A novel patient-specific model to compute coronary fractional flow reserve

A review of computational methodologies to predict the fractional flow reserve in coronary arteries with stenosis

Computational methodologies for predicting the fractional flow reserve (FFR) in coronary arteries with stenosis have gained significant attention due to their potential impact on healthcare outcomes. Coronary artery disease is a leading cause of mortality worldwide, prompting the need for accurate diagnostic and treatment approaches. The use of medical image-based anatomical vascular geometries in computational fluid dynamics (CFD) simulations to evaluate the hemodynamics has emerged as a promising tool in the medical field. This comprehensive review aims to explore the state-of-the-art computational methodologies focusing on the possible considerations. Key aspects include the rheology of blood, boundary conditions, fluid-structure interaction (FSI) between blood and the arterial wall, and multiscale modelling (MM) of stenosis. Through an in-depth analysis of the literature, the goal is to obtain an overview of the major achievements regarding non-invasive methods to compute FFR and to identify existing gaps and challenges that inform further advances in the field. This research has the major objective of improving the current diagnostic capabilities and enhancing patient care in the context of cardiovascular diseases.

Diagnostic Performance of On-Site Automatic Coronary Computed Tomography Angiography-Derived Fractional Flow Reserve

BACKGROUND AND OBJECTIVES

Fractional flow reserve (FFR) is an invasive standard method to identify ischemia-causing coronary artery disease (CAD). With the advancement of technology, FFR can be noninvasively computed from coronary computed tomography angiography (CCTA). Recently, a novel simpler method has been developed to calculate on-site CCTA-derived FFR (CT-FFR) with a commercially available workstation.

METHODS

A total of 319 CAD patients who underwent CCTA, invasive coronary angiography, and FFR measurement were included. The primary outcome was the accuracy of CT-FFR for defining myocardial ischemia evaluated with an invasive FFR as a reference. The presence of ischemia was defined as FFR ≤0.80. Anatomical obstructive stenosis was defined as diameter stenosis on CCTA ≥50%, and the diagnostic performance of CT-FFR and CCTA stenosis for ischemia was compared.

RESULTS

Among participants (mean age 64.7±9.4 years, male 77.7%), mean FFR was 0.82±0.10, and 126 (39.5%) patients had an invasive FFR value of ≤0.80. The diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of CT-FFR were 80.6% (95% confidence interval [CI], 80.5-80.7%), 88.1% (95% CI, 82.4-93.7%), 75.6% (95% CI, 69.6-81.7%), 70.3% (95% CI, 63.1-77.4%), and 90.7% (95% CI, 86.2-95.2%), respectively. CT-FFR had higher diagnostic accuracy (80.6% vs. 59.1%, p<0.001) and discriminant ability (area under the curve from receiver operating characteristic curve 0.86 vs. 0.64, p<0.001), compared with anatomical obstructive stenosis on CCTA.

CONCLUSIONS

This novel CT-FFR obtained from an on-site workstation demonstrated clinically acceptable diagnostic performance and provided better diagnostic accuracy and discriminant ability for identifying hemodynamically significant lesions than CCTA alone.

Computational fluid dynamics modeling of coronary artery blood flow using OpenFOAM: Validation with the food and drug administration benchmark nozzle model

Cardiovascular disease (CVD), a global health concern, particularly coronary artery disease (CAD), poses a significant threat to well-being. Seeking safer and cost-effective diagnostic alternatives to invasive coronary angiography, noninvasive coronary computed tomography angiography (CCTA) gains prominence. This study employed OpenFOAM, an open-source Computational Fluid Dynamics (CFD) software, to analyze hemodynamic parameters in coronary arteries with serial stenoses. Patient-specific three-dimensional (3D) models from CCTA images offer insights into hemodynamic changes. OpenFOAM breaks away from traditional commercial software, validated against the FDA benchmark nozzle model for reliability. Applying this refined methodology to seventeen coronary arteries across nine patients, the study evaluates parameters like fractional flow reserve computed tomography simulation (FFRCTS), fluid velocity, and wall shear stress (WSS) over time. Findings include FFRCTS values exceeding 0.8 for grade 0 stenosis and falling below 0.5 for grade 5 stenosis. Central velocity remains nearly constant for grade 1 stenosis but increases 3.4-fold for grade 5 stenosis. This research innovates by utilizing OpenFOAM, departing from previous reliance on commercial software. Combining qualitative stenosis grading with quantitative FFRCTS and velocity measurements offers a more comprehensive assessment of coronary artery conditions. The study introduces 3D renderings of wall shear stress distribution across stenosis grades, providing an intuitive visualization of hemodynamic changes for valuable insights into coronary stenosis diagnosis.

Assessing the impact of turbulent kinetic energy boundary conditions on turbulent flow simulations using computational fluid dynamics

Computational fluid dynamics has been widely used to study hemodynamics, but accurately determining boundary conditions for turbulent blood flow remains challenging. This study aims to investigate the effect of patient-specific turbulence boundary conditions on the accuracy of turbulent flow simulation. Using a stenosis model with 50% severity in diameter, the post-stenosis turbulence flow region was simulated with different planes to obtain inlet boundary conditions and simulate downstream flows. The errors of simulated flow fields obtained with turbulence kinetic energy (TKE) boundary data and arbitrary turbulence intensity were compared. Additionally, the study tested various TKE data resolutions and noise levels to simulate experimental environments. The mean absolute error of velocity and TKE was investigated with various turbulence intensities and TKE mapping. While voxel size and signal-to-noise ratio of the TKE data affected the results, simulation with SNR > 5 and voxel size < 10% resulted in better accuracy than simulations with turbulence intensities. The simulation with appropriate TKE boundary data resulted in a more accurate velocity and turbulence field than those with arbitrary turbulence intensity boundary conditions. The study demonstrated the potential improvement of turbulent blood flow simulation with patient-specific turbulence boundary conditions, which can be obtained from recent measurement techniques.

Performance of a Novel CT-Derived Fractional Flow Reserve Measurement to Detect Hemodynamically Significant Coronary Stenosis

BACKGROUND

Fractional flow reserve (FFR) based on computed tomography (CT) has been shown to better identify ischemia-causing coronary stenosis. However, this current technology requires high computational power, which inhibits its widespread implementation in clinical practice. This prospective, multicenter study aimed at validating the diagnostic performance of a novel simple CT based fractional flow reserve (CT-FFR) calculation method in patients with coronary artery disease.

METHODS

Patients who underwent coronary CT angiography (CCTA) within 90 days and invasive coronary angiography (ICA) were prospectively enrolled. A hemodynamically significant lesion was defined as an FFR ≤ 0.80, and the area under the receiver operating characteristic curve (AUC) was the primary measure. After the planned analysis for the initial algorithm A, we performed another set of exploratory analyses for an improved algorithm B.

RESULTS

Of 184 patients who agreed to participate in the study, 151 were finally analyzed. Hemodynamically significant lesions were observed in 79 patients (52.3%). The AUC was 0.71 (95% confidence interval [CI], 0.63-0.80) for CCTA, 0.65 (95% CI, 0.56-0.74) for CT-FFR algorithm A (P = 0.866), and 0.78 (95% CI, 0.70-0.86) for algorithm B (P = 0.112). Diagnostic accuracy was 0.63 (0.55-0.71) for CCTA alone, 0.66 (0.58-0.74) for algorithm A, and 0.76 (0.68-0.82) for algorithm B.

CONCLUSION

This study suggests the feasibility of automated CT-FFR, which can be performed on-site within several hours. However, the diagnostic performance of the current algorithm does not meet the a priori criteria for superiority. Future research is required to improve the accuracy.

Mapping the use of computational modelling and simulation in clinics: A survey

In silico medicine describes the application of computational modelling and simulation (CM&S) to the study, diagnosis, treatment or prevention of a disease. Tremendous research advances have been achieved to facilitate the use of CM&S in clinical applications. Nevertheless, the uptake of CM&S in clinical practice is not always timely and accurately reflected in the literature. A clear view on the current awareness, actual usage and opinions from the clinicians is needed to identify barriers and opportunities for the future of in silico medicine. The aim of this study was capturing the state of CM&S in clinics by means of a survey toward the clinical community. Responses were collected online using the Virtual Physiological Human institute communication channels, engagement with clinical societies, hospitals and individual contacts, between 2020 and 2021. Statistical analyses were done with R. Participants (n = 163) responded from all over the world. Clinicians were mostly aged between 35 and 64 years-old, with heterogeneous levels of experience and areas of expertise (i.e., 48% cardiology, 13% musculoskeletal, 8% general surgery, 5% paediatrics). The CM&S terms "Personalised medicine" and "Patient-specific modelling" were the most well-known within the respondents. "In silico clinical trials" and "Digital Twin" were the least known. The familiarity with different methods depended on the medical specialty. CM&S was used in clinics mostly to plan interventions. To date, the usage frequency is still scarce. A well-recognized benefit associated to CM&S is the increased trust in planning procedures. Overall, the recorded level of trust for CM&S is high and not proportional to awareness level. The main barriers appear to be access to computing resources, perception that CM&S is slow. Importantly, clinicians see a role for CM&S expertise in their team in the future. This survey offers a snapshot of the current situation of CM&S in clinics. Although the sample size and representativity could be increased, the results provide the community with actionable data to build a responsible strategy for accelerating a positive uptake of in silico medicine. New iterations and follow-up activities will track the evolution of responses over time and contribute to strengthen the engagement with the medical community.

Diagnostic Performance of On-Site Computed Tomography Derived Fractional Flow Reserve on Non-Culprit Coronary Lesions in Patients with Acute Coronary Syndrome

The role of coronary computed tomography angiography (CCTA) derived fractional flow reserve (CT-FFR) in the assessment of non-culprit lesions (NCL) in patients with acute coronary syndrome (ACS) is debated. In this prospective clinical study, a total of 68 ACS patients with 89 moderate (30−70% diameter stenosis) NCLs were enrolled to evaluate the diagnostic accuracy of on-site CT-FFR compared to invasive fractional flow reserve (FFRi) and dobutamine stress echocardiography (DSE) as reference standards. CT-FFR and FFRi values ≤0.80, as well as new or worsening wall motion abnormality in ≥2 contiguous segments on the supplying area of an NCL on DSE, were considered positive for ischemia. Sensitivity, specificity, positive, and negative predictive value of CT-FFR relative to FFRi and DSE were 51%, 89%, 75%, and 74% and 37%, 77%, 42%, and 74%, respectively. CT-FFR value (β = 0.334, p < 0.001) and CT-FFR drop from proximal to distal measuring point [(CT-FFR drop), β = −0.289, p = 0.002)] were independent predictors of FFRi value in multivariate linear regression analysis. Based on comparing their receiver operating characteristics area under the curve (AUC) values, CT-FFR value and CT-FFR drop provided better discriminatory power than CCTA-based minimal lumen diameter stenosis to distinguish between an NCL with positive and negative FFRi [0.77 (95% Confidence Intervals, CI: 0.67−0.86) and 0.77 (CI: 0.67−0.86) vs. 0.63 (CI: 0.52−0.73), p = 0.029 and p = 0.043, respectively]. Neither CT-FFR value nor CT-FFR drop was predictive of regional wall motion score index at peak stress (β = −0.440, p = 0.441 and β = 0.403, p = 0.494) or was able to confirm ischemia on the territory of an NCL revealed by DSE (AUC = 0.54, CI: 0.43−0.64 and AUC = 0.55, CI: 0.44−0.65, respectively). In conclusion, on-site CT-FFR is superior to conventional CCTA-based anatomical analysis in the assessment of moderate NCLs; however, its diagnostic capacity is not sufficient to make it a gatekeeper to invasive functional evaluation. Moreover, based on its comparison with DSE, CT-FFR might not yield any information on the microvascular dysfunction in the territory of an NCL.

PERSONALIZED FLOW DIVISION METHOD BASED ON THE LEFT-RIGHT CORONARY CROSS-SECTIONAL AREA

This paper proposes a personalized method to estimate blood flow distribution based on the cross-sectional area of the left-right coronary artery openings. According to the cross-sectional area of the left-right coronary artery in 30 cases, a personalized flow distribution model was derived. A 0D/3D geometric multiscale model was used for the numerical simulation of FFR. To evaluate the accuracy of the cross-sectional area method, invasive FFR was used as the standard. The diagnostic efficiency of the proposed method was verified through the simulation results of the volume and the fixed ratio methods. The flow of the left-right coronary artery was proportional to the 3/4 power of the cross-sectional area. The 95% LOA between the cross-sectional area method, volume method, fixed ratio method and FFR were [Formula: see text]0.06 ([[Formula: see text]0.22, 0.10]), [Formula: see text]0.03 ([[Formula: see text]0.35, 0.28]), and [Formula: see text]0.05 ([[Formula: see text]0.30, 0.20]), the accuracy values were 94.44%, 77.78%, and 77.78%, respectively. Flow distribution based on the cross-sectional area represents the supply and demand relationship of the myocardium. The flow of the left-right coronary arteries is proportional to the 3/4 exponent of the cross-sectional area, which affects the accuracy of FFRCT by affecting the exit boundary conditions of the 0D/3D model.

A Simple Method for Automatic 3D Reconstruction of Coronary Arteries From X-Ray Angiography

Automatic three-dimensional (3-D) reconstruction of the coronary arteries (CA) from medical imaging modalities is still a challenging task. In this study, we present a deep learning-based method of automatic identification of the two ends of the vessel from X-ray coronary angiography (XCA). We also present a method of using template models of CA in matching the two-dimensional segmented vessels from two different angles of XCA. For the deep learning network, we used a U-net consisting of an encoder (Resnet) and a decoder. The two ends of the vessel were manually labeled to generate training images. The network was trained with 2,342, 1,907, and 1,523 labeled images for the left anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA), respectively. For template models of CA, ten reconstructed 3-D models were averaged for each artery. The accuracy of correspondence using template models was compared with that of manual matching. The deep learning network pointed the proximal region (20% of the total length) in 97.7, 97.5, and 96.4% of 315, 201, and 167 test images for LAD, LCX, and RCA, respectively. The success rates in pointing the distal region were 94.9, 89.8, and 94.6%, respectively. The average distances between the projected points from the reconstructed 3-D model to the detector and the points on the segmented vessels were not statistically different between the template and manual matchings. The computed FFR was not significantly different between the two matchings either. Deep learning methodology is feasible in identifying the two ends of the vessel in XCA, and the accuracy of using template models is comparable to that of manual correspondence in matching the segmented vessels from two angles.

On the relevance of boundary conditions and viscosity models in blood flow simulations in patient-specific aorto-coronary bypass models

Physiologically realistic results are the aim of every blood flow simulation. This is not different in aorto-coronary bypasses where the properties of the coronary circulation may significantly affect the relevance of the performed simulations. By considering three patient-specific bypass geometries, the present article focuses on two aspects of the coronary blood flow - its phasic flow pattern and its behaviour affected by blood rheology. For the phasic flow property, a multiscale modelling approach is chosen as a means to assess the ability of five different types of coronary boundary conditions (mean arterial pressure, Windkessel model and three lumped parameter models) to attain realistic coronary haemodynamics. From the analysed variants of boundary conditions, the best option in terms of physiological characteristics and its potential for use in patient-based simulations, is utilised to account for the effect of shear-dependent viscosity on the resulting haemodynamics and wall shear stress stimulation. Aside from the Newtonian model, the blood rheology is approximated by two non-Newtonian models in order to determine whether the choice of a viscosity model is important in simulations involving coronary circulation. A comprehensive analysis of obtained results demonstrated notable superiority of all lumped parameter models, especially in comparison to the constant outlet pressure, which regardless of bypass type gave overestimated and physiologically misleading results. In terms of rheology, it was noted that blood in undamaged coronary arteries behaves as a Newtonian fluid, whereas in vessels with atypical lumen geometry, such as that of anastomosis or stenosis, its shear-thinning behaviour should not be ignored.

Validation of the diagnostic performance of 'HeartMedi V.1.0', a novel CT-derived fractional flow reserve measurement, for patients with coronary artery disease: a study protocol

INTRODUCTION

Coronary CT angiography (CCTA) is widely used for non-invasive coronary artery evaluation, but it is limited in identifying the nature of functional characteristics that cause ischaemia. Recent computational fluid dynamic (CFD) techniques applied to CCTA images permit non-invasive computation of fractional flow reserve (FFR), a measure of lesion-specific ischaemia. However, this technology has limitations, such as long computational time and the need for expensive equipment, which hinder widespread use.

METHODS AND ANALYSIS

This study is a prospective, multicentre, comparative and confirmatory trial designed to evaluate the diagnostic performance of HeartMedi V.1.0, a novel CT-derived FFR measurement for the detection of haemodynamically significant coronary artery stenoses identified by CCTA, based on invasive FFR as a reference standard. The invasive FFR values ≤0.80 will be considered haemodynamically significant. The study will enrol 184 patients who underwent CCTA, invasive coronary angiography and invasive FFR. Computational FFR (c-FFR) will be analysed by CFD techniques using a lumped parameter model based on vessel length method. Blinded core laboratory interpretation will be performed for CCTA, invasive coronary angiography, invasive FFR and c-FFR. The primary objective of the study is to compare the area under the receiver-operator characteristic curve between c-FFR and CCTA to non-invasively detect the presence of haemodynamically significant coronary stenosis. The secondary endpoints include diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value and correlation of c-FFR with invasive FFR.

ETHICS AND DISSEMINATION

The study has ethic approval from the ethics committee of Seoul National University Bundang Hospital (E-1709/420-001) and informed consent will be obtained for all enrolled patients. The result will be published in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

KCT0002725; Pre-results.

Diagnostic performance of a vessel-length-based method to compute the instantaneous wave-free ratio in coronary arteries

The instantaneous wave-free ratio (iFR) is a recently introduced vasodilator-free index to assess the functional severity of coronary stenosis in the resting state, while fractional flow reserve (FFR) is the gold standard index in hyperemia. The computed instantaneous wave-free ratio (CT-iFR) is a noninvasive method to estimate iFR using computer simulations. Here, we developed a vessel-length-based CT-iFR method in patient-specific models of coronary arteries. This method was implemented by coupling a three-dimensional computational fluid dynamics model with a lumped parameter model (LPM) of coronary circulation in a non-hyperemic resting state. A time-varying resistance in the LPM was used for the iFR simulation. In total, 50 coronary vessels of 32 patients were computed, and their CT-iFR values were compared with clinically measured iFRs to evaluate the diagnostic performance of the present CT-iFR method. The area under the receiver operating characteristics curve of CT-iFR validation was 0.93. In diagnostic performances of CT-iFR, accuracy, sensitivity, and specificity were 86%, 83.3%, and 86.8%, respectively. These results indicate that this CT-iFR method can be used as a pre-operative aid to establish a percutaneous coronary intervention strategy as a noninvasive alternative to iFR.

Integrating Patient-Specific Electrocardiogram Signals and Image-Based Computational Fluid Dynamics Method to Analyze Coronary Blood Flow in Patients during Cardiac Arrhythmias

Purpose

The aim of this study was to use the computational fluid dynamics (CFD) method, patient-specific electrocardiogram (ECG) signals, and computed tomography three-dimensional image reconstruction technique to investigate the blood flow in coronary arteries during cardiac arrhythmia.

Methods

Two patients with premature ventricular contraction-type cardiac arrhythmia and one with atrial fibrillation-type cardiac arrhythmia were investigated. The inlet velocity of the coronary artery in simulation was applied with the measured velocity profile of the left ventricular outflow tract (LVOT) from the Doppler echocardiography. The measured patient central aortic blood pressure waveform was employed for the coronary artery outlet in simulation. The no-slip boundary condition was applied to the arterial wall.

Results

For the patient with irregular cardiac rhythms (Case I), the coronary blood flow rate under the shortened and lengthened cardiac rhythms were 0.66 and 0.96 mL/s, respectively. In Case II, the maximum velocity at the LVOT under a normal heartbeat was found to be 101 cm/s, whereas the average value was 73 cm/s. In Case III, the patient was also diagnosed with a congenital stenosis problem at the myocardial bridge (MCB) at the LAD. The measured blood flow rate at the MCB of the LAD for the three heartbeats in Case III was found to be 0.68, 1.08, and 1.14 mL/s.

Conclusion

The integration of patient-specific ECG signals and image-based CFD methods can clearly analyze hemodynamic information for patients during cardiac arrhythmia. The cardiac arrhythmia can reduce the blood flow in the coronary arteries.

Prediction of Plaque Progression in Coronary Arteries Based on a Novel Hemodynamic Index Calculated From Virtual Stenosis Method

Rationale

Predicting the sites in coronary arteries that are susceptible to plaque deposition is essential for the development of clinical treatment strategies and prevention. However, to date, no physiological biomarkers for this purpose have been developed. We hypothesized that the possibility of plaque deposition at a specific site in the coronary artery is associated with wall shear stress (WSS) and fractional flow reserve (FFR).

Background and Objective

We proposed a new biomarker called the stenosis susceptibility index (SSI) using the FFR and WSS derived using virtual stenosis method. To validate the clinical efficacy of this index, we applied the method to actual pilot clinical cases. This index non-invasively quantifies the vasodilation effects of vascular endothelial cells relative to FFR variation at a specific coronary artery site.

Methods and Results

Using virtual stenosis method, we computed maximum WSS and FFR according to the variation in stenotic severity at each potential stenotic site and then plotted the variations of maximum WSS (y-axis) and FFR (x-axis). The slope of the graph indicated a site-specific SSI value. Then we determined the most susceptible sites for plaque deposition by comparing SSI values between the potential sites. Applying this method to seven patients revealed 71.4% in per-patient basis analysis 77.8% accuracy in per-vessel basis analysis in percutaneous coronary intervention (PCI) site prediction.

Conclusion

The SSI index can be used as a predictive biomarker to identify plaque deposition sites. Patients with relatively smaller SSI values also had a higher tendency for myocardial infarction. In conclusion, sites susceptible to plaque deposition can be identified using the SSI index.

Fluid-structure Interaction in the Cerebral Venous Transverse Sinus

The biomechanics of the cerebral venous system plays an important role in determining blood flow to the brain. Computational approaches to help elucidate the role of the cerebral venous system in health and disease have largely focused on lumped-parameter models and one-dimensional computational fluid dynamics simulations. To expand upon the prior work, and to investigate the possible role of cerebral venous collapse in normal physiology and pathological conditions, we developed a fluid-structure interaction (FSI) model of the cerebral venous transverse sinus (TS), coupled to a lumpedparameter representation of the upstream cerebral circulation to provide boundary conditions for the FSI simulation. We simulated the effects of local venous hemodynamics on the TS distention and investigated TS vascular collapse under increased intracranial pressure, as has been hypothesized in the pathogenesis of idiopathic intracranial hypertension. Our baseline simulations reproduced pressures and flows in the cerebral venous system that compared favorably with what has been reported in the literature. The FSI simulations under increased intracranial pressure showed a decreased venous flow through and progressive collapse of the TS veins. Our simulations captured the dynamic behavior of the vascular collapse and may help shed light on the interactions between the cerebrovascular and cerebrospinal fluid spaces in health and disease.

Diagnostic Performance of a Novel Method for Fractional Flow Reserve Computed from Noninvasive Computed Tomography Angiography (NOVEL-FLOW Study)

Coronary computed tomography angiography (CCTA)-derived fractional flow reserve from computed tomography (CT-FFR) may provide better diagnostic performance over CCTA alone, but the complexity of its method limits the use in clinical environment. The aim of the present study is to validate a newly developed vessel-length based computational fluid dynamics scheme for the computation of FFR based on CCTA data, compare them with invasively measured FFR, and evaluate its diagnostic performance with that of CCTA. One hundred seventeen patients from 4 medical institutions who had clinically indicated invasive coronary angiography for suspected coronary artery disease (CAD) were enrolled. Invasive FFR measurement was performed in 218 vessels and these measurements were regarded as the reference standard. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of CT-FFR on a per-vessel basis were 85.8%, 86.2%, 85.5%, 79.8%, and 90.3%, respectively, for CT-FFR ≤0.80, and 66.1%, 75.9%, 59.5%, 55.5%, and 78.8%, respectively, for CCTA ≥50%. A higher area under the receiver operating characteristic curve for CT-FFR was observed compared with CCTA (0.93 vs 0.74, p <0.0001). The CT-FFR and FFR correlated well (r = 0.76, p <0.001) with slight underestimation by CT-FFR (0.014 ± 0.077, p = 0.007). With a novel method of vessel-length based computational fluid dynamics scheme, CT-FFR can be performed at a personal computer enhancing its applicability in clinical situation. The diagnostic accuracy of CT-FFR for the detection of functionally significant CAD was good and was superior to that of CCTA within a population of suspected CAD.

A vessel length-based method to compute coronary fractional flow reserve from optical coherence tomography images

Background

Hemodynamic simulation for quantifying fractional flow reserve (FFR) is often performed in a patient-specific geometry of coronary arteries reconstructed from the images from various imaging modalities. Because optical coherence tomography (OCT) images can provide more precise vascular lumen geometry, regardless of stenotic severity, hemodynamic simulation based on OCT images may be effective. The aim of this study is to perform OCT–FFR simulations by coupling a 3D CFD model from geometrically correct OCT images with a LPM based on vessel lengths extracted from CAG data with clinical validations for the present method.

Methods

To simulate coronary hemodynamics, we developed a fast and accurate method that combined a computational fluid dynamics (CFD) model of an OCT-based region of interest (ROI) with a lumped parameter model (LPM) of the coronary microvasculature and veins. Here, the LPM was based on vessel lengths extracted from coronary X-ray angiography (CAG) images. Based on a vessel length-based approach, we describe a theoretical formulation for the total resistance of the LPM from a three-dimensional (3D) CFD model of the ROI.

Results

To show the utility of this method, we present calculated examples of FFR from OCT images. To validate the OCT-based FFR calculation (OCT–FFR) clinically, we compared the computed OCT–FFR values for 17 vessels of 13 patients with clinically measured FFR (M-FFR) values.

Conclusion

A novel formulation for the total resistance of LPM is introduced to accurately simulate a 3D CFD model of the ROI. The simulated FFR values compared well with clinically measured ones, showing the accuracy of the method. Moreover, the present method is fast in terms of computational time, enabling clinicians to provide solutions handled within the hospital.

Physiome approach for the analysis of vascular flow reserve in the heart and brain

This work reviews the key aspects of coronary and neurovascular flow reserves with an emphasis on physiomic modeling characteristics by the use of a variety of numerical approaches. First, we explain the definition of fractional flow reserve (FFR) in coronary artery and introduce its clinical significance. Then, computational researches for obtaining FFR are reviewed, and their clinical outcomes are compared. In the case of cerebrovascular reserve (CVR), in spite of substantial progress in the simulation of cerebral hemodynamics, only a few computational studies exist. Thus, we discuss the limitations of CVR simulation study and suggest the challenging issue to overcome these. Also, the future direction of physiomic researches for the flow reserves in coronary arteries and cerebral arteries is described. Also, we introduce a machine learning algorithm trained by the existing physiomic simulation data of flow reserve and suggest a prospective research direction related to this.

The Impact of the Geometric Characteristics on the Hemodynamics in the Stenotic Coronary Artery

The alterations of the hemodynamics in the coronary arteries, which result from patient-specific geometric significances are complex. The effect of the stenosis on the blood flow alteration had been wildly reported, but the combinational contribution from geometric factors required a comprehensive investigation to provide patient-specific information for diagnosis and assisting in the decision on the further treatment strategies. In the present study, we investigated the correlation between hemodynamic parameters and individual geometric factors in the patient-specific coronary arteries. Computational fluid dynamic simulations were performed on 22 patient-specific 3-dimensional coronary artery models that were reconstructed based on computed tomography angiography images. Our results showed that the increasing severity of the stenosis is associated with the increased maximum wall shear stress at the stenosis region (r = 0.752, P < 0.001). In contrast, the length of the recirculation zone has a moderate association with the curvature of the lesion segment (r = 0.505, P = 0.019) and the length of the lesions (r = 0.527, P = 0.064). Moreover, bifurcation in the coronary arteries is significantly correlated with the occurrence of recirculation, whereas the severity of distal stenosis demonstrated an effect on the alteration of the flow in the upstream bifurcation. These findings could serve as an indication for treatment planning and assist in prognosis evaluation.

Physiologic Assessment of Coronary Artery Disease: Focus on Fractional Flow Reserve

The presence of myocardial ischemia is the most important prognostic factor in patients with ischemic heart disease. Fractional flow reserve (FFR) is a gold standard invasive method used to detect the stenosis-specific myocardial ischemia. FFR-guided revascularization strategy is superior to angiography-guided strategy. The recently developed hyperemia-free index, instantaneous wave free ratio is being actively investigated. A non-invasive FFR derived from coronary CT angiography is now used in clinical practice. Due to rapid expansion of invasive and non-invasive physiologic assessment, comprehensive understanding of the role and potential pitfalls of each modality are required for its application. In this review, we focus on the basic and clinical aspects of physiologic assessment in ischemic heart disease.

Development of an In Vitro Model to Characterize the Effects of Transcatheter Aortic Valve on Coronary Artery Flow

Impairment of coronary artery flow, in either acute or chronic conditions, is a severe complication of transcatheter aortic valve (TAV) implantation, which can arise due to improper TAV positioning. However, little work has been done to quantify the effects of the TAV positioning on the coronary flow. In this study, a realistic in vitro model of coronary artery flow was developed and used to investigate the impact of TAV deployed orientations on coronary flow. The coronary hemodynamics was first replicated mathematically using a lumped parameter model with time-varying myocardial resistance. Based on the analytical model, two stepper motor controlled stopcock valves were integrated in a left heart simulator to represent the variable myocardial resistance in the experimental setup. The coronary flow and pressure waveforms obtained from the in vitro system were consistent with published data. With a TAV deployed in different orientations, the measured results demonstrated that TAV orientation does not have a significant impact on the coronary flow. The developed in vitro model can be further utilized to simulate coronary flow under various pathological conditions.