Background: Pericoronary adipose tissue attenuation (PCATa), derived from coronary computed tomography angiography (CCTA), is a novel marker of inflammation in the coronary arteries. Patients with type 2 diabetes mellitus (T2DM) are at elevated risk of coronary artery disease (CAD), potentially due to systemic inflammation. This study evaluated whether baseline PCATa predicts changes in plaque composition and burden over 12 months. Methods: This prospective longitudinal study included 200 participants with T2DM, who had neither symptoms nor a prior diagnosis of CAD (mean age 61 ± 9.4 years, 72% male). PCATa was measured at the baseline scan along the proximal 40 mm of each major coronary artery, and the values were averaged to calculate the participant-level PCATa. High PCATa levels were determined using the validated cut-off of -70.1 Hounsfield units. Compositional plaque changes were quantified as the differences between baseline and 12-month scans, and plaque burden was calculated as the normalized atheroma volume. Multivariable regression analyses assessed the associations between baseline PCATa and compositional plaque changes and evaluated risk factors, including high PCATa, in predicting non-calcified plaque burden progression. Results: Plaque compositional volumes and burden increased over 12 months, while PCATa remained stable. After multivariable adjustments, baseline PCATa was significantly associated with changes in total plaque volume (β = 0.005, p = 0.005), non-calcified plaque volume (β = 0.006, p = 0.007), total plaque burden (β = 1.7, p = 0.007), and non-calcified plaque burden (β = 2.0, p = 0.006), but not with calcified plaque volume or burden. High baseline PCATa was observed in 44 participants (22%) and was the only independent predictor of non-calcified plaque burden progression (odds ratio 3.5, p = 0.002). Conclusions: Baseline PCATa is significantly associated with increases in total and non-calcified plaque volumes and burden over 12 months in participants with T2DM without symptoms or known CAD. High PCATa levels uniquely predict non-calcified plaque burden progression, suggesting that PCATa may serve as a marker for subclinical atherosclerosis progression. This warrants further investigation into PCATa for cardiovascular risk assessment, particularly in high-risk populations such as individuals with T2DM. Trial registration: Trial registration: NCT06644651. Graphical PCATa = Pericoronary Adipose Tissue attenuation. T2DM = Type 2 diabetes mellitus. CAD = Coronary Artery Disease. N = numbers. CCTA = Coronary CT angiography. Created in BioRender. Research insights: What is currently known about this topic? Type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD) share inflammatory mechanisms. Individuals with T2DM face a two- to four-fold increased risk of CAD compared with those without T2DM. Pericoronary adipose tissue attenuation (PCATa) is a novel marker of coronary inflammation. What is the key research question? Can baseline PCATa predict compositional plaque changes over 12 months in T2DM without known CAD? What is new? Baseline PCATa relates to higher total and non-calcified plaque (NCP) volumes after adjustment. Baseline PCATa associates with increased total- and NCP burden after multivariable adjustment. High baseline PCATa (> -70.1 HU) independently predicts NCP burden progression. How might this study influence clinical practice? PCATa may be a marker for subclinical atherosclerosis progression.

Aims: This study assessed the relationship between air pollution exposure, fine particulate matter ≤2.5 µm (PM2.5) and nitrogen dioxide (NO2), and coronary calcium score (CCS) in a cohort of 60–75-year-old men from the Danish Cardiovascular Screening Trials (DANCAVAS). Methods and results: A total of 12 301 participants were included. Residential and novel workplace address spanning up to 40 years was geocoded. Air pollution exposure was modelled using the Danish Eulerian Hemisphere model (DEHM)/Urban Background Model (UBM)/AirGIS system. Median PM2.5 exposure was 13.7 µg/m3 (interquartile range [IQR]: 13.2–14.1). The median NO2 exposure was 16.3 µg/m3 (IQR: 14.7–18.4). The median CCS was 99 (IQR: 8–410). The primary outcome was CCS ≥ 100, secondary outcomes included CCS ≥ 400 and ordinal-scaled CCS (0, 1–99, 100–399, 400–999, and >999). Binary logistic regression analyses revealed no significant associations; however, generalized ordinal logistic regression analysis of CCS indicated that PM2.5 exposure was associated with coronary artery calcification (CAC) presence (CCS = 0 vs. CCS ≥ 1) with an adjusted odds ratio = 1.11 (95% confidence interval: 1.04–1.18) per 1 µg/m3 increase in PM2.5. No associations were observed for higher CAC categories. The findings for NO2 were non-significant. Addition of workplace exposure showed only moderate changes in effect estimates. Conclusion: Exposure to PM2.5 was modestly associated with the presence of CAC, particularly when combining residential and workplace exposures. No consistent associations were observed with NO2 or advanced stages of calcification. Findings suggest that long-term ambient PM2.5 exposure may contribute to early subclinical atherosclerotic changes; however, modest effect sizes and lack of association with CAC severity call for cautious interpretation.

Deep learning image reconstruction (DLIR) is a technique that should reduce noise and improve image quality. This study assessed the impact of using both higher tube currents as well as DLIR on the image quality and diagnostic accuracy. The study consisted of 51 symptomatic obese (BMI > 30 kg/m²) patients with low to moderate risk of coronary artery disease (CAD). All patients underwent coronary computed tomography angiography (CCTA) twice, first with the Revolution CT scanner and then with the upgraded Revolution Apex scanner with the ability to increase tube current. Images were reconstructed using ASiR-V 50% and DLIR. The image quality was evaluated by an observer using a Likert score and by ROI measurements in aorta and the myocardium. Image quality was significantly improved with the Revolution Apex scanner and reconstruction with DLIR resulting in an odds ratio of 1.23 (p = 0.017), and noise was reduced by 41%. A total of 88% of the image sets performed with Revolution Apex + DLIR were assessed as good enough for diagnosis compared to 69% of the image sets performed with Revolution Apex/CT + ASiR-V. In obese patients, the combination of higher tube current and DLIR significantly improves the subjective image quality and diagnostic utility and reduces noise.

Pericoronary adipose tissue attenuation (PCAT_a), observed from coronary computed tomography angiography (CCTA), is emerging as an inflammation marker. This study evaluated the relationship between PCAT_a and plaque characteristics, including plaque type, burden, and coronary calcification. An observational study was conducted on 466 patients with suspected chronic coronary syndrome who underwent clinically indicated CCTA. PCAT_a was measured along the proximal 40 mm of the coronary arteries and averaged to represent the patient’s level. Plaque type was assessed, compositional plaque volumes were measured, and plaque burdens were quantified. The coronary calcification scores (CCSs) were categorized into groups. Statistical methods included t-tests, ANOVA, and multivariate regression analysis. PCAT_a differed significantly between calcified (−81.7 Hounsfield units (HU)) and soft (−77.5 HU) plaques. PCAT_a was positively associated with total plaque burden (β = 3.6) and non-calcified plaque burden (β = 7.0), but negatively correlated with calcified plaque burden (β = −3.5), independent of clinical factors and tube voltage (p < 0.05). The effect of PCAT_a was stronger when plaques of a different composition were absent. No significant differences in PCAT_a were found among different CCS groups. PCAT_a increased for calcified compared to soft plaques. The non-calcified plaque burden was associated with a higher PCAT_a, while the calcified plaque burden was associated with a lower PCAT_a.

We investigated whether prediabetes diagnosed by hemoglobinA1c (HbA1c) or oral glucose tolerance test (OGTT) could predict presence and severity of coronary artery disease (CAD) in symptomatic patients. The presence of plaque, stenosis, plaque characteristics, and coronary artery calcium (CAC) were evaluated by coronary CT angiography in 702 patients with suspicion of CAD. Patients were classified by glycemic status using the American Diabetes Association criteria for HbA1c and OGTT, and compared to their respective normal ranges. Prediabetes was observed in 24% by HbA1c and 72% by OGTT. Both prediabetes classifications were associated with increased presence of plaque, stenosis, calcified plaques, CAC >400, and a lower frequency of zero CAC compared to their respective normal range (all, p < 0.05). After adjusting for potential confounders, patients with HbA1c-prediabetes had an odds ratio of 2.1 (95% CI: 1.3–3.5) for CAC >400 and 1.5 (95% CI: 1.0–2.4) for plaque presence, while none of the associations for OGTT-prediabetes were significant. The receiver operating characteristic-curve for HbA1c-prediabetes showed an area under the curve of 0.81 for CAC >400 and 0.77 for plaque presence. Prediabetes defined by HbA1c predicts presence and severity of CAD. Although OGTT identified more patients with prediabetes, their risk of CAD were not explained by prediabetes using these diagnostic-criteria.

Background: Cardiovascular disease remains the primary cause of morbidity and mortality despite advancements in the treatment of patients with type 2 diabetes. Effective diabetes management extends beyond blood glucose control and includes cardiovascular prevention and treatment. However, the conventional healthcare model often emphasizes single-disease-specific management, leading to fragmented care. We aim to establish an affordable Cardio-Metabolic Clinic (CMC) that can provide comprehensive assessment and specialized care with a focus on cardiovascular protection. Methods: The ProtecT-2-D study is a prospective, randomized control trial at the Cardiovascular Research Unit, Odense University Hospital Svendborg, Denmark. In this study, 1500 participants with type 2 diabetes and cardiovascular disease will be randomly assigned in a 2:1 ratio to receive either the intervention: treatment in the CMC, or the control: standard of care. The Cardio-Metabolic Clinic applies a decision-making algorithm coded with the latest guidelines to evaluate lifestyle factors and manage medical treatment. Health examinations are conducted at baseline and after three years, and clinical events will be assessed through registry and journal audits after five and ten years. The primary outcome is the time to the first occurrence of a composite of cardiovascular deaths, non-fatal acute myocardial infarctions, non-fatal stroke, or hospitalization due to heart failure at a time frame of five years. Discussion: The Cardio-Metabolic Clinic represents a pioneering approach to diabetes management that aims to improve patient outcomes by reducing the cardiovascular disease burden. This study could transform diabetes care and offer a multidisciplinary, cost-effective, and specialized treatment. We need to establish the efficacy and feasibility of a CMC to integrate comparable clinics into broader healthcare systems, and potentially enhance cardiovascular health in patients with type 2 diabetes. Trial registration number: ClinicalTrials.gov NCT06203860. Graphical