AI-DERIVED AUTOMATED QUANTIFICATION OF CARDIAC CHAMBERS AND MYOCARDIUM FROM NON-CONTRAST CT: PREDICTION OF ADVERSE CARDIOVASCULAR EVENTS IN ASYMPTOMATIC SUBJECTS
Therapeutic Area: ASCVD/CVD Risk Assessment Background: The significance of myocardial mass and chamber volumes from non-contrast computed tomography (CT) for predicting major adverse cardiovascular events (MACE) has not been studied. Our objective was to evaluate the role of artificial intelligence...
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Published: |
Elsevier,
2024-09-01T00:00:00Z.
|
| Subjects: | |
| Online Access: | Connect to this object online. |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Therapeutic Area: ASCVD/CVD Risk Assessment Background: The significance of myocardial mass and chamber volumes from non-contrast computed tomography (CT) for predicting major adverse cardiovascular events (MACE) has not been studied. Our objective was to evaluate the role of artificial intelligence-enabled multi-chamber cardiac volumetry from non-contrast CT for long-term risk stratification in asymptomatic subjects without known coronary artery disease. Methods: Our study included 2022 asymptomatic individuals (55.6±9.0 years; 59.2% male) from the EISNER (Early Identification of Subclinical Atherosclerosis by Noninvasive Imaging Research) trial. The multi-chamber cardiac volumetry was performed using deep-learning algorithms from routine non-contrast CT scans for coronary artery calcium scoring. MACE was defined as myocardial infarction, late (>180 days) revascularization, and cardiac death. Results: A total of 215 individuals (11%) suffered MACE at a mean follow-up of 13.9±3 years. Individuals with MACE, as compared to those without MACE, had higher left ventricle (LV) myocardial mass (118.1 g vs 106.9 g, p<0.001) and higher LV chamber volume (105.0 cm3 vs. 96.9 cm3, p<0.001). In multivariable logistic regression, LV myocardial mass (HR 1.19[95% CI 1.04-1.36] per standard deviation) and left ventricular volume (HR 1.16 [95% CI 1.02-1.32] per standard deviation) were independent predictors of MACE. Patients with the highest LV myocardial mass (> 118.1 g) and chamber (> 105.0 cm3) volume, as divided into tertiles, presented a steep increase in the risk of MACE (log rank p<0.001). Conclusions: LV volume and myocardial mass quantified automatically by AI from routine non-contrast CT independently predicted long-term MACE risk in asymptomatic patients without known coronary artery disease. AI-derived LV measurements from routine non-contrast cardiac CT without physician interaction may improve the risk stratification of MACE. |
|---|---|
| Item Description: | 2666-6677 10.1016/j.ajpc.2024.100850 |