A novel arterial redox-specific machine learning-derived radiomic signature of perivascular adipose tissue predicts cardiac mortality from routine CCTA
Main Authors: | Kotanidis, CP, Akawi, N, Thomas, S, Siddique, M, Oikonomou, EK, Alashi, A, Akoutnianakis, I, Antonopoulos, AS, Krasopoulos, G, Sayeed, R, Neubauer, S, Channon, KM, Desai, MY, Antoniades, C |
---|---|
Format: | Conference item |
Language: | English |
Published: |
Oxford University Press
2020
|
Similar Items
-
Improved cardiac risk stratification in individuals with high risk plaque features using the perivascular fat attenuation index on CCTA
by: Kotanidis, CP, et al.
Published: (2020) -
Perivascular fat attenuation index mapping around the right and left coronary artery independently predict cardiac mortality
by: Kotanidis, CP, et al.
Published: (2020) -
Perivascular fat attenuation index stratifies cardiac risk associated with high-risk plaques in the CRISP-CT study
by: Oikonomou, E, et al.
Published: (2020) -
Computed tomography-based perivascular fat phenotyping identifies unstable coronary lesions and active vascular calcification
by: Oikonomou, EK, et al.
Published: (2018) -
Effects of canagliflozin on human myocardial redox signalling: clinical implications
by: Kondo, H, et al.
Published: (2021)