Dataset Information

Multimodality Imaging for the Assessment of Severe Aortic Stenosis.

ABSTRACT: Aortic stenosis is the most common type of valvular heart disease. Aortic stenosis is characterized both by progressive valve narrowing and the left ventricular remodeling response that ensues. In aortic stenosis, therapeutic decision essentially depends on symptomatic status, stenosis severity, and status of left ventricular systolic function. Imaging is fundamental for the initial diagnostic work-up, follow-up, and selection of the optimal timing and type of intervention. Noninvasive imaging has played a pivotal role in enhancing our understanding of the complex pathophysiology underlying aortic stenosis, as well as disease progression in both the valve and myocardium. The present review provides the application of multimodality imaging in aortic stenosis.

SUBMITTER: Park SJ

PROVIDER: S-EPMC6795563 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Multimodality Imaging for the Assessment of Severe Aortic Stenosis.

Park Sung Ji SJ Dweck Marc R MR

Journal of cardiovascular imaging 20191001 4

Aortic stenosis is the most common type of valvular heart disease. Aortic stenosis is characterized both by progressive valve narrowing and the left ventricular remodeling response that ensues. In aortic stenosis, therapeutic decision essentially depends on symptomatic status, stenosis severity, and status of left ventricular systolic function. Imaging is fundamental for the initial diagnostic work-up, follow-up, and selection of the optimal timing and type of intervention. Noninvasive imaging h ...[more]

PMID: 31614393

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Project description:Severe aortic stenosis (AS) is prevalent in adults ≥ 65 years, a significant cause of morbidity and mortality, with no medical therapy. Lipid and proteomic alterations of human AS tissue were determined using mass spectrometry imaging (MSI) and liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) to understand histopathology, potential biomarkers of disease, and progression from non-calcified to calcified phenotype. A reproducible MSI method was developed using healthy murine aortic valves (n = 3) and subsequently applied to human AS (n = 2). Relative lipid levels were spatially mapped and associated with different microdomains. Proteomics for non-calcified and calcified microdomains were performed to ascertain differences in expression. Increased pro-osteogenic and inflammatory lysophosphatidylcholine (LPC) 16:0 and 18:0 were co-localized with calcified microdomains. Proteomics analysis identified differential patterns in calcified microdomains with high LPC and low cholesterol as compared to non-calcified microdomains with low LPC and high cholesterol. Calcified microdomains had higher levels of: apolipoproteins (Apo) B-100 (p < 0.001) and Apo A-IV (p < 0.001), complement C3 and C4-B (p < 0.001), C5 (p = 0.007), C8 beta chain (p = 0.013) and C9 (p = 0.010), antithrombotic proteins alpha-2-macroglobulin (p < 0.0001) and antithrombin III (p = 0.002), and higher anti-calcific fetuin-A (p = 0.02), while the osteoblast differentiating factor transgelin (p < 0.0001), extracellular matrix proteins versican, prolargin, and lumican ( p < 0.001) and regulator protein complement factor H (p < 0.001) were higher in non-calcified microdomains. A combined lipidomic and proteomic approach provided insight into factors potentially contributing to progression from non-calcified to calcific disease in severe AS. Additional studies of these candidates and protein networks could yield new targets for slowing progression of AS.

Dataset Information

Multimodality Imaging for the Assessment of Severe Aortic Stenosis.

Publications

Multimodality Imaging for the Assessment of Severe Aortic Stenosis.

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