Objectives To determine normal pericoronary adipose tissue mean attenuation (PCATMA) values for left the anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA) in patients without plaques on coronary CT angiography (cCTA), taking into account tube voltage influence. Methods This retrospective study included 192 patients (76 (39.6%) men; median age 49 years (range, 19–79)) who underwent cCTA with third-generation dual-source CT for the suspicion of CAD between 2015 and 2017. We selected patients without plaque on cCTA. PCATMA was measured semi-automatically on cCTA images in the proximal segment of the three main coronary arteries with 10 mm length. Paired t-testing was used to compare PCATMA between combinations of two coronary arteries within each patient, and one-way ANOVA testing was used to compare PCATMA in different kV groups. Results The overall mean ± standard deviation (SD) PCATMA was − 90.3 ± 11.1 HU. PCATMA in men was higher than that in women: − 88.5 ± 10.5 HU versus − 91.5 ± 11.3 HU (p = 0.001). PCATMA of LAD, LCX, and RCA was − 92.4 ± 11.6 HU, − 88.4 ± 9.9 HU, and − 90.2 ± 11.4 HU, respectively. Pairwise comparison of the arteries showed significant difference in PCATMA: LAD and LCX (p < 0.001), LAD and RCA (p = 0.009), LCX and RCA (p = 0.033). PCATMA of the 70 kV, 80 kV, 90 kV, 100 kV, and 120 kV groups was − 95.6 ± 9.6 HU, − 90.2 ± 11.5 HU, − 87.3 ± 9.9 HU, − 82.7 ± 6.2 HU, and − 79.3 ± 6.8 HU, respectively (p < 0.001). Conclusions In patients without plaque on cCTA, PCATMA varied by tube voltage, with minor differences in PCATMA between coronary arteries (LAD, LCX, RCA). PCATMA values need to be interpreted taking into account tube voltage setting. Key Points • In patients without plaque on cCTA, PCATMAdiffers slightly by coronary artery (LAD, LCX, RCA). • Tube voltage of cCTA affects PCATMAmeasurement, with mean PCATMAincreasing linearly with increasing kV. • For longitudinal cCTA analysis of PCATMA, the use of equal kV setting is strongly recommended.

The antagonistic effects of caffeine on adenosine receptors are a possible cause of false-negative stress perfusion imaging. The purpose of this study was to determine the effects of coffee intake <4 h prior to stress perfusion cardiac magnetic resonance imaging (CMR) in regadenoson- versus adenosine-induced hyperemia as measured with T1-mapping. 98 consecutive patients with suspected coronary artery disease referred for either adenosine or regadenoson perfusion CMR were included in this analysis. Twenty-four patients reported coffee consumption <4 h before CMR (15 patients with adenosine, and 9 patients with regadenoson); 74 patients reported no coffee intake (50 patients with adenosine, and 24 patients with regadenoson). T1 mapping was performed using a modified look-locker inversion recovery sequence. T1 reactivity was determined by subtracting T1rest from T1stress. T1rest, T1stress, and T1 reactivity in patients referred for regadenoson perfusion CMR were not significantly different when comparing patients with <4 h coffee intake and patients who reported no coffee intake (976 ± 4 ms, 1019 ± 48 ms, and 4.4 ± 3.2% vs 971 ± 33 ms, 1023 ± 43 ms, and 5.4 ± 2.4%) (p = 0.70, 0.79, and 0.40), and similar to values in patients without coffee intake undergoing adenosine CMR. In patients with <4 h coffee intake, T1stress, and T1 reactivity were significantly lower for adenosine (898 ± 51 ms, and −7.8 ± 5.0%) compared to regadenoson perfusion CMR (p < 0.001). Coffee intake <4 h prior to regadenoson perfusion CMR has no effect on stress-induced hyperemia as measured with T1 mapping.

a b s t r a c tBackground: Computational quantitative flow ratio (QFR) based on 3-dimensional quantitative coronary angiography (3D QCA) analysis offers the opportunity to assess the significance of coronary artery disease (CAD) without using an invasive pressure wire or inducing hyperemia. This study aimed to evaluate the diagnostic performance of QFR compared to wire-based fractional flow reserve (FFR) and to validate the previously reported QFR cut-off value of N0.90 to safely rule out functionally significant CAD. Methods: QFR was retrospectively derived from standard-care coronary angiograms. Correlation and agreement of fixed-flow QFR (fQFR) and contrast-flow QFR (cQFR) models with invasive wire-based FFR was calculated. Diagnostic performance of QFR was evaluated at different QFR cut-off values defining significant CAD (FFR ≤ 0.80). Results: 101 vessels in 96 patients who underwent FFR were studied. Mean FFR was 0.87 ± 0.08 and 21 of 101 (21%) vessels had an FFR ≤ 0.80. Correlation of fQFR and cQFR with FFR was r = 0.71 (p b 0.001) and r = 0.70 (p b 0.001), respectively. Sensitivity and specificity were 57% and 93% for fQFR and 67% and 96% for cQFR at a QFR cut-off value N0.80 defining non-significant CAD, respectively. fQFR N 0.90 was present in 34 (34%) and cQFR N 0.90 in 39 (39%) vessels. For both QFR models, none of the vessels with QFR N 0.90 had an FFR ≤ 0.80.Conclusions: QFR appears to be a safe and effective gatekeeper to wire-based FFR when applying a QFR threshold of N0.90 to rule out significant CAD. Further prospective research is required to establish QFR in the real-life setting of functional CAD assessment in the catheterization laboratory.