Main Coronary Flow Calculation With the Assistance of Physiological Side Branch Flow

OBJECTIVE

Fractional flow reserve (FFR) derived from coronary angiography, referred to as ICA-FFR, is a less-invasive alternative for invasive FFR measurement based on computational fluid dynamics. Blood flow into side branches influences the accuracy of ICA-FFR. However, properly compensating for side branch flow in ICA-FFR analysis is challenging. In this study, we proposed a physiological side branch flow model to comprehensively compensate side branch flow for ICA-FFR analysis with no need for reconstructing side branch geometry.

METHODOLOGY

the physiological side branch flow model employed a reduced-order model to calculate the pressure distribution in vessel segments. The main coronary artery (without side branches) was delineated and divided based on bifurcation nodes. The model compensates for flow to invisible side branches within each segment and flow to visible side branches at each bifurcation node. Lastly, ICA-FFR based on physiological side branch flow model (ICA-FFR) was calculated from a single angiographic view. Functional stenosis is defined by FFR 0.80.

RESULT

Our study involved 223 vessels from 172 patients. Using invasive FFR as a reference, the Pearson correlation coefficient of ICA-FFR was 0.93. ICA-FFR showed a high AUC (AUC = 0.96) and accuracy (91.9) in predicting functional stenosis.

CONCLUSION

The proposed model accurately compensates for flow to side branches without their geometry in ICA-FFR analysis. ICA-FFR analysis exhibits high feasibility and diagnostic performance in identifying functional stenosis.

Enhancing cardiac assessments: accurate and efficient prediction of quantitative fractional flow reserve

Background

Obstruction within the left anterior descending coronary artery (LAD) is prevalent, serving as a prominent and independent predictor of mortality. Invasive Fractional flow reserve (FFR) is the gold standard for Coronary Artery Disease risk assessment. Despite advances in computational and imaging techniques, no definitive methodology currently assures clinicians of reliable, non-invasive strategies for future planning.

Method

The present research encompassed a cohort of 150 participants who were admitted to the Rajaie Cardiovascular, Medical, and Research Center. The method includes a three-dimensional geometry reconstruction, computational fluid dynamics simulations, and methodology optimization for the computation time. Four patients are analyzed within this study to showcase the proposed methodology. The invasive FFR results reported by the clinic have validated the optimized model.

Results

The computational FFR data derived from all methodologies are compared with those reported by the clinic for each case. The chosen methodology has yielded virtual FFR values that exhibit remarkable proximity to the clinically reported patient-specific FFR values, with the MSE of 6.186e-7 and R2 of 0.99 (p = 0.00434).

Conclusion

This approach has shown reliable results for all 150 patients. The results are both computationally and clinically user-friendly, with the accumulative pre and post-processing time of 15 min on a desktop computer (Intel i7 processor, 16 GB RAM). The proposed methodology has the potential to significantly assist clinicians with diagnosis.

Patient-specific in silico 3D coronary model in cardiac catheterisation laboratories

Coronary artery disease is caused by the buildup of atherosclerotic plaque in the coronary arteries, affecting the blood supply to the heart, one of the leading causes of death around the world. X-ray coronary angiography is the most common procedure for diagnosing coronary artery disease, which uses contrast material and x-rays to observe vascular lesions. With this type of procedure, blood flow in coronary arteries is viewed in real-time, making it possible to detect stenoses precisely and control percutaneous coronary interventions and stent insertions. Angiograms of coronary arteries are used to plan the necessary revascularisation procedures based on the calculation of occlusions and the affected segments. However, their interpretation in cardiac catheterisation laboratories presently relies on sequentially evaluating multiple 2D image projections, which limits measuring lesion severity, identifying the true shape of vessels, and analysing quantitative data. In silico modelling, which involves computational simulations of patient-specific data, can revolutionise interventional cardiology by providing valuable insights and optimising treatment methods. This paper explores the challenges and future directions associated with applying patient-specific in silico models in catheterisation laboratories. We discuss the implications of the lack of patient-specific in silico models and how their absence hinders the ability to accurately predict and assess the behaviour of individual patients during interventional procedures. Then, we introduce the different components of a typical patient-specific in silico model and explore the potential future directions to bridge this gap and promote the development and utilisation of patient-specific in silico models in the catheterisation laboratories.

The pressure-derived microvascular resistance reserve and its correlation to Doppler MRR measurement-a proof of concept study

Background

Microvascular resistance reserve (MRR) is a recently introduced specific index of coronary microcirculation. MRR calculation can utilize parameters deriving from coronary flow reserve (CFR) assessment, provided that intracoronary pressure data are also available. The previously proposed pressure-bounded CFR (CFRpb) defines the possible CFR interval on the basis of resting and hyperemic pressure gradients in the epicardial vessel, however, its correlation to the Doppler wire measurement was reported to be rather poor without the correction for hydrostatic pressure.

Purpose

We aimed to determine the pressure-bounded coronary MRR interval with hydrostatic pressure correction according to the previously established equations of CFRpb adapted for the MRR concept. Furthermore, we also aimed to design a prediction model using the actual MRR value within the pressure-bounded interval and validate the results against the gold-standard Doppler wire technique.

Methods

Hydrostatic pressure between the tip of the catheter and the sensor of the pressure wire was calculated by height difference measurement from a lateral angiographic view. In the derivation cohort the pressure-bounded MRR interval (between MRRpbmin and MRRpbmax) was determined solely from hydrostatic pressure-corrected intracoronary pressure data. The actual MRR was calculated by simple hemodynamic equations incorporating the anatomical data of the three-dimensionally reconstructed coronary artery (MRRp-3D). These results were analyzed by regression analyses to find relations between the MRRpb bounds and the actual MRRp-3D.

Results

In the derivation cohort of 23 measurements, linear regression analysis showed a tight relation between MRRpbmax and MRRp-3D (r 2 = 0.74, p < 0.0001). Using this relation (MRRp-3D = 1.04 + 0.51 × MRRpbmax), the linear prediction of the MRR was tested in the validation cohort of 19 measurements against the gold standard Doppler wire technique. A significant correlation was found between the linearly predicted and the measured values (r = 0.54, p = 0.01). If the area stenosis (AS%) was included to a quadratic prediction model, the correlation was improved (r = 0.63, p = 0.004).

Conclusions

The MRR can be predicted reliably to assess microvascular function by our simple model. After the correction for hydrostatic pressure error, the pressure data during routine FFR measurement provides a simultaneous physiological assessment of the macro- and microvasculature.

Non-invasive Angiographic-based Fractional Flow Reserve: Technical Development, Clinical Implications, and Future Perspectives

New non- and less-invasive techniques have been developed to overcome the procedural and operator related burden of the fractional flow reserve (FFR) for the assessment of potentially significant stenosis in the coronary arteries. Virtual FFR-techniques can obviate the need for the additional flow or pressure wires as used for FFR measurements. This review provides an overview of the developments and validation of the virtual FFR-algorithms, states the challenges, discusses the upcoming clinical trials, and postulates the future role of virtual FFR in the clinical practice.

Pressure- and 3D-Derived Coronary Flow Reserve with Hydrostatic Pressure Correction: Comparison with Intracoronary Doppler Measurements

Purpose: To develop a method of coronary flow reserve (CFR) calculation derived from three-dimensional (3D) coronary angiographic parameters and intracoronary pressure data during fractional flow reserve (FFR) measurement. Methods: Altogether 19 coronary arteries of 16 native and 3 stented vessels were reconstructed in 3D. The measured distal intracoronary pressures were corrected to the hydrostatic pressure based on the height differences between the levels of the vessel orifice and the sensor position. Classical fluid dynamic equations were applied to calculate the flow during the resting state and vasodilatation based on morphological data and intracoronary pressure values. 3D-derived coronary flow reserve (CFRp-3D) was defined as the ratio between the calculated hyperemic and the resting flow and was compared to the CFR values simultaneously measured by the Doppler sensor (CFRDoppler). Results: Haemodynamic calculations using the distal coronary pressures corrected for hydrostatic pressures showed a strong correlation between the individual CFRp-3D values and the CFRDoppler measurements (r = 0.89, p < 0.0001). Hydrostatic pressure correction increased the specificity of the method from 46.1% to 92.3% for predicting an abnormal CFRDoppler < 2. Conclusions: CFRp-3D calculation with hydrostatic pressure correction during FFR measurement facilitates a comprehensive hemodynamic assessment, supporting the complex evaluation of macro-and microvascular coronary artery disease.

Angiography-based estimation of coronary physiology: A frame is worth a thousand words

Cumulative evidence has shown that coronary revascularization should be guided by functional significance of coronary lesions. Fractional flow reserve (FFR) is the gold standard for assessment of hemodynamic significance of coronary stenosis and FFR-guided percutaneous coronary intervention has improved clinical outcomes in patients with coronary artery disease. However, limitations of FFR such as increased operational time and cost, requirement of pressure wire and adenosine and technical difficulties have led to significant underutilization of the method in clinical practice. In the last few years, several methods of FFR estimation based on coronary angiography images have emerged to overcome invasive FFR limitations. The common elements of the novel indices include a 3D anatomical reconstruction of coronary vessels by angiographic projections and various approaches to fluid dynamics computation. Angiography-derived FFR methods have shown high diagnostic accuracy compared to invasive FFR. Although there are promising results regarding their prognostic role, large randomized trials evaluating clinical outcomes are lacking. The aim of this review is to present currently available angiography-derived FFR indices and highlight their differences, advantages, disadvantages and potential clinical implications.

The Holistic Coronary Physiology Display: Calculation of the Flow Separation Index in Vessel-Specific Individual Flow Range during Fractional Flow Reserve Measurement Using 3D Coronary Reconstruction

In order to make optimal decisions on the treatment of atherosclerotic coronary heart disease (CHD), appropriate evaluation is necessary, including both the anatomical and physiological assessment of the coronary arteries. According to current guidelines, a fractional flow reserve (FFR)-based clinical decision is recommended, but coronary flow reserve (CFR) measurements and microvascular evaluation should also be considered in special cases for a detailed exploration of the coronary disease state. We aimed to generate an extended physiological evaluation during routine FFR measurement and define a new pathological flow-related prognostic factor. Fluid dynamic equations were applied to calculate CFR on the basis of the three-dimensional (3D) reconstruction of the invasively acquired coronary angiogram and the measured intracoronary pressure data. A new, potentially robust prognostic parameter of a coronary lesion called the "flow separation index" (FS_i), which is thought to detect the pathological flow amount through a stenosis was introduced in a vessel-specific flow range. Correlations between FS_i and the clinically established physiological indices (CFR and FFR) were determined. The FS_i was calculated in 19 vessels of 16 patients, including data from the pre- and post-stent revascularization treatment of 3 patients. There was no significant correlation between the FS_i and the CFR (r = -0.23, p = 0.34); however, there was significant negative correlation between the FS_i and the FFR (r = -0.66, p = 0.002). An even stronger correlation was found between the FS_i and the ratio of the resting pressure ratio and the FFR (r = 0.92, p < 0.0001). The diagnostic power of the FS_i for predicting the FFR value of <0.80, as a gold standard prognostic factor, was tested by receiver operating characteristic analysis. FS_i > 0.022 proved to be the cutoff value of the prediction of a pathologically low FFR with a 0.856 area under the curve (95% confidence interval: 0.620 to 0.972). The present flow-pressure-velocity display provides a comprehensive summary of patient-specific pathophysiology in CHD. The consequences of epicardial stenoses can be evaluated together with their complex relations to microvascular conditions. Based on these values, clinical decision-making concerning both pharmacological therapy and percutaneous or surgical revascularization may be more precisely guided.

Virtual (Computed) Fractional Flow Reserve: Future Role in Acute Coronary Syndromes

The current management of acute coronary syndromes (ACS) is with an invasive strategy to guide treatment. However, identifying the lesions which are physiologically significant can be challenging. Non-invasive imaging is generally not appropriate or timely in the acute setting, so the decision is generally based upon visual assessment of the angiogram, supplemented in a small minority by invasive pressure wire studies using fractional flow reserve (FFR) or related indices. Whilst pressure wire usage is slowly increasing, it is not feasible in many vessels, patients and situations. Limited evidence for the use of FFR in non-ST elevation (NSTE) ACS suggests a 25% change in management, compared with traditional assessment, with a shift from more to less extensive revascularisation. Virtual (computed) FFR (vFFR), which uses a 3D model of the coronary arteries constructed from the invasive angiogram, and application of the physical laws of fluid flow, has the potential to be used more widely in this situation. It is less invasive, fast and can be integrated into catheter laboratory software. For severe lesions, or mild disease, it is probably not required, but it could improve the management of moderate disease in 'real time' for patients with non-ST elevation acute coronary syndromes (NSTE-ACS), and in bystander disease in ST elevation myocardial infarction. Its practicability and impact in the acute setting need to be tested, but the underpinning science and potential benefits for rapid and streamlined decision-making are enticing.

Computerised Methodologies for Non-Invasive Angiography-Derived Fractional Flow Reserve Assessment: A Critical Review

Fractional flow reserve is the gold standard for assessing the haemodynamic significance of intermediate coronary artery stenoses. Cumulative evidence has shown that FFR-guided revascularisation reduces stent implantations and improves patient outcomes. However, despite the wealth of evidence and guideline recommendations, its use in clinical practice remains minimal. Patient and technical limitations of FFR as well as the need for intracoronary instrumentation, use of adenosine, and increased costs have limited FFR's applicability in clinical practice. Over the last decade, several angiography-derived FFR software packages have been developed which do not require intracoronary pressure assessment with a guidewire or need for administration of hyperaemic agents. At present, there are 3 commercially available software packages and several other non-commercial technologies that have been described in the literature. These technologies have been validated against invasive FFR showing good accuracy and correlation. However, the methodology behind these solutions is different-some algorithms are based on solving the governing equations of fluid dynamics such as the Navier-Stokes equation while others have opted for a more simplified mathematical formula approach. The aim of this review is to critically appraise the methodology behind all the known angiography-derived FFR technologies highlighting the key differences and limitations.

Accuracy of Fractional Flow Reserve Derived From Coronary Angiography

BACKGROUND

Measuring fractional flow reserve (FFR) with a pressure wire remains underutilized because of the invasiveness of guide wire placement or the need for a hyperemic stimulus. FFR derived from routine coronary angiography (FFRangio) eliminates both of these requirements and displays FFR values of the entire coronary tree. The FFRangio Accuracy versus Standard FFR (FAST-FFR) study is a prospective, multicenter, international trial with the primary goal of determining the accuracy of FFRangio.

METHODS

Coronary angiography was performed in a routine fashion in patients with suspected coronary artery disease. FFR was measured in vessels with coronary lesions of varying severity using a coronary pressure wire and hyperemic stimulus. Based on angiograms of the respective arteries acquired in ≥2 different projections, on-site operators blinded to FFR then calculated FFRangio using proprietary software. Coprimary end points were the sensitivity and specificity of the dichotomously scored FFRangio for predicting pressure wire-derived FFR using a cutoff value of 0.80. The study was powered to meet prespecified performance goals for sensitivity and specificity.

RESULTS

Ten centers in the United States, Europe, and Israel enrolled a total of 301 subjects and 319 vessels meeting inclusion/exclusion criteria which were included in the final analysis. The mean FFR was 0.81 and 43% of vessels had an FFR≤0.80. The per-vessel sensitivity and specificity were 94% (95% CI, 88% to 97%) and 91% (86% to 95%), respectively, both of which exceeded the prespecified performance goals. The diagnostic accuracy of FFRangio was 92% overall and remained high when only considering FFR values between 0.75 to 0.85 (87%). FFRangio values correlated well with FFR measurements ( r=0.80, P<0.001) and the Bland-Altman 95% confidence limits were between -0.14 and 0.12. The device success rate for FFRangio was 99%.

CONCLUSIONS

FFRangio measured from the coronary angiogram alone has a high sensitivity, specificity, and accuracy compared with pressure wire-derived FFR. FFRangio has the promise to substantially increase physiological coronary lesion assessment in the catheterization laboratory, thereby potentially leading to improved patient outcomes.

CLINICAL TRIAL REGISTRATION

URL: https://www.clinicaltrials.gov . Unique Identifier: NCT03226262.