A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography

BACKGROUND: Coronary inflammation induces dynamic changes in the balance between water and lipid content in perivascular adipose tissue (PVAT), as captured by perivascular Fat Attenuation Index (FAI) in standard coronary CT angiography (CCTA). However, inflammation is not the only process involved i...

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Detalles Bibliográficos
Autores principales: Oikonomou, Evangelos K, Williams, Michelle C, Kotanidis, Christos P, Desai, Milind Y, Marwan, Mohamed, Antonopoulos, Alexios S, Thomas, Katharine E, Thomas, Sheena, Akoumianakis, Ioannis, Fan, Lampson M, Kesavan, Sujatha, Herdman, Laura, Alashi, Alaa, Centeno, Erika Hutt, Lyasheva, Maria, Griffin, Brian P, Flamm, Scott D, Shirodaria, Cheerag, Sabharwal, Nikant, Kelion, Andrew, Dweck, Marc R, Van Beek, Edwin J R, Deanfield, John, Hopewell, Jemma C, Neubauer, Stefan, Channon, Keith M, Achenbach, Stephan, Newby, David E, Antoniades, Charalambos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Fast Track Clinical Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6855141/
https://www.ncbi.nlm.nih.gov/pubmed/31504423
http://dx.doi.org/10.1093/eurheartj/ehz592

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