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Transluminal attenuation gradient (TAG), defined as the gradient of the contrast agent attenuation drop along the vessel, is an imaging biomarker that indicates stenosis in the coronary arteries. The transluminal attenuation flow encoding (TAFE) equation is a theoretical platform that quantifies blood flow in each coronary artery based on computed tomography angiography (CTA) imaging. This formulation couples TAG (i.e., contrast dispersion along the vessel) with fluid dynamics. However, this theoretical concept has never been validated experimentally. The aim of this proof-of-principle phantom study is to validate TAFE based on CTA imaging. Dynamic CTA images were acquired every 0.5 s. The average TAFE estimated flow rates were compared against four predefined pump values in a straight (20, 25, 30, 35, and 40 ml/min) and a tapered phantom (25, 35, 45, and 55 ml/min). Using the TAFE formulation with no correction, the flow rates were underestimated by 33% and 81% in the straight and tapered phantoms, respectively. The TAFE formulation was corrected for imaging artifacts focusing on partial volume averaging and radial variation of contrast enhancement. After corrections, the flow rates estimated in the straight and tapered phantoms had an excellent Pearson correlation of r = 0.99 and 0.87 (p < 0.001), respectively, with only a 0.6%±0.2 mL/min difference in estimation of the flow rate. In this proof-of-concept phantom study, we corrected the TAFE formulation and showed a good agreement with the actual pump values. Future clinical validations are needed for feasibility of TAFE in clinical use., (Copyright © 2022 by ASME.)

Endothelial shear stress (ESS) identifies coronary plaques at high risk for progression and/or rupture leading to a future acute coronary syndrome. In this study an optimized methodology was developed to derive ESS, pressure drop and oscillatory shear index using computational fluid dynamics (CFD) in 3D models of coronary arteries derived from non-invasive coronary computed tomography angiography (CTA). These CTA-based ESS calculations were compared to the ESS calculations using the gold standard with fusion of invasive imaging and CTA. In 14 patients paired patient-specific CFD models based on invasive and non-invasive imaging of the left anterior descending (LAD) coronary arteries were created. Ten patients were used to optimize the methodology, and four patients to test this methodology. Time-averaged ESS (TAESS) was calculated for both coronary models applying patient-specific physiological data available at the time of imaging. For data analysis, each 3D reconstructed coronary artery was divided into 2 mm segments and each segment was subdivided into 8 arcs (45°).TAESS and other hemodynamic parameters were averaged per segment as well as per arc. Furthermore, the paired segment- and arc-averaged TAESS were categorized into patient-specific tertiles (low, medium and high). In the ten LADs, used for optimization of the methodology, we found high correlations between invasively-derived and non-invasively-derived TAESS averaged over segments (n = 263, r = 0.86) as well as arcs (n = 2104, r = 0.85, p < 0.001). The correlation was also strong in the four testing-patients with r = 0.95 (n = 117 segments, p = 0.001) and r = 0.93 (n = 936 arcs, p = 0.001).There was an overall high concordance of 78% of the three TAESS categories comparing both methodologies using the segment- and 76% for the arc-averages in the first ten patients. This concordance was lower in the four testing patients (64 and 64% in segment- and arc-averaged TAESS). Although the correlation and concordance were high for both patient groups, the absolute TAESS values averaged per segment and arc were overestimated using non-invasive vs. invasive imaging [testing patients: TAESS segment: 30.1(17.1-83.8) vs. 15.8(8.8-63.4) and TAESS arc: 29.4(16.2-74.7) vs 15.0(8.9-57.4) p < 0.001]. We showed that our methodology can accurately assess the TAESS distribution non-invasively from CTA and demonstrated a good correlation with TAESS calculated using IVUS/OCT 3D reconstructed models.

Coronary artery calcium is an accurate predictor of cardiovascular events. While it is visible on all computed tomography (CT) scans of the chest, this information is not routinely quantified as it requires expertise, time, and specialized equipment. Here, we show a robust and time-efficient deep learning system to automatically quantify coronary calcium on routine cardiac-gated and non-gated CT. As we evaluate in 20,084 individuals from distinct asymptomatic (Framingham Heart Study, NLST) and stable and acute chest pain (PROMISE, ROMICAT-II) cohorts, the automated score is a strong predictor of cardiovascular events, independent of risk factors (multivariable-adjusted hazard ratios up to 4.3), shows high correlation with manual quantification, and robust test-retest reliability. Our results demonstrate the clinical value of a deep learning system for the automated prediction of cardiovascular events. Implementation into clinical practice would address the unmet need of automating proven imaging biomarkers to guide management and improve population health.

Improvements in spatial and temporal resolution now permit robust high quality characterization of presence, morphology and composition of coronary atherosclerosis in computed tomography (CT). These characteristics include high risk features such as large plaque volume, low CT attenuation, napkin-ring sign, spotty calcification and positive remodeling. Because of the high image quality, principles of patient-specific computational fluid dynamics modeling of blood flow through the coronary arteries can now be applied to CT and allow the calculation of local lesion-specific hemodynamics such as endothelial shear stress, fractional flow reserve and axial plaque stress. This review examines recent advances in coronary CT image-based computational modeling and discusses the opportunity to identify lesions at risk for rupture much earlier than today through the combination of anatomic and hemodynamic information.

Objectives: To investigate the association between directly measured density and morphology of coronary artery calcium (CAC) with cardiovascular disease (CVD) events, using computed tomography (CT)., Methods: Framingham Heart Study (FHS) participants with CAC in noncontrast cardiac CT (2002-2005) were included and followed until 2016. Participants with known CVD or uninterpretable CT scans were excluded. We assessed and correlated (Spearman) CAC density, CAC volume, and the number of calcified segments. Moreover, we counted morphology features including shape (cylindrical, spherical, semi-tubular, and spotty), location (bifurcation, facing pericardium, or facing myocardium), and boundary regularity. In multivariate Cox regression analyses, we associated all CAC characteristics with CVD events (CVD-death, myocardial infarction, stroke)., Results: Among 1330 included participants (57.8 ± 11.7 years; 63% male), 73 (5.5%) experienced CVD events in a median follow-up of 9.1 (7.8-10.1) years. CAC density correlated strongly with CAC volume (Spearman's ρ = 0.75; p < 0.001) and lower number of calcified segments (ρ = - 0.86; p < 0.001; controlled for CAC volume). In the survival analysis, CAC density was associated with CVD events independent of Framingham risk score (HR (per SD) = 2.09; 95%CI, 1.30-3.34; p = 0.002) but not after adjustment for CAC volume (p = 0.648). The extent of spherically shaped and pericardially sided calcifications was associated with fewer CVD events accounting for the number of calcified segments (HR (per count) = 0.55; 95%CI, 0.31-0.98; p = 0.042 and HR = 0.66; 95%CI, 0.45-0.98; p = 0.039, respectively)., Conclusions: Directly measured CAC density does not predict CVD events due to the strong correlation with CAC volume. The spherical shape and pericardial-sided location of CAC are associated with fewer CVD events and may represent morphological features related to stable coronary plaques., Key Points: • Coronary calcium density may not be independently associated with cardiovascular events. • Coronary calcium density correlates strongly with calcium volume. • Spherical shape and pericardial-sided location of CAC are associated with fewer CVD events.

Background: We present the formulation and testing of a new CT angiography (CTA)-based method for noninvasive measurement of absolute coronary blood flow (CBF) termed transluminal attenuation flow encoding (TAFE). CTA provides assessment of coronary plaque but does not allow for detection of vessel specific ischemia. A simple and direct method to calculate absolute CBF from a standard CTA could isolate the functional consequence of disease and aid therapy decisions., Methods: We present the theoretical framework and initial testing of TAFE. Nine canine models of ischemic heart disease were prepared and underwent CT imaging and microsphere measurements of myocardial blood flow. Additionally, 39 acute chest pain patients with normal coronary arteries underwent coronary CTA. We applied TAFE to calculate absolute CBF in the coronary arteries using 4 vessel input parameters including transluminal attenuation gradient, cross-sectional area, length, and the contrast bolus duration derived from the arterial input function., Results: In animal studies, TAFE-derived CBF in the left anterior descending, left circumflex, and right coronary artery was 20.8 ± 10.4 mL/min, 27.0 ± 13.4 mL/min, and 6.0 ± 3.7 mL/min, respectively. TAFE-derived CBF divided by myocardial mass strongly correlated with microsphere myocardial blood flow (R(2) = 0.90, P < .001). In human studies, TAFE-derived CBF in the left anterior descending, left circumflex, and right coronary artery was 26.4 ± 10.7 mL/min, 20.1 ± 13.0 mL/min, and 43.2 ± 40.9 mL/min, respectively. CBF per unit mass was 0.93 ± 0.48 mL/g/min in patients. Interobserver variability was minimal with excellent correlation (R = 0.96, P < .0001) and agreement (mean difference, 4.2 mL/min)., Conclusion: TAFE allows for quantification of absolute CBF from a standard CTA acquisition and may provide functional significance of coronary disease without complex computational methods., (Copyright © 2015 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.)