical genes in regulating the stability of atherosclerotic plaques. Our results provided a comprehensive transcriptomic and proteomic knowledge on the stability of atherosclerotic plaques.

Project description:BackgroundDuring atherosclerosis, the narrowing of the arterial lumen is observed through the accumulation of bio compounds and the formation of plaque within artery walls. A non-linear optical imaging modality (NLOM), coherent anti-stokes Raman scattering (CARS) microscopy, can be used to image lipid-rich structures commonly found in atherosclerotic plaques. By matching the lipid's molecular vibrational frequencies (CH bonds), it is possible to map the accumulation of lipid-rich structures without the need for exogenous labelling and/or processing of the samples. CARS allows for the visualization of the morphological features of plaque. In combination with supervised machine learning, CARS imaged morphological features can be used to characterize the progression of atherosclerotic plaques. RESULTS: Based on a set of label-free CARS images of atherosclerotic plaques (i.e. foam cell clusters) from a Watanabe heritable hyperlipidemic rabbit model, we developed an automated pipeline to classify atherosclerotic lesions based on their major morphological features. Our method uses image preprocessing to first improve the quality of the CARS-imaged plaque, followed by the segmentation of the plaque using Otsu thresholding, marker-controlled watershed, K-means segmentation and a novel independent foam cell thresholding segmentation. To define relevant morphological features, 27 quantitative features were extracted and further refined by a novel coefficient of variation feature refinement method in accordance with filter-type feature selection. Refined morphological features were supplied into three supervised machine learning algorithms; K-nearest neighbour, support vector machine and decision tree classifier. The classification pipeline showcased the ability to exploit relevant plaque morphological features to accurately classify 3 pre-defined stages of atherosclerosis: early fatty streak development (EFS) and advancing atheroma (AA) with a greater than 85% class accuracy CONCLUSIONS: Through the combination of CARS microscopy and computational methods, a powerful classification tool was developed to identify the progression of atherosclerotic plaque in an automated manner. Using a curated dataset, the classification pipeline demonstrated the ability to differentiate between EFS, EF and AA. Thus, presenting the opportunity to classify the onset of atherosclerosis at an earlier stage of development.

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New methods to image unstable atherosclerotic plaques.

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New methods to image unstable atherosclerotic plaques.

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