Prospective deep learning-based quantitative assessment of coronary plaque by computed tomography angiography compared with intravascular ultrasound: the REVEALPLAQUE study.
Jagat NarulaThomas D StuckeyGaku Sr NakazawaAmir AhmadiMitsuaki MatsumuraKersten PetersenSaba MirzaNicholas NgSarah MullenMichiel SchaapJonathan LeipsicCampbell RogersCharles A TaylorHarout YacoubHimanshu GuptaHitoshi MatsuoSarah RinehartAkiko MaeharaPublished in: European heart journal. Cardiovascular Imaging (2024)
AI-enabled CCTA quantification and characterization of atherosclerosis demonstrated strong agreement with IVUS reference standard measurements. This tool may prove effective for accurate evaluation of coronary atherosclerotic burden and cardiovascular risk assessment.
Keyphrases
- coronary artery
- coronary artery disease
- deep learning
- risk assessment
- artificial intelligence
- magnetic resonance imaging
- cardiovascular disease
- machine learning
- high resolution
- heavy metals
- computed tomography
- magnetic resonance
- convolutional neural network
- aortic stenosis
- risk factors
- aortic valve
- atrial fibrillation
- climate change
- ultrasound guided
- left ventricular
- transcatheter aortic valve replacement