AI-Defined Cardiac Anatomy Improves Risk Stratification of Hybrid Perfusion Imaging.
JACC Cardiovasc Imaging
; 17(7): 780-791, 2024 Jul.
Article
en En
| MEDLINE
| ID: mdl-38456877
ABSTRACT
BACKGROUND:
Computed tomography attenuation correction (CTAC) improves perfusion quantification of hybrid myocardial perfusion imaging by correcting for attenuation artifacts. Artificial intelligence (AI) can automatically measure coronary artery calcium (CAC) from CTAC to improve risk prediction but could potentially derive additional anatomic features.OBJECTIVES:
The authors evaluated AI-based derivation of cardiac anatomy from CTAC and assessed its added prognostic utility.METHODS:
The authors considered consecutive patients without known coronary artery disease who underwent single-photon emission computed tomography/computed tomography (CT) myocardial perfusion imaging at 3 separate centers. Previously validated AI models were used to segment CAC and cardiac structures (left atrium, left ventricle, right atrium, right ventricular volume, and left ventricular [LV] mass) from CTAC. They evaluated associations with major adverse cardiovascular events (MACEs), which included death, myocardial infarction, unstable angina, or revascularization.RESULTS:
In total, 7,613 patients were included with a median age of 64 years. During a median follow-up of 2.4 years (IQR 1.3-3.4 years), MACEs occurred in 1,045 (13.7%) patients. Fully automated AI processing took an average of 6.2 ± 0.2 seconds for CAC and 15.8 ± 3.2 seconds for cardiac volumes and LV mass. Patients in the highest quartile of LV mass and left atrium, LV, right atrium, and right ventricular volume were at significantly increased risk of MACEs compared to patients in the lowest quartile, with HR ranging from 1.46 to 3.31. The addition of all CT-based volumes and CT-based LV mass improved the continuous net reclassification index by 23.1%.CONCLUSIONS:
AI can automatically derive LV mass and cardiac chamber volumes from CT attenuation imaging, significantly improving cardiovascular risk assessment for hybrid perfusion imaging.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Enfermedad de la Arteria Coronaria
/
Inteligencia Artificial
/
Valor Predictivo de las Pruebas
/
Imagen de Perfusión Miocárdica
/
Calcificación Vascular
/
Tomografía Computarizada por Tomografía Computarizada de Emisión de Fotón Único
/
Angiografía por Tomografía Computarizada
Límite:
Aged
/
Female
/
Humans
/
Male
/
Middle aged
Idioma:
En
Revista:
JACC Cardiovasc Imaging
Asunto de la revista:
ANGIOLOGIA
/
CARDIOLOGIA
/
DIAGNOSTICO POR IMAGEM
Año:
2024
Tipo del documento:
Article
País de afiliación:
Canadá