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Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
Published on: August 28, 2018
Prevalence and Prognostic Value of Incidentally Detected Coronary Artery Calcium Using Artificial Intelligence Among
Brittany N Weber1, David W Biery2, Milena Petranovic3
1Heart and Vascular Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Insights
Coronary artery calcium (CAC) scoring, detected by AI, is common in immune-mediated inflammatory diseases (IMIDs) and predicts mortality and cardiovascular events, aiding risk assessment in this high-risk group.
Area of Science:
- Cardiology
- Immunology
- Radiology
Background:
- Coronary artery calcium (CAC) scoring is a known cardiovascular risk predictor in the general population.
- Its prognostic value in immune-mediated inflammatory diseases (IMIDs) remains undercharacterized.
Purpose of the Study:
- To evaluate the prevalence of CAC using an AI algorithm on routine chest CT scans in IMID patients.
- To assess the association between CAC and adverse cardiovascular events in this population.
Main Methods:
- Retrospective cohort study of 2,546 patients (40-70 years) with IMIDs (lupus, RA, psoriatic disease) without prior atherosclerotic cardiovascular disease.
- CAC presence and severity quantified using a validated AI algorithm (CAC-AI).
- Cox proportional hazards modeling assessed associations of CAC-AI categories (0, 1-99, ≥100) with all-cause mortality and major adverse cardiovascular events (MACE), adjusted for CV risk factors.
Main Results:
- 53% of patients had detectable CAC-AI; only 6.0% were on statin therapy.
- Low CAC burden (CAC-AI = 1-99) significantly increased risk for all-cause mortality (aHR: 1.41) and MACE (aHR: 2.05).
- Higher CAC burden (CAC-AI ≥100) showed even greater risk for all-cause mortality (aHR: 2.45) and MACE (aHR: 3.24).
Conclusions:
- Incidental CAC, detected by AI, is highly prevalent in IMID patients.
- CAC-AI is significantly associated with increased all-cause mortality and MACE in this population.
- CAC-AI offers valuable prognostic information for risk stratification and treatment in IMID patients.
Background:
Coronary artery calcium (CAC) scoring is strongly associated with cardiovascular (CV) events among the general population; however, its prognostic value among individuals with immune-mediated inflammatory diseases (IMIDs) is not well characterized.
Objectives:
This study aims to assess the prevalence of CAC derived from routine chest computed tomography (CT) using a validated artificial intelligence (AI) algorithm and its association with adverse CV events among those with IMIDs.
Methods:
The authors studied a retrospective cohort of all patients 40 to 70 years of age with a diagnosis of systemic lupus erythematosus, rheumatoid arthritis, or psoriatic disease, and no prior atherosclerotic cardiovascular disease who underwent chest CT at 2 medical centers in Boston, Massachusetts, USA, from 2000 to 2023 as part of routine care. The presence and severity of CAC was determined using a validated AI methodology. Cox proportional hazards modeling was used to assess the association of CAC-AI categories (CAC-AI = 0, CAC-AI = 1-99, and CAC-AI ≥100) with all-cause mortality and major adverse cardiovascular events (MACE) (nonfatal myocardial infarction, coronary revascularization, nonfatal stroke, or CV mortality). All models were adjusted for age, sex, and traditional CV risk factors.
Results:
In total, 2,546 individuals with IMIDs (median age: 59 years [Q1-Q3: 53-65 years]; 1,694 [66.5%] women) were included with a median follow-up of 8.1 years. Among this cohort, 53% had CAC-AI >0 while only 6.0% were on a statin. A low burden of CAC (CAC-AI = 1-99) was associated with an increased risk of all-cause mortality (adjusted HR: 1.41; P = 0.010) and MACE (adjusted HR: 2.05; P < 0.001) with even greater risk observed among individuals with CAC-AI ≥100 (adjusted HR: 2.45; P < 0.001) and MACE (adjusted HR: 3.24; P < 0.001).
Conclusions:
Among those with IMIDs, incidental CAC-AI was highly prevalent and significantly associated with both all-cause mortality and MACE. These findings suggest that CAC-AI may provide important prognostic information, allowing for improved risk stratification and treatment within an already high-risk and undertreated population.
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