The main objectives of this work are to validate a 1D-0D unsteady solver with a distributed stenosis model for the patient-specific estimation of resting haemodynamic indices and to assess the sensitivity of instantaneous wave-free ratio (iFR) predictions to uncertainties in input parameters. We considered 52 patients with stable coronary artery disease, for which 81 invasive iFR measurements were available. We validated the performance of our solver compared to 3D steady-state and transient results and invasive measurements. Next, we used a polynomial chaos approach to characterise the uncertainty in iFR predictions based on the inputs associated with boundary conditions (coronary flow, compliance and aortic/left ventricular pressures) and vascular geometry (radius). Agreement between iFR and the ratio between cardiac cycle averaged distal and aortic pressure waveforms (restingP d / P a $$ {P}_d/{P}_a $$ ) obtained through 1D-0D and 3D models was satisfactory, with a bias of 0.0-0.005 (±0.016-0.026). The sensitivity analysis showed that iFR estimation is mostly affected by uncertainties in vascular geometry and coronary flow (steady-state parameters). In particular, our 1D-0D method overestimates invasive iFR measurements, with a bias of -0.036 (±0.101), indicating that better flow estimates could significantly improve our modelling pipeline. Conversely, we showed that standard pressure waveforms could be used for simulations, since the impact of uncertainties related to inlet-pressure waveforms on iFR prediction is negligible. Furthermore, while compliance is the most relevant transient parameter, its effect on iFR estimates is negligible compared to that of vascular geometry and flow. Finally, we observed a strong correlation between iFR and restingP d / P a $$ {P}_d/{P}_a $$ , suggesting that steady-state simulations could replace unsteady simulations for iFR prediction.

Fractional Flow Reserve (FFR) is generally considered the gold standard in hemodynamics to assess the impact of a stenosis on the blood flow. The standard procedure to measure involves the displacement of a pressure guide along the circulatory system until it is placed next to the lesion to be analyzed. The main objective of the present study is to analyze the influence of the pressure guide on the invasive FFR measurements and its implications in clinical practice.

We studied the influence of pressure wires on the measurement of Fractional Flow Reserve (FFR) through a combination of Computational Fluid Dynamics (CFD) simulations using 45 clinical patient data with 58 lesions and ideal geometries. The analysis is conducted considering patients that were subjected to a computer tomography and also have direct measurements using a pressure guide. Influence of the stenosis severity, degree of occlusion and blood viscosity has also been studied.

The influence of pressure wires specifically affects severe stenosis with a lumen diameter reduction of 50 % or greater. This type of stenosis leads to reduced hyperemic flow and increased coronary pressure drop. Thus, we identified that the placement of wires during FFR measurements results in partial obstruction of the coronary artery lumen, leading to increased pressure drop and subsequent reduction in blood flow. The severity of low FFR values associated with severe stenosis may be prone to overestimation when compared to stenosis without severe narrowing. These results have practical implications, particularly in the interpretation of lesions falling within the "gray zone" (0,75-0,80).

The pressure wire's presence significantly alters the flow on severe lesions, which has an impact on the FFR calculation. In contrast, the impact of the pressure wire appears to be reduced when the FFR is larger than 0.8. The findings provide critical information for physicians, emphasizing the need for cautious interpretation of FFR values, particularly in severe stenosis. It also offers insights into improving the correlation between FFRct models and invasive measurements by incorporating the influence of pressure wires.

Coronary computed tomography-derived fractional flow reserve (FFR-CT) assesses whether coronary artery lesions will result in myocardial ischemia. This study aimed to evaluate the predictive value of FFR-CT for cardiovascular events in patients with coronary artery disease (CAD).

Data were collected retrospectively from patients with CAD who underwent FFR-CT at our hospital from January 2020 to February 2022 (1-year average follow-up). Patients were divided into ischemic (FFR-CT ≤ 0.80) and non-ischemic (FFR-CT > 0.80) groups. The incidence of endpoint events (cardiac death, acute myocardial infarction, unplanned revascularization, unstable angina, and stable angina) was calculated. The FFR-CT value was correlated with endpoint events using Cox regression models and Kaplan-Meier survival curves.

We recruited 134 patients (93 [69.4%] and 41 [30.6%] patients in the ischemic and non-ischemic groups, respectively). The ischemic group had a higher proportion of men, patients with type 2 diabetes and hypertension, and patients taking antiplatelet drugs and β‑blockers than did the non-ischemic group (all p < 0.05), whereas other parameters were comparable. Multivariate Cox regression analysis revealed no significant differences in cardiac death, acute myocardial infarction, unplanned revascularization, and unstable angina between the groups. The incidence of stable angina events (hazard ratio: 3.092, 95% confidence interval: 1.362-7.022, p = 0.007) was significantly higher in the ischemic group. Kaplan-Meier survival analysis revealed a significant difference in event-free survival for stable angina between the groups (p = 0.002).

In patients with CAD, FFR-CT showed an independent predictive value for stable angina within 1 year of examination.

Coronary computed tomography angiography (CCTA) and CCTA-derived fractional flow reserve (FFRCT) are the best non-invasive techniques to assess coronary artery disease (CAD) and myocardial ischemia. Advances in these technologies allow a paradigm shift to the use of CCTA and FFRCT for advanced plaque characterization and planning myocardial revascularization.

The functional assessment of the severity of coronary stenosis from coronary computed tomography angiography (CCTA)-derived fractional flow reserve (FFR) has recently attracted interest. However, existing algorithms run at high computational cost. Therefore, this study proposes a fast calculation method of FFR for the diagnosis of ischemia-causing coronary stenosis.

We combined CCTA and machine learning to develop a simplified single-vessel coronary model for rapid calculation of FFR. First, a zero-dimensional model of single-vessel coronary was established based on CCTA, and microcirculation resistance was determined through the relationship between coronary pressure and flow. In addition, a coronary stenosis model based on machine learning was introduced to determine stenosis resistance. Computational FFR (cFFR) was then obtained by combining the zero-dimensional model and the stenosis model with inlet boundary conditions for resting (cFFRr) and hyperemic (cFFRh) aortic pressure, respectively. We retrospectively analyzed 75 patients who underwent clinically invasive FFR (iFFR), and verified the model accuracy by comparison of cFFR with iFFR.

The average computing time of cFFR was less than 2 s. The correlations between cFFRr and cFFRh with iFFR were r = 0.89 (p < 0.001) and r = 0.90 (p < 0.001), respectively. Diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio for cFFRr and cFFRh were 90.7%, 95.0%, 89.1%, 76.0%, 98.0%, 8.7, 0.1 and 92.0%, 95.0%, 90.9%, 79.2%, 98.0%, 10.5, 0.1, respectively.

The proposed model enables rapid prediction of cFFR and exhibits high diagnostic performance in selected patient cohorts. The model thus provides an accurate and time-efficient computational tool to detect ischemia-causing stenosis and assist with clinical decision-making.

Blood flow and pressure calculated using the currently available methods have shown the potential to predict the progression of pathology, guide treatment strategies and help with postoperative recovery. However, the conspicuous disadvantage of these methods might be the time-consuming nature due to the simulation of virtual interventional treatment. The purpose of this study is to propose a fast novel physics-based model, called FAST, for the prediction of blood flow and pressure. More specifically, blood flow in a vessel is discretized into a number of micro-flow elements along the centerline of the artery, so that when using the equation of viscous fluid motion, the complex blood flow in the artery is simplified into a one-dimensional (1D) steady-state flow. We demonstrate that this method can compute the fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA). 345 patients with 402 lesions are used to evaluate the feasibility of the FAST simulation through a comparison with three-dimensional (3D) computational fluid dynamics (CFD) simulation. Invasive FFR is also introduced to validate the diagnostic performance of the FAST method as a reference standard. The performance of the FAST method is comparable with the 3D CFD method. Compared with invasive FFR, the accuracy, sensitivity and specificity of FAST is 88.6%, 83.2% and 91.3%, respectively. The AUC of FFR_FAST is 0.906. This demonstrates that the FAST algorithm and 3D CFD method show high consistency in predicting steady-state blood flow and pressure. Meanwhile, the FAST method also shows the potential in detecting lesion-specific ischemia.

A quick calculation approach of steady-state fractional flow reserve (FFRss) based on computed tomography angiography (CTA) images is a reliable non-invasive way of calculate FFR, the assumptions used in the research should be study further to increase forecast accuracy. The effect of inlet and outlet boundary conditions on FFRss was investigated.

15 patients who had been diagnosed with coronary artery disease were enrolled in this study. We investigated the sensitivity of calculating FFR to boundary circumstances, using invasive FFR as a benchmark. There are two types of inlet: (1) aortic pressure based on clinically measured. (2) mean pressure calculated based on physiological formula; we further studied the outlet changes of FFRss under different coronary vasodilation responses (24%, 48%, 72%).

According to the calculate FFR results of all patients, FFR_SST (based on the clinical experiment) and FFR_SSM (based on the physiological formula) {r = 0.99, [95% confidence interval (CI):0.0.94 to 1.14] (p < 0.001)}. Although the pressure difference between the two pressure boundary conditions is 15 mmHg, the calculated FFR result does not change significantly. The microcirculation resistance of the outlet gradually rose as the vasodilation state changed, and the computed FFR increased.

A numerical analysis of the effects of proximal and distal boundary constraints of computational models on computed CT-FFR is presented. The findings revealed that distal boundary circumstances (hyperemic vasodilation response of coronary micro-vessels) have a significant impact on FFR, providing evidence to guide the development and application of a computational model for estimating FFR.

Coronary computed tomography angiography (CCTA) and CCTA-derived fractional flow reserve (FFRCT) are the best non-invasive techniques to assess coronary artery disease (CAD) and myocardial ischemia. Advances in these technologies allow a paradigm shift to the use of CCTA and FFRCT for advanced plaque characterization and planning myocardial revascularization.

Coronary CT angiography (CCTA)-derived quantitative flow ratio (CT-QFR) is a novel non-invasive technology to assess the physiological significance of coronary stenoses, which enables fast and on-site computation of fractional flow reserve (FFR) from CCTA images. The objective of this investigator-initiated, prospective, single-centre clinical trial is to evaluate the diagnostic performance of CT-QFR with respect to angiography-derived QFR, using FFR as the reference standard.

A total of 216 patients who have at least one lesion with a diameter stenosis of 30%-90% in an artery with ≥2.0 mm reference diameter will be enrolled in the study. FFR will be measured during invasive coronary angiography. CT-QFR and QFR will be assessed in two independent core laboratories in a blinded fashion. The primary endpoint is the diagnostic accuracy of CT-QFR in identifying haemodynamically significant coronary stenosis with FFR as the reference standard. The major secondary endpoint is the non-inferiority of CT-QFR compared with QFR in the patients without extensively calcified lesions.

The study was approved by the Ethics Committee of Huadong Hospital Affiliated to Fudan University (2020K192). Outcomes will be disseminated through publications in peer-reviewed journals and presentations at scientific conferences.

NCT04665817.

Fractional flow reserve (FFR) is considered to be the criterion standard for the clinical diagnosis of functional myocardial ischemia. In this study, we explored the effect of the coronary arterial diameter derived from coronary computed tomography angiography on FFR.

We retrospectively reviewed the clinical information of 131 patients with moderate coronary artery stenosis. To compare the mean diameter of stenotic vessels, patients were divided into ischemic and nonischemic groups. According to the clinical statistics of the diameter of the ischemic group and the nonischemic group, we established 8 ideal models of coronary artery diameter of 4 mm (40%, 50%, 60%, and 70% stenosis) and diameter of 3 mm (40%, 50%, 60%, and 70% stenosis). Two sets of numerical simulation experiments were carried out: experiment 1 evaluated the variation rate of CT-based computation of non-invasive fractional flow reserve (FFRCT) with vessel diameters of 4 mm and 3 mm under different stenosis rates, and experiment 2 explored the variation of FFRCT with vessel diameters of 4 mm and 3 mm under different cardiac outputs. We simulated changes in the flow of narrow blood vessels by changes in cardiac output.

According to clinical statistics, the mean ± SD diameter of stenotic vessels in the ischemic and nonischemic groups was 3.67 ± 0.77 mm and 3.31 ± 0.64 mm (P < 0.05 for difference), respectively. In experiment 1, the FFRCT of coronary with a diameter of 4 mm was 0.86, 0.80, 0.66, and 0.35, and that with a diameter of 3 mm was 0.90, 0.84, 0.71, and 0.50, respectively. In experiment 2, the FFRCT of the coronary vessel diameter of 4 mm was 0.84, 0.80, 0.76, and 0.72, respectively. The FFRCT coronary vessels with a diameter of 3 mm were 0.87, 0.84, 0.80, and 0.76, respectively.

As the stenosis increases, compared with narrow blood vessel of small diameter, the narrow blood vessel with larger diameter is accompanied by faster flow rate changes and is more prone to ischemia.

To explore the influence of the blood flow-diameter scaling laws of $ \mathrm{Q}\mathrm{\alpha }{\mathrm{D}}^{3} $, $ \mathrm{Q}\mathrm{\alpha }{\mathrm{D}}^{2.7} $ and $ \text{Q}\alpha \text{D}{}^{7}\!\!\diagup\!\!{}_{3}\; $ on the numerical simulation of fraction flow reserve based on CTA images and to find the optimal exponents.

1) 26 patients with coronary artery disease were screened according to the inclusion criteria; 2) Microcirculation resistance (Rm) was calculated under the 3, 2.7 and 7/3 power of the flow-diameter scaling law, which were recorded as 3Rm, 2.7Rm and 7/3Rm, respectively; 3) 3Rm, 2.7Rm and 7/3Rm were used as exit boundary conditions to simulate FFRCT, quoted as 3FFRCT, 2.7FFRCT and 7/3FFRCT, respectively; 4) The correlation and diagnostic performance between three kinds of FFRCT and FFR were analyzed.

The p-values of comparing 3Rm, 2.7Rm and 7/3Rm with FFR were 0.004, 0.005 and 0.010, respectively; the r value between 7/3FFRCT and FFR (0.96) was better than that of 3FFRCT (0.95) and 2.7FFRCT (0.95); the 95% LoA between 7/3FFRCT and FFR (-0.08~0.11) was smaller than that of 3FFRCT (-0.10~0.12) and 2.7FFRCT (-0.09~0.11); the AUC and accuracy of 7/3FFRCT [0.962 (0.805-0.999), 96.15%] were the same as those of 2.7FFRCT [0.962 (0.805-0.999), 96.15%] and better than those of 3FFRCT [0.944 (0.777-0.996), 92.3%]. The prediction threshold of 7/3FFRCT (0.791) was closer to 0.8 than that of 3FFRCT (0.816) and 2.7FFRCT (0.787).

The blood flow-diameter scaling law affects the FFRCT simulation by influencing the exit boundary condition Rm of the calculation. With $ Q\alpha D{}^{7}\!\!\diagup\!\!{}_{3}\; $, FFRCT had the highest diagnostic performance. The blood flow-diameter scaling law provides theoretical support for the blood flow distribution in the bifurcated vessel and improves the FFRCT model.

The fractional flow reserve index (FFR) is currently used as a gold standard to quantify coronary stenosis's functional relevance. Due to its highly invasive nature, the development of noninvasive surrogates based on simulations has drawn much attention in recent years, emphasizing efficient strategies that enable translational research. The focus of this work is twofold. First, to assess the feasibility of using a mid-fidelity numerical strategy (transversally enriched pipe element method, TEPEM), placed between low- and high-fidelity models, for the estimation of flow-related quantities, such as FFR and wall shear stress (WSS). Low-fidelity models, as zero- or one-dimensional models, are computationally inexpensive but in detriment of poorer spatially detailed predictions. On the other hand, high-fidelity models, such as classical three-dimensional numerical approximations, can provide detailed predictions but their transition to clinical application is prohibitive due to high computational costs. As a second goal, we quantify the impact of the length of lateral branches in the blood flow through the interrogated vessel of interest to further reduce the computational burden. Both studies are addressed considering a cohort of 17 coronary geometries. A total of 20 locations were selected to estimate the FFR index for a wide range of Coronary Flow Reserve (CFR) scenarios. Numerical results suggest that the mid-fidelity TEPEM model is a reliable approach for the efficient estimation of the FFR index and WSS, with an error in the order of [Formula: see text] and [Formula: see text], respectively, when compared to the high-fidelity prediction. Moreover, such mid-fidelity models require much less computational resources, in compliance with infrastructure frequently available in the clinic, by achieving a speedup between 30 and 60 times compared to a conventional finite element approach. Also, we show that shortening peripheral branches does not introduce considerable perturbations either in the flow patterns, in the wall shear stress, or the pressure drop. Comparing the different geometric models, the error in the estimation of FFR index and WSS is reduced to less than [Formula: see text] and [Formula: see text], respectively.

Background: The optimal site for measuring computed tomography (CT)-derived fractional flow reserve (FFR_CT) to detect significant coronary artery disease (CAD) remains unknown. We investigated how diagnostic performance changes with FFR_CT measurement site. Methods and Results: The diagnostic performance of FFR_CT, measured 1-2 cm distal to the stenosis vs. a far-distal site, in detecting significant CAD with invasive fractional flow reserve ≤0.8 was evaluated in 254 diseased vessels from 146 patients with stable or suspected CAD diagnosed by coronary CT angiography. Receiver operating characteristic curve analysis revealed a significantly larger area under the curve for FFR_CT measured 1-2 cm distal to the stenosis than at a far-distal site (0.829 vs. 0.791, respectively; P=0.0305). The rate of reclassification of positive FFR_CT was 19% for measurements made 1-2 cm distal to the stenosis, and diagnostic accuracy for FFR_CT 0.71-0.80 improved from 36% to 58% (P=0.0052). Vessel-based diagnostic accuracy of FFR_CT 1-2 cm distal to the stenosis and at a far-distal site was 75% and 65%, respectively (P<0.0001), with corresponding sensitivity of 87% and 94% (P=0.0039), specificity of 60% and 29% (P<0.0001), a positive predictive value of 73% and 62% (P=0.028), and a negative predictive value of 78% and 79% (P=0.958). Conclusions: Our data suggest measuring FFR_CT 1-2 cm distal to the stenosis has better diagnostic performance for detecting physiologically significant CAD.

Fraction flow reserve (FFR) derived from computed tomography (FFR_CT) has been proposed to be an effective gatekeeper for invasive angiographic referral. The purpose of the present study is to examine the real-world diagnostic performance of FFR_CT and myocardial perfusion imaging as well as to assess the utility of FFR_CT as a gatekeeper for invasive coronary angiography in patients suspected of having obstructive coronary artery disease. Total of 146 consecutive patients underwent both single-photon emission computed tomography (SPECT) and invasive FFR were evaluated. An FFR_CT value 1 to 2 cm distal to a stenosis ≤0.80 was defined as positive for ischemia and a summed stress score ≥2 or transient ischemic dilatation ≥1.2 were positive for ischemia with the invasive FFR value of <0.80 serving as the gold standard. The patient-based sensitivity of FFR_CT was significantly higher than SPECT (91 vs 52%, p <0.001) and exhibited similar positive predictive value (82 vs 82%, p = 0.91). These trends were observed even in patients with multivessel and left main trunk disease and those with severe coronary calcification. In conclusion, our data suggest that FFR_CT has higher diagnostic performance characteristics than SPECT and details the superior FFR_CT analysis in detecting patients with hemodynamically significant coronary artery disease. Our results support the clinical utility of FFR_CT analysis as a gatekeeper for invasive coronary angiography in clinical practice.

Fractional Flow Reserve (FFR) is regarded as a fundamental index to assess pulmonary artery stenosis. The application of FFR can increase the accuracy of detection of pulmonary artery stenosis. However, the invasive examination may carry a number of physiological risks for patients. Therefore, we propose a personalized pulmonary circulation model to non- invasively calculate FFR of pulmonary artery stenosis. Method- ology: We employed a personalized pulmonary circulation model to non-invasively calculate FFR using only computed tomography angiogram (CTA) data. This model combined boundary conditions estimation and 3D pulmonary artery morphology reconstruction for CFD simulation. First, we obtained patient-specific boundary conditions by adapting the right ventricle stroke volume and main pulmonary artery pressure feature points (systolic, diastolic, and mean pressure). Secondly, the 3D pulmonary artery morphology was reconstructed by threshold segmentation. The CFD simulation was then performed to obtain pressure distribution in the entire pulmonary artery. Finally, the FFR in pulmonary artery stenoses was calculated as the ratio of distal pressure and proximal pres- sure.

To validate our model, we compared the calculated FFR with measured FFR by pressure guide wires examination of 8 patients. The FFR calculated by our model showed a good agreement with measured FFR by pressure guide wires exami- nation. The average accuracy rate was 91.41%.

The proposed personalized pulmonary model is capable of reasonably non-invasively calculating FFR with sufficient accuracy.

FFR calculated in our model may contribute to non-invasive detection of pulmonary artery stenosis and to the assessment of invasive interventions.

The fractional flow reserve (FFR) index is an important clinical indicator for characterizing coronary artery disease (CAD) functional significance, allowing cardiologists to decide whether intervention is required or not. Noninvasive techniques for calculating FFR are still incompletely resolved and rely heavily on time consuming numerical methods, which may hinder their clinical translation. This paper reports on the development of two fast and noninvasive methods for predicting FFR in diseased coronary arteries. The new methods are derived from physical principles and account for patient-specific physiological parameters that can be noninvasively measured. The developed algebraic equations calculate FFR without performing any tedious numerical simulations, making them attractive for clinical applications. The performance of the methods is assessed by comparing their predictions with measurements and with results obtained by full three-dimensional numerical simulations on healthy and diseased idealized coronary arteries and actual anatomical branches. Results generated by the new methodology are within 5% of measurements and in very good agreement with values obtained numerically.

To compare the diagnostic performance of on-site workstation-based computed tomography-derived fractional flow reserve (CT-FFR)Few data of CT-FFR were reported regarding the diagnostic performance for detecting hemodynamically significant coronary artery disease (CAD). This retrospective single-center analysis included 132 vessels in 77 patients who underwent CT angiography, myocardial perfusion imaging (MPI), and invasive FFR. The correlation coefficient between CT-FFR and invasive FFR and optimal cut-off value for CT-FFR to identify invasive FFR ≤ 0.8 were evaluated. The diagnostic accuracies of CT- FFR, and MPI were evaluated using an area under the receiver-operating characteristic curve (AUC) with invasive FFR as a reference standard. Diagnostic performance of CT-FFR was also evaluated concerning lesion characteristics, including intermediate lesions, left main lesions, tandem lesions, and/or diffuse lesions, and coronary calcium (Agatston score over 400). The Receiver Operating Characteristic curve analysis showed that the optimal cut-off value of CT-FFR for detecting invasive FFR ≤ 0.80 was 0.80 [AUC = 0.83, 95%CI: 0.76-0.90). Diagnostic sensitivity, specificity, positive and negative predictive value, and accuracy of CT-FFR when compared with those of MPI regarding per-patient analysis were 93% vs. 63%, 48% vs. 61%, 81% vs. 79%, 73% vs. 41%, and 79% vs. 62%, respectively, and for per-vessel analysis were 89% vs. 24%, 66% vs. 82%, 75% vs. 61%, 83% vs. 48%, and 78% vs. 51%, respectively. The AUC of the CT-FFR was significantly higher than MPI (0.83 vs. 0.57, p < 0.0001) regarding the per-vessel analysis. No differences in the diagnostic performance of CT-FFR were noted in the presence of intermediate lesions, left main lesions, tandem lesions, and/or diffuse lesions, and severe coronary calcium. On-site CT-FFR delivered a higher diagnostic performance than MPI for detecting CAD with invasive FFR ≤ 0.8, indicating the potential of CT-FFR as the gatekeeper of invasive coronary angiogram as well as percutaneous coronary intervention.

To calculate fractional flow reserve (FFR) based on computed tomography angiography (i.e., FFRCT) by considering the branch flow distribution in the coronary arteries.

FFR is the gold standard to diagnose myocardial ischemia caused by coronary stenosis. An accurate and noninvasive method for obtaining total coronary blood flow is needed for the calculation of FFRCT.

A mathematical model for estimating the coronary blood flow rate and two approaches for setting the patient-specific flow boundary condition were proposed. Coronary branch flow distribution methods based on a volume-flow approach and a diameter-flow approach were employed for the numerical simulation of FFRCT. The values of simulated FFRCT for 16 patients were compared with their clinically measured FFR.

The ratio of total coronary blood flow to cardiac output and the myocardial blood flow under the condition of hyperemia were 16.97% and 4.07 mL/min/g, respectively. The errors of FFRCT compared with clinical data under the volume-flow approach and diameter-flow approach were 10.47% and 11.76%, respectively, the diagnostic accuracies of FFRCT were 65% and 85%, and the consistencies were 95% and 90%.

The mathematical model for estimating the coronary blood flow rate and the coronary branch flow distribution method can be applied to calculate the value of clinical noninvasive FFRCT.

Personalized physics-based flow models are becoming increasingly important in cardiovascular medicine. They are a powerful complement to traditional methods of clinical decision-making and offer a wealth of physiological information beyond conventional anatomic viewing using medical imaging data. These models have been used to identify key hemodynamic biomarkers, such as pressure gradient and wall shear stress, which are associated with determining the functional severity of cardiovascular diseases. Importantly, simulation-driven diagnostics can help researchers understand the complex interplay between geometric and fluid dynamic parameters, which can ultimately improve patient outcomes and treatment planning. The possibility to compute and predict diagnostic variables and hemodynamics biomarkers can therefore play a pivotal role in reducing adverse treatment outcomes and accelerate development of novel strategies for cardiovascular disease management.

To determine the diagnostic performance of instantaneous wave-free ratio (iFR) derived from non-invasive coronary computed tomography angiography (CTA; iFR_CT) for ischaemia-causing coronary stenosis, and to compare the diagnostic efficacy of iFR_CT, CTA, and CTA plus iFR_CT.

Thirty-nine patients (55 vessels) with known or suspected coronary artery disease were included. All patients underwent invasive coronary angiography and fractional flow reserve (FFR) according to CTA findings and clinical indicators. The same raw data used for CTA were used to build patient-specific computed flow dynamic models and to calculate iFR_CT.

On a vessel-based level, the correlation between iFR_CT and FFR was moderate (r=0.65, p<0.05); the optimal iFR_CT cut-off value was 0.85 based on an FFR cut-off value of 0.80, resulting in 85% sensitivity, 69% specificity, 61% positive predictive value (PPV), 89% negative predictive value (NPV), and 75% accuracy. The AUC showed significant differences between iFR_CT and CTA (vessel-based: 0.84 versus 0.68; patient-based: 0.84 versus 0.62; both p<0.01). The accuracy of CTA combined with iFR_CT was significantly increased compared to CTA alone for vessels with intermediate stenosis (83% versus 40%, p<0.01).

iFR_CT showed better diagnostic performance than CTA. iFR_CT may be a promising method for detection of ischaemia-causing coronary stenosis, even in vessels with intermediate stenosis.

Our goal was to evaluate the efficacy of a fully automated method for assessing the image quality (IQ) of coronary computed tomography angiography (CCTA).

The machine learning method was trained using 75 CCTA studies by mapping features (noise, contrast, misregistration scores, and un-interpretability index) to an IQ score based on manual ground truth data. The automated method was validated on a set of 50 CCTA studies and subsequently tested on a new set of 172 CCTA studies against visual IQ scores on a 5-point Likert scale.

The area under the curve in the validation set was 0.96. In the 172 CCTA studies, our method yielded a Cohen's kappa statistic for the agreement between automated and visual IQ assessment of 0.67 (p < 0.01). In the group where good to excellent (n = 163), fair (n = 6), and poor visual IQ scores (n = 3) were graded, 155, 5, and 2 of the patients received an automated IQ score > 50 %, respectively.

Fully automated assessment of the IQ of CCTA data sets by machine learning was reproducible and provided similar results compared with visual analysis within the limits of inter-operator variability.

• The proposed method enables automated and reproducible image quality assessment. • Machine learning and visual assessments yielded comparable estimates of image quality. • Automated assessment potentially allows for more standardised image quality. • Image quality assessment enables standardization of clinical trial results across different datasets.

Information on coronary physiology and myocardial blood flow (MBF) in patients with suspected angina is increasingly important to inform treatment decisions. A number of different techniques including myocardial perfusion imaging (MPI), noninvasive estimation of MBF, and coronary flow reserve (CFR), as well as invasive methods for CFR and fractional flow reserve (FFR) are now readily available. However, despite their incorporation into contemporary guidelines, these techniques are still poorly understood and their interpretation to guide revascularization decisions is often inconsistent. In particular, these inconsistencies arise when there are discrepancies between the various techniques. The purpose of this article is therefore to review the basic principles, techniques, and clinical value of MPI, FFR, and CFR-with particular focus on interpreting their agreements and disagreements.

Evaluation of resting myocardial computed tomography perfusion (CTP) by coronary CT angiography (CCTA) might serve as a useful addition for determining coronary artery disease. We aimed to evaluate the incremental benefit of resting CTP over coronary stenosis for predicting ischemia using a computational algorithm trained by machine learning methods.

252 patients underwent CCTA and invasive fractional flow reserve (FFR). CT stenosis was classified as 0%, 1-30%, 31-49%, 50-70%, and >70% maximal stenosis. Significant ischemia was defined as invasive FFR < 0.80. Resting CTP analysis was performed using a gradient boosting classifier for supervised machine learning.

On a per-patient basis, accuracy, sensitivity, specificity, positive predictive, and negative predictive values according to resting CTP when added to CT stenosis (>70%) for predicting ischemia were 68.3%, 52.7%, 84.6%, 78.2%, and 63.0%, respectively. Compared with CT stenosis [area under the receiver operating characteristic curve (AUC): 0.68, 95% confidence interval (CI) 0.62-0.74], the addition of resting CTP appeared to improve discrimination (AUC: 0.75, 95% CI 0.69-0.81, P value .001) and reclassification (net reclassification improvement: 0.52, P value < .001) of ischemia.

The addition of resting CTP analysis acquired from machine learning techniques may improve the predictive utility of significant ischemia over coronary stenosis.

Amongst patients with suspected obstructive coronary artery disease (CAD), less than a third of patients have obstructive disease on invasive coronary angiography (ICA) and fewer still have flow-limiting obstructive disease as determined by invasive fractional flow reserve (FFR). FFR is a powerful tool in guiding revascularization of flow-limiting lesions which in turn improves clinical outcome in those with haemodynamically significant obstructive disease. However FFR is infrequently performed due to the cost, time and patient discomfort the procedure entails. Further advances in non-invasive imaging has allowed FFR to be derived non-invasively by applying computational fluid dynamic (CFD) modeling to the coronary computed tomography angiography (CCTA) dataset without the need to induce hyperemia or modify the standard CCTA acquisition protocol. FFR derived from CCTA has been shown to have excellent correlation with invasive FFR and remains diagnostically robust in presence of reduced signal-to-noise ratio (SNR), coronary calcification and motion artifact. More recently, new data have emerged evaluating the clinical impact of fractional flow reserve computed tomography (FFRCT) on the assessment and management of patients with stable chest pain. One such study is the Prospective LongitudinAl trial of FFRCT: Outcome and Resource IMpacts (PLATFORM) study which showed an improved patient selection for ICA using CCTA-FFRCT approach by increasing the likelihood of identifying obstructive CAD at ICA amongst those intended for invasive testing. CCTA-FFRCT may therefore serve as efficacious gatekeeper to ICA that enriches the ICA population. The utility of FFRCT has also helped deepened our understanding of CAD. Through CFD modeling, it is now recognized that there are mechanistic forces of wall shear stress (WSS) and axial plaque force acting on coronary plaques. This has created further interest in exploring the possible interplay between these mechanistic forces on the development of coronary plaque and vulnerability of these plaques to rupture.

To investigate the correlation between left coronary bifurcation angle and coronary stenosis as assessed by coronary computed tomography angiography (CCTA)-generated computational fluid dynamics (CFD) analysis when compared to the CCTA analysis of coronary lumen stenosis and plaque lesion length with invasive coronary angiography (ICA) as the reference method.

Thirty patients (22 males, mean age: 59±6.9 years) with calcified plaques at the left coronary artery were included in the study with all patients undergoing CCTA and ICA examinations. CFD simulation was performed to analyze hemodynamic changes to the left coronary artery models in terms of wall shear stress, wall pressure and flow velocity, with findings correlated to the coronary stenosis and degree of bifurcation angle. Calcified plaque length was measured in the left coronary artery with diagnostic value compared to that from coronary lumen and bifurcation angle assessments.

Of 26 significant stenosis at left anterior descending (LAD) and 13 at left circumflex (LCx) on CCTA, only 14 and 5 of them were confirmed to be >50% stenosis at LAD and LCx respectively on ICA, resulting in sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 100%, 52%, 49% and 100%. The mean plaque length was measured 5.3±3.6 and 4.4±1.9 mm at LAD and LCx, respectively, with diagnostic sensitivity, specificity, PPV and NPV being 92.8%, 46.7%, 61.9% and 87.5% for extensively calcified plaques. The mean bifurcation angle was measured 83.9±13.6º and 83.8±13.3º on CCTA and ICA, respectively, with no significant difference (P=0.98). The corresponding sensitivity, specificity, PPV and NPV were 100%, 78.6%, 84.2% and 100% based on bifurcation angle measurement on CCTA, 100%, 73.3%, 78.9% and 100% based on bifurcation angle measurements on ICA, respectively. Wall shear stress was noted to increase in the LAD and LCx models with significant stenosis and wider angulation (>80º), but demonstrated little or no change in most of the coronary models with no significant stenosis and narrower angulation (<80º).

This study further clarifies the relationship between left coronary bifurcation angle and significant stenosis, with angulation measurement serving as a more accurate approach than coronary lumen assessment or plaque lesion length for determining significant coronary stenosis. Left coronary bifurcation angle is suggested to be incorporated into coronary artery disease (CAD) assessment when diagnosing significant CAD.

We evaluated the association between atherosclerotic plaque characteristics (APCs) by CT -including positive remodelling (PR), low attenuation plaque (LAP) and spotty calcification (SC)- and lesion ischaemia by fractional flow reserve (FFR).

Two hundred and fifty-two patients (17 centres, five countries) underwent CT, FFR derived from CT (FFRCT) with invasive FFR performed for 407 coronary lesions. FFR ≤0.8 was indicative of lesion-specific ischaemia. CT diameter ≥50% stenosis was considered obstructive. APCs by CT were defined as: (1) PR, lesion diameter/reference diameter >1.10; (2) LAP, any voxel <30 HU; and (3) SC, nodular calcified plaque <3 mm. Odds ratios (OR) and area under the ROC curve (AUC) of APCs for lesion-specific ischaemia were analysed. PR, LAP and SC were associated with ischaemia, with a three to fivefold higher prevalence than in non-ischaemic lesions. Among individual APC, PR (OR 4.7, p<0.001), but not SC or LAP, was strongly associated with lesion-specific ischaemia and provided incremental prediction for lesion-specific ischaemia over CT stenosis plus FFRCT (AUC 0.87 vs. 0.83, p=0.002).

APCs' features -especially PR- by CT improve identification and reclassification of coronary lesions which cause ischaemia over CT stenosis and FFRCT.

Studies evaluating the relationship between dense coronary calcium (DC) and myocardial ischemia have had incongruent results. We sought to clarify whether DC, as detected by computed coronary tomographic angiography (CCTA), is an independent predictor of ischemia as measured by invasive fractional flow reserve (FFR).

In total, 249 (399 lesions) stable patients undergoing CCTA and invasive FFR were enrolled for this post-hoc analysis. DC was defined as plaque with ≥350 HU using quantification software, and ischemia was defined as FFR ≤0.80. We evaluated the relationship of dense calcium volume (DCV), lesion plaque volume (LPV), non-calcified plaque volume (NCV), and area stenosis (AS) with ischemia using logistic regression reporting odds ratios (OR) with 95% confidence intervals (95% CI).

Mean age was 63.0 ± 8.6 years, and 73 (29.3%) were female. Mean DCV was higher in lesions with FFR ≤0.80 (57.0 ± 54.7 mm³vs. 37.6 ± 49.5 mm³, [p < 0.001]). DCV and LPV were closely correlated (Pearson's coefficient = 0.49 [p < 0.001]). After adjustment for AS, LPV (OR 1.01, 95% CI 1.00-1.04, p < 0.001) but not DCV (OR 1.01, 95% CI 0.96-1.06, p = 0.69) was independently associated with ischemia.

Dense calcium is not an independent predictor of ischemia, but rather a marker of aggregate LPV, which in turn, is predictive of ischemia.

The instantaneous wave-free ratio (iFR) closely related to fractional flow reserve (FFR) is a adenosine-independent physiologic index of coronary stenosis severity. We sought to evaluate whether iFR derived from coronary computed tomographic angiography (iFRCT) can be used as a novel noninvasive method for diagnosis of ischemia-causing coronary stenosis.We retrospectively enrolled 33 patients (47 lesions) with coronary artery disease (CAD) and examined with coronary computed tomographic angiography (CTA), invasive coronary angiography (ICA), and FFR. Patient-specific anatomical model of the coronary artery was built by original resting end-diastolic CTA images. Based on the model and computational fluid dynamics, individual boundary conditions were set to calculate iFRCT as the mean pressure distal to the stenosis divided by the mean aortic pressure during the diastolic wave-free period of rest state. Ischemia was assessed by an FFR of up to 0.8, while anatomically obstructive CAD was defined by a stenosis of at least 50% by ICA. The correlation between iFRCT and FFR was evaluated. The receiver operating characteristic (ROC) curve was used to select the cut-off value of iFRCT for diagnosis of ischemia-causing stenosis. The diagnostic performances of iFRCT, coronary CTA, and iFRCT plus CTA for ischemia-causing stenosis were compared with ROC curve and Delong method.On a per-vessel basis, iFRCT and FFR had linear correlation (r = 0.75, p < 0.01). ROC analysis identified an optimal iFRCT cut-off value of 0.82 for categorization based on an FFR cut-off value 0.8, and the diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of iFRCT were 78.72%,70.59%, 83.33%,70.59%, and 83.33%, respectively. Compared with obstructive CAD diagnosed by coronary CTA (AUC = 0.60), iFRCT yielded diagnostic improvement over stenosis assessment with AUC increasing from 0.6 by CTA to 0.87 (P < 0.01) and 0.90 (P < 0.01) when iFRCT plus CTA.In conclusion, iFRCT is a promising index improving diagnostic performance over coronary CTA for detection of ischemia-causing coronary stenosis.

Wall shear stress (WSS) is an established predictor of coronary atherosclerosis progression. Prior studies have reported that high WSS has been associated with high-risk atherosclerotic plaque characteristics (APCs). WSS and APCs are quantifiable by coronary computed tomography angiography, but the relationship of coronary lesion ischemia-evaluated by fractional flow reserve-to WSS and APCs has not been examined.

WSS measures were obtained from 100 evaluable patients who underwent coronary computed tomography angiography and invasive coronary angiography with fractional flow reserve. Patients were categorized according to tertiles of mean WSS values defined as low, intermediate, and high. Coronary ischemia was defined as fractional flow reserve ≤0.80. Stenosis severity was determined by minimal luminal diameter. APCs were defined as positive remodeling, low attenuation plaque, and spotty calcification. The likelihood of having positive remodeling and low-attenuation plaque was greater in the high WSS group compared with the low WSS group after adjusting for minimal luminal diameter (odds ratio for positive remodeling: 2.54, 95% CI 1.12-5.77; odds ratio for low-attenuation plaque: 2.68, 95% CI 1.02-7.06; both P<0.05). No significant relationship was observed between WSS and fractional flow reserve when adjusting for either minimal luminal diameter or APCs. WSS displayed no incremental benefit above stenosis severity and APCs for detecting lesions that caused ischemia (area under the curve for stenosis and APCs: 0.87, 95% CI 0.81-0.93; area under the curve for stenosis, APCs, and WSS: 0.88, 95% CI 0.82-0.93; P=0.30 for difference).

High WSS is associated with APCs independent of stenosis severity. WSS provided no added value beyond stenosis severity and APCs for detecting lesions with significant ischemia.

Non-invasive fractional flow reserve measured by coronary computed tomography angiography (FFR_CT) has demonstrated a high diagnostic accuracy for detecting coronary artery disease (CAD) in selected patients in prior clinical trials. However, feasibility of FFR_CT in unselected population have not been fully evaluated. Among 60 consecutive patients who had suspected significant CAD by coronary computed tomography angiography (CCTA) and were planned to undergo invasive coronary angiography, 48 patients were enrolled in this study comparing FFR_CT with invasive fractional flow reserve (FFR) without any exclusion criteria for the quality of CCTA image. FFR_CT was measured in a blinded fashion by an independent core laboratory. FFR_CT value was evaluable in 43 out of 48 (89.6 %) patients with high prevalence of severe calcification in CCTA images [calcium score (CS) >400: 40 %, and CS > 1000: 19 %). Per-vessel FFR_CT value showed good correlation with invasive FFR value (Spearman's rank correlation = 0.69, P < 0.001). The area under the receiver operator characteristics curve (AUC) of FFR_CT was 0.87. Per-vessel accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 68.6, 92.9, 52.4, 56.5, and 91.7 %, respectively. Even in eight patients (13 vessels) with extremely severely calcified lesions (CS > 1000), per-vessel FFR_CT value showed a diagnostic performance similar to that in patients with CS ≤ 1000 (Spearman's rank correlation = 0.81, P < 0.001). FFR_CT could be measured in the majority of consecutive patients who had suspected significant CAD by CCTA in real clinical practice and demonstrated good diagnostic performance for detecting hemodynamically significant CAD even in patients with extremely severe calcified vessels.

The functional assessment of a hemodynamic significant stenosis base on blood pressure variation has been applied for evaluation of the myocardial ischemic event. This functional assessment shows great potential for improving the accuracy of the classification of the severity of carotid stenosis. To explore the value of grading the stenosis using a pressure gradient (PG)-we had reconstructed patient-specific carotid geometries based on MRI images-computational fluid dynamics were performed to analyze the PG in their stenotic arteries. Doppler ultrasound image data and the corresponding MRI image data of 19 patients with carotid stenosis were collected. Based on these, 31 stenotic carotid arterial geometries were reconstructed. A combinatorial boundary condition method was implemented for steady-state computer fluid dynamics simulations. Anatomic parameters, including tortuosity (T), the angle of bifurcation, and the cross-sectional area of the remaining lumen, were collected to investigate the effect on the pressure distribution. The PG is highly correlated with the severe stenosis (r = 0.902), whereas generally, the T and the angle of the bifurcation negatively correlate to the pressure drop of the internal carotid artery stenosis. The calculation required <10 min/case, which made it prepared for the fast diagnosis of the severe stenosis. According to the results, we had proposed a potential threshold value for distinguishing severe stenosis from mild-moderate stenosis (PG = 0.88). In conclusion, the PG could serve as the additional factor for improving the accuracy of grading the severity of the stenosis.

Coronary computed tomography angiography (cCTA) has been established for the non-invasive diagnosis of coronary artery disease (CAD). Previous studies demonstrated the high diagnostic accuracy of cCTA, particularly for ruling out CAD. As a known limitation of cCTA a large number of visually significant coronary stenoses are found to be hemodynamically not relevant by invasive fractional flow reserve (FFR). CT-based FFR (CT-FFR) builds on recent advances in computational fluid dynamics and image simulation techniques. Along with CT myocardial perfusion imaging, CT-FFR is a promising approach towards a more accurate estimation of the hemodynamic relevance of coronary artery stenoses. CT-FFR is derived from regular CT datasets without additional image acquisitions, contrast material, or medication. Two CT-FFR techniques can be differentiated. The initial method requires external use of supercomputers and has gained approval for clinical use in the USA. Furthermore, a prototype-software has been introduced which is less computationally demanding via integration of reduced-order models for on-site calculation of CT-FFR. The present article reviews these methods in the context of available study results and meta-analyses. Furthermore, limitations and future concepts of CT-FFR are discussed.

Invasive fractional flow reserve (FFR) is the gold standard for the determination of physiologic stenosis severity and the need for revascularization. FFR computed from standard acquired coronary computed tomographic angiography datasets (FFRCT) is an emerging technology which allows calculation of FFR using resting image data from coronary computed tomographic angiography (CCTA). However, the diagnostic accuracy of FFRCT in the evaluation of lesion-specific myocardial ischemia remains to be confirmed, especially in patients with intermediate coronary stenosis. We performed an integrated analysis of data from 3 prospective, international, and multicenter trials, which assessed the diagnostic performance of FFRCT using invasive FFR as a reference standard. Three studies evaluating 609 patients and 1050 vessels were included. The total calculated sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of FFRCT were 82.8%, 77.7%, 60.8%, 91.6%, and 79.2%, respectively, for the per-vessel analysis, and 89.4%, 70.5%, 69.7%, 89.7%, and 78.7%, respectively, for the per-patient analysis. Compared with CCTA alone, FFRCT demonstrated significantly improved accuracy (P < 0.001) in detecting lesion-specific ischemia. In patients with intermediate coronary stenosis, FFRCT remained both highly sensitive and specific with respect to the diagnosis of ischemia. In conclusion, FFRCT appears to be a reliable noninvasive alternative to invasive FFR, as it demonstrates high accuracy in the determination of anatomy and lesion-specific ischemia, which justifies the performance of additional randomized controlled trials to evaluate both the clinical benefits and the cost-effectiveness of FFRCT-guided coronary revascularization.