Inverse Association between Educational Status and Coronary CT Calcium Scores: Should We Reflect This in Our ASCVD Risk Assumptions?

Education is not a factor included in most cardiovascular risk models, including SCORE2. However, higher education has been associated with lower cardiovascular morbidity and mortality. Using CACS as a proxy for ASCVD, we studied the association between CACS and educational status. Subjects, aged 40-69, from the Paracelsus 10,000 cohort, who underwent calcium scoring as part of screening for subclinical ASCVD, were classified into low, medium, and high educational status using the Generalized International Standard Classification of Education. CACS was dichotomised as either 0 or >0 for logistic regression modelling. Our analysis showed that higher educational status was associated with higher odds for 0 CACS (aOR 0.42; 95%CI 0.26-0.70; p = 0.001). However, there was no statistically significant association between the levels of total, HDL or LDL cholesterol and educational status, nor any statistical differences in HbA1c. SCORE2 did not differ between the three educational categories (4 ± 2% vs. 4 ± 3% vs. 4 ± 2%; p = 0.29). While our observations confirmed the relationship between increased educational status and lower ASCVD risk, the effect of educational status was not mediated via its impact on classical risk factors in our cohort. Thus, perhaps educational status should be taken into account to more accurately reflect individual risk in cardiovascular risk models.

Improved bias and reproducibility of coronary artery calcification features using deconvolution

Purpose

Our long-range goal is to improve whole-heart CT calcium scores by extracting quantitative features from individual calcifications. Here, we perform deconvolution to improve bias/reproducibility of small calcification assessments, which can be degraded at the normal CT calcium score image resolution.

Approach

We analyzed features of individual calcifications on repeated standard (2.5 mm) and thin (1.25 mm) slice scans from QRM-Cardio phantom, cadaver hearts, and CARDIA study participants. Preprocessing to improve the resolution involved of Lucy-Richardson deconvolution with a measured point spread function (PSF) or three-dimensional blind deconvolution in which the PSF was iteratively optimized on high detail structures such as calcifications in images.

Results

Using QRM with inserts having known mg-calcium, we determined that both blind and conventional deconvolution improved mass measurements nearly equally well on standard images. Further, deconvolved thin images gave an excellent recovery of actual mass scores, suggesting that such processing could be our gold standard. For CARDIA images, blind deconvolution greatly improved results on standard slices. Bias across 33 calcifications (without, with deconvolution) was (23%, 9%), (18%, 1%), and ( - 19 % , - 1 % ) for Agatston, volume, and mass scores, respectively. Reproducibility was (0.13, 0.10), (0.12, 0.08), and (0.11, 0.06), respectively. Mass scores were more reproducible than Agatston scores or volume scores. For many other calcification features, blind deconvolution improved reproducibility in 21 out of 24 features. Cadaver images showed similar improvements in bias/reproducibility and slightly better results with a measured PSF.

Conclusions

Deconvolution improves bias and reproducibility of multiple features extracted from individual calcifications in CT calcium score exams. Blind deconvolution is useful for improving feature assessments of coronary calcification in archived datasets.