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

<p style="text-align:justify;"> <b>Background:</b> 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 angiogra...

Full description

Bibliographic Details
Main Authors:	Oikonomou, EK, Williams, MC, Kotanidis, CP, Desai, MY, Marwan, MM, Antonopoulos, AS, Thomas, KE, Thomas, S, Akoumianakis, I, Fan, LM, Kesavan, S, Herdman, L, Alashi, A, Centeno, E, Lyasheva, M, Griffin, BP, Flamm, SD, Shirodaria, C, Sabharwal, N, Kelion, A, Dweck, MR, Van Beek, EJR, Deanfield, J, Hopewell, JC, Neubauer, S, Channon, KM, Achenbach, S, Newby, DE, Antoniades, C
Format:	Journal article
Language:	English
Published:	Oxford University Press 2019

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

Similar Items