Coronary CT angiography (CCTA) pericoronary adipose tissue (PCAT) markers are promising indicators of inflammation. To determine the effect of patient and imaging parameters on the associations between non-calcified plaque (NCP) and PCAT attenuation and gradient. This was a single-center, retrospective analysis of consecutive patients with stable chest pain who underwent CCTA and had zero calcium scores. CCTA images were evaluated for the presence of NCP, obstructive stenosis, segment stenosis and involvement score (SSS, SIS), and high-risk plaque (HRP). PCAT markers were assessed using semi-automated software. Uni- and multivariable regression models correcting for patient and imaging characteristics between plaque and PCAT markers were evaluated. Overall, 1652 patients had zero calcium score (mean age: 51 years ​± ​11 [SD], 871 women); PCAT attenuation values ranged between -123 HU and -51 HU, and 649 patients had plaque. In univariable analysis, the presence of NCP, SSS, SIS, and HRP were associated with PCAT attenuation (2, 1, 1, 6 HU; respectively; p ​< ​.001 all); while obstructive stenosis was not (1 HU, p ​= ​.58). In multivariable analysis, none of the plaque markers were associated with PCAT attenuation (0 HU p ​= ​.93, 0 HU p ​= ​.39, 1 HU p ​= ​.18, 2 HU p ​= ​.10, 1 HU p ​= ​.71, respectively), while patient and imaging characteristics showed significant associations, such as: male sex (1 HU, p ​= ​.003), heart rate [1/min] (-0.2 HU, p ​< ​.001), 120 ​kVp (8 HU, p ​< ​.001) and pixel spacing [mm³] (32 HU, p ​< ​.001). Similar results were observed for PCAT gradient. PCAT markers were significantly associated with NCP, however the associations did not persist following correction for patient and imaging characteristics.

Vascular age can be derived from cardiovascular (CV) risk scores such as the Framingham Risk Score (FRS) and the Systematic Coronary Risk Evaluation (SCORE). Recently, coronary artery calcium score (CACS) was proposed as a means of assessing arterial age. We aimed to compare these approaches for the assessment of vascular age. FRS-, SCORE-, and CACS-based vascular ages of 241 consecutive Caucasian patients undergoing coronary CT angiography were defined according to previously published methods. Vascular ages based on FRS, SCORE, and CACS were 68.0 (IQR: 55.0–82.0), 63.0 (IQR: 53.0–75.0), and 47.1 (IQR: 39.1–72.3) years, respectively, (p < 0.001). FRS- and SCORE-based biological age showed strong correlation [ICC: 0.91 (95%CI: 0.88–0.93)], while CACS-based vascular age moderately correlated with FRS- and SCORE-based vascular age [ICC: 0.66 (95%CI: 0.56–0.73) and ICC: 0.65 (95%CI: 0.56–0.73), respectively, both p < 0.001)]. Based on FRS, SCORE, and CACS, 83.4%, 93.8%, and 42.3% of the subjects had higher vascular age than their documented chronological age (FRS+, SCORE+, CACS+), and 53.2% of the FRS+ (107/201) and 57.1% of the SCORE+ (129/226) groups were classified as CACS-. Traditional risk equations demonstrate a tendency of overestimating vascular age in low- to intermediate-risk patients compared to CACS. Prospective studies are warranted to further evaluate the contribution of different vascular age calculations to CV preventive strategies.

Aims: Cardiac CT is increasingly applied for planning and follow-up of transcatheter aortic valve implantation (TAVI). However, there are no data available on reverse remodelling after TAVI assessed by CT. Therefore, we aimed to evaluate the predictors and the prognostic value of left ventricular (LV) reverse remodelling following TAVI using CT angiography. Methods and results: We investigated 117 patients with severe, symptomatic aortic stenosis (AS) who underwent CT scanning before and after TAVI procedure with a mean follow-up time of 2.6 years after TAVI. We found a significant reduction in LV mass (LVM) and LVM indexed to body surface area comparing pre- vs. post-TAVI images: 180.5 ± 53.0 vs. 137.1 ± 44.8 g and 99.7 ± 25.4 vs. 75.4 ± 19.9 g/m2, respectively, both P < 0.001. Subclinical leaflet thrombosis (SLT) was detected in 25.6% (30/117) patients. More than 20% reduction in LVM was defined as reverse remodelling and was detected in 62.4% (73/117) of the patients. SLT, change in mean pressure gradient on echocardiography and prior myocardial infarction was independently associated with LV reverse remodelling after adjusting for age, gender, and traditional risk factors (hypertension, body mass index, diabetes mellitus, and hyperlipidaemia): OR = 0.27, P = 0.022 for SLT and OR = 0.22, P = 0.006 for prior myocardial infarction, OR = 1.51, P = 0.004 for 10 mmHg change in mean pressure gradient. Reverse remodelling was independently associated with favourable outcomes (HR = 0.23; P = 0.019). Conclusion: TAVI resulted in a significant LVM regression on CT. The presence of SLT showed an inverse association with LV reverse remodelling and thus it may hinder the beneficial LV structural changes. Reverse remodelling was associated with improved long-term prognosis.

Obtaining accurate coronary artery calcium (CAC) score measurements from CCTA datasets with virtual non-iodine (VNI) algorithms would reduce acquisition time and radiation dose. We aimed to assess the agreement of VNI-derived and conventional true non-contrast (TNC)-based CAC scores and to identify the predictors of accuracy. CCTA datasets were acquired with either 120 or 140 ​kVp. CAC scores and volumes were calculated from TNC and VNI images in 197 consecutive patients undergoing CCTA. CAC density score, mean volume/lesion, aortic Hounsfield units and standard deviations were then measured. Finally, percentage deviation (VNI - TNC/TNC∗100) of CTA-derived CAC scores from non-enhanced scans was calculated for each patient. Predictors (including anthropometric and acquisition parameters, as well as CAC characteristics) of the degree of discrepancy were evaluated using linear regression analysis. While the agreement between TNC and VNI was substantial (mean bias, 6.6; limits of agreement, 178.5/145.3), a non-negligible proportion of patients (36/197, 18.3%) were falsely reclassified as CAC score ​= ​0 on VNI. The use of higher tube voltage significantly decreased the percentage deviation relative to TNC-based values (β ​= ​-0.21 [95%CI: 0.38 to -0.03], p ​= ​0.020) and a higher CAC density score also proved to be an independent predictor of a smaller difference (β ​= ​-0.22 [95%CI: 0.37 to -0.07], p ​= ​0.006). The performance of VNI-based calcium scoring may be improved by increased tube voltage protocols, while the accuracy may be compromised for calcified lesions of lower density. The implementation of VNI in clinical routine, however, needs to be preceded by a solution for detecting smaller lesions as well.

Filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR) are ubiquitously applied in the reconstruction of coronary CT angiography (CCTA) datasets. However, currently no data is available on the impact of a model-based adaptive filter (MBAF2), recently developed for a dedicated cardiac scanner. Our aim was to determine the effect of MBAF2 on subjective and objective image quality parameters of coronary arteries on CCTA. Images of 102 consecutive patients referred for CCTA were evaluated. Four reconstructions of coronary images (FBP, ASIR, MBAF2, ASIR + MBAF2) were co-registered and cross-section were assessed for qualitative (graininess, sharpness, overall image quality) and quantitative [image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)] image quality parameters. Image noise and signal were measured in the aortic root and the left main coronary artery, respectively. Graininess, sharpness, and overall image quality was assessed on a 4-point Likert scale. As compared to FBP, ASIR, and MBAF2, ASIR + MBAF2 resulted in reduced image noise [53.1 ± 12.3, 30.6 ± 8.5, 36.3 ± 4.2, 26.3 ± 4.0 Hounsfield units (HU), respectively; p < 0.001], improved SNR (8.4 ± 2.6, 14.1 ± 3.6, 11.8 ± 2.3, 16.3 ± 3.3 HU, respectively; p < 0.001) and CNR (9.4 ± 2.7, 15.9 ± 4.0, 13.3 ± 2.5, 18.3 ± 3.5 HU, respectively; p < 0.001). No difference in sharpness was observed amongst the reconstructions (p = 0.08). Although ASIR + MBAF2 was non-superior to ASIR regarding overall image quality (p = 0.99), it performed better than FBP (p < 0.001) and MBAF2 (p < 0.001) alone. The combination of ASIR and MBAF2 resulted in reduced image noise and improved SNR and CNR. The implementation of MBAF2 in clinical practice may result in improved noise reduction performance and could potentiate radiation dose reduction.