Beyond Stress Ischemia: Unveiling the Multifaceted Nature of Coronary Vulnerable Plaques Using Cardiac Computed Tomography.
Gianluigi NapoliSaima MushtaqPaolo BasileMaria Cristina CarellaDaniele De FeoMichele Davide LatorreAndrea BaggianoMarco Matteo CicconeGianluca PontoneAndrea Igoren GuaricciPublished in: Journal of clinical medicine (2024)
Historically, cardiovascular prevention has been predominantly focused on stress-induced ischemia, but recent trials have challenged this paradigm, highlighting the emerging role of vulnerable, non-flow-limiting coronary plaques, leading to a shift towards integrating plaque morphology with functional data into risk prediction models. Coronary computed tomography angiography (CCTA) represents a high-resolution, low-risk, and largely available non-invasive modality for the precise delineation of plaque composition, morphology, and inflammatory activity, further enhancing our ability to stratify high-risk plaque and predict adverse cardiovascular outcomes. Coronary artery calcium (CAC) scoring, derived from CCTA, has emerged as a promising tool for predicting future cardiovascular events in asymptomatic individuals, demonstrating incremental prognostic value beyond traditional cardiovascular risk factors in terms of myocardial infarction, stroke, and all-cause mortality. Additionally, CCTA-derived information on adverse plaque characteristics, geometric characteristics, and hemodynamic forces provides valuable insights into plaque vulnerability and seems promising in guiding revascularization strategies. Additionally, non-invasive assessments of epicardial and pericoronary adipose tissue (PCAT) further refine risk stratification, adding prognostic significance to coronary artery disease (CAD), correlating with plaque development, vulnerability, and rupture. Moreover, CT imaging not only aids in risk stratification but is now emerging as a screening tool able to monitor CAD progression and treatment efficacy over time. Thus, the integration of CAC scoring and PCAT evaluation into risk stratification algorithms, as well as the identification of high-risk plaque morphology and adverse geometric and hemodynamic characteristics, holds promising results for guiding personalized preventive interventions, helping physicians in identifying high-risk individuals earlier, tailoring lifestyle and pharmacological interventions, and improving clinical outcomes in their patients.
Keyphrases
- coronary artery disease
- cardiovascular events
- percutaneous coronary intervention
- coronary artery bypass grafting
- coronary artery
- high resolution
- stress induced
- computed tomography
- adipose tissue
- cardiovascular risk factors
- physical activity
- end stage renal disease
- left ventricular
- metabolic syndrome
- machine learning
- primary care
- heart failure
- chronic kidney disease
- healthcare
- aortic stenosis
- newly diagnosed
- cardiovascular disease
- positron emission tomography
- ejection fraction
- image quality
- type diabetes
- pulmonary artery
- peritoneal dialysis
- pulmonary hypertension
- skeletal muscle
- dual energy
- deep learning
- antiretroviral therapy
- health information
- smoking cessation
- liquid chromatography