Key result
An elevated CAC-DAD score independently predicted MACE (HR 2.57; 95% CI 1.43-4.61; P=0.002) and improved risk prediction compared with the standard Agatston score.
Why the study?
Current CAC techniques disregard plaque distribution and the protective effects of high CAC density, prompting investigation into whether a novel CAC-dispersion and density score provides superior prognostic value to the Agatston score.
Does a novel CAC-dispersion and density (CAC-DAD) score improve prediction of major adverse cardiovascular events compared to the traditional Agatston score in patients undergoing cardiac CT?
Cross-Sectional (n=961)
Blinded analyzers
Yes
Does a novel CAC-dispersion and density (CAC-DAD) score improve prediction of major adverse cardiovascular events compared to the traditional Agatston score in patients undergoing cardiac CT?
Hazard Ratio: 2.57 (95% CI 1.43–4.61)
p-value: p=0.002
A novel deep learning-derived CAC dispersion and density score improves the prediction of major adverse cardiovascular events compared to the traditional Agatston score.
May refine MACE stratification on cardiac CT; hypothesis-generating until prospectively validated.
BACKGROUND: Coronary artery calcification (CAC) provides robust prediction for major adverse cardiovascular events (MACE), but current techniques disregard plaque distribution and protective effects of high CAC density. We investigated whether a novel CAC-dispersion and density (CAC-DAD) score will exhibit superior prognostic value compared with the Agatston score (AS) for MACE prediction. METHODS: We conducted a multicenter, retrospective, cross-sectional study of 961 patients (median age, 67 years; 61% men) who underwent cardiac computed tomography for cardiovascular or perioperative risk assessment. Blinded analyzers applied deep learning algorithms to noncontrast scans to calculate the CAC-DAD score, which adjusts for the spatial distribution of CAC and assigns a protective weight factor for lesions with ≥1000 Hounsfield units. Associations were assessed using frailty regression. RESULTS: Over a median follow-up of 30 (30–460) days, 61 patients experienced MACE (nonfatal myocardial infarction or cardiovascular mortality). An elevated CAC-DAD score (≥2050 based on optimal cutoff) captured more MACE than AS ≥400 (74% versus 57%; P =0.002). Univariable analysis revealed that an elevated CAC-DAD score, AS ≥400 and AS ≥100, age, diabetes, hypertension, and statin use predicted MACE. On multivariable analysis, only the CAC-DAD score (hazard ratio, 2.57 [95% CI, 1.43–4.61]; P =0.002), age, statins, and diabetes remained significant. The inclusion of the CAC-DAD score in a predictive model containing demographic factors and AS improved the C statistic from 0.61 to 0.66 ( P =0.008). CONCLUSIONS: The fully automated CAC-DAD score improves MACE prediction compared with the AS. Patients with a high CAC-DAD score, including those with a low AS, may be at higher risk and warrant intensification of their preventative therapies.
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Huangfu et al. (2025) conducted a cross-sectional in Cardiovascular risk (n=961). Elevated CAC-DAD score vs. Agatston score was evaluated on MACE (nonfatal myocardial infarction or cardiovascular mortality) (HR 2.57, 95% CI 1.43-4.61, p=0.002). An elevated CAC-DAD score independently predicted MACE (HR 2.57; 95% CI 1.43-4.61; P=0.002) and improved risk prediction compared with the standard Agatston score.
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