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JACC Cardiovasc Imaging ; 17(2): 165-175, 2024 Feb.
Artículo en Inglés | MEDLINE | ID: mdl-37410009

RESUMEN

BACKGROUND: With growing adoption of coronary computed tomographic angiography (CTA), there is increasing evidence for and interest in the prognostic importance of atherosclerotic plaque volume. Manual tools for plaque segmentation are cumbersome, and their routine implementation in clinical practice is limited. OBJECTIVES: The aim of this study was to develop nomographic quantitative plaque values from a large consecutive multicenter cohort using coronary CTA. METHODS: Quantitative assessment of total atherosclerotic plaque and plaque subtype volumes was performed in patients undergoing clinically indicated coronary CTA, using an Artificial Intelligence-Enabled Quantitative Coronary Plaque Analysis tool. RESULTS: A total of 11,808 patients were included in the analysis; their mean age was 62.7 ± 12.2 years, and 5,423 (45.9%) were women. The median total plaque volume was 223 mm3 (IQR: 29-614 mm3) and was significantly higher in male participants (360 mm3; IQR: 78-805 mm3) compared with female participants (108 mm3; IQR: 10-388 mm3) (P < 0.0001). Total plaque increased with age in both male and female patients. Younger patients exhibited a higher prevalence of noncalcified plaque. The distribution of total plaque volume and its components was reported in every decile by age group and sex. CONCLUSIONS: The authors developed pragmatic age- and sex-stratified percentile nomograms for atherosclerotic plaque measures using findings from coronary CTA. The impact of age and sex on total plaque and its components should be considered in the risk-benefit analysis when treating patients. Artificial Intelligence-Enabled Quantitative Coronary Plaque Analysis work flows could provide context to better interpret coronary computed tomographic angiographic measures and could be integrated into clinical decision making.


Asunto(s)
Enfermedad de la Arteria Coronaria , Placa Aterosclerótica , Humanos , Masculino , Femenino , Persona de Mediana Edad , Anciano , Enfermedad de la Arteria Coronaria/diagnóstico por imagen , Enfermedad de la Arteria Coronaria/epidemiología , Angiografía Coronaria/métodos , Inteligencia Artificial , Valor Predictivo de las Pruebas , Angiografía por Tomografía Computarizada/métodos , Tomografía Computarizada por Rayos X
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