Virtual Coronary Intervention: A Treatment Planning Tool Based Upon the Angiogram

Objectives: This study sought to assess the ability of a novel virtual coronary intervention (VCI) tool based on invasive angiography to predict the patient's physiological response to stenting. Background: Fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) is associated with improved clinical and economic outcomes compared with angiographic guidance alone. Virtual (v)FFR can be calculated based upon a 3-dimensional (3D) reconstruction of the coronary anatomy from the angiogram, using computational fluid dynamics (CFD) modeling. This technology can be used to perform virtual stenting, with a predicted post-PCI FFR, and the prospect of optimized treatment planning. Methods: Patients undergoing elective PCI had pressure-wire-based FFR measurements pre- and post-PCI. A 3D reconstruction of the diseased artery was generated from the angiogram and imported into the VIRTUheart workflow, without the need for any invasive physiological measurements. VCI was performed using a radius correction tool replicating the dimensions of the stent deployed during PCI. Virtual FFR (vFFR) was calculated pre- and post-VCI, using CFD analysis. vFFR pre- and post-VCI were compared with measured (m)FFR pre- and post-PCI, respectively. Results: Fifty-four patients and 59 vessels underwent PCI. The mFFR and vFFR pre-PCI were 0.66 ± 0.14 and 0.68 ± 0.13, respectively. Pre-PCI vFFR deviated from mFFR by ±0.05 (mean Δ = -0.02; SD = 0.07). The mean mFFR and vFFR post-PCI/VCI were 0.90 ± 0.05 and 0.92 ± 0.05, respectively. Post-VCI vFFR deviated from post-PCI mFFR by ±0.02 (mean Δ = -0.01; SD = 0.03). Mean CFD processing time was 95 s per case. Conclusions: The authors have developed a novel VCI tool, based upon the angiogram, that predicts the physiological response to stenting with a high degree of accuracy

Effect of side branch flow upon physiological indices in coronary artery disease

Recent efforts have demonstrated the ability of computational models to predict fractional flow reserve from coronary artery imaging without the need for invasive instrumentation. However, these models include only larger coronary arteries as smaller side branches cannot be resolved and are therefore neglected. The goal of this study was to evaluate the impact of neglecting the flow to these side branches when computing angiography-derived fractional flow reserve (vFFR) and indices of volumetric coronary artery blood flow. To compensate for the flow to side branches, a leakage function based upon vessel taper (Murray’s Law) was added to a previously developed computational model of coronary blood flow. The augmented model with a leakage function (1Dleaky) and the original model (1D) were then applied to predict FFR as well as inlet and outlet flow in 146 arteries from 80 patients who underwent invasive coronary angiography and FFR measurement. The results show that the leakage function did not significantly change the vFFR but did significantly impact the estimated volumetric flow rate and predicted coronary flow reserve. As both procedures achieved similar predictive accuracy of vFFR despite large differences in coronary blood flow, these results suggest careful consideration of the application of this index for quantitatively assessing flow

The relationship between coronary stenosis morphology and fractional flow reserve: a computational fluid dynamics modelling study

Aims: International guidelines mandate the use of fractional flow reserve (FFR) and/or non-hyperaemic pressure ratios to assess the physiological significance of moderate coronary artery lesions to guide revascularization decisions. However, they remain underused such that visual estimation of lesion severity continues to be the predominant decision-making tool. It would be pragmatic to have an improved understanding of the relationship between lesion morphology and haemodynamics. The aim of this study was to compute virtual FFR (vFFR) in idealized coronary artery geometries with a variety of stenosis and vessel characteristics. Methods and results: Coronary artery geometries were modelled, based upon physiologically realistic branched arteries. Common stenosis characteristics were studied, including % narrowing, length, eccentricity, shape, number, position relative to branch, and distal (myocardial) resistance. Computational fluid dynamics modelling was used to calculate vFFRs using the VIRTUheart™ system. Percentage lesion severity had the greatest effect upon FFR. Any ≥80% diameter stenosis in two views (i.e. concentric) was physiologically significant (FFR ≤ 0.80), irrespective of length, shape, or vessel diameter. Almost all eccentric stenoses and all 50% concentric stenoses were physiologically non-significant, whilst 70% uniform concentric stenoses about 10 mm long straddled the ischaemic threshold (FFR 0.80). A low microvascular resistance (MVR) reduced FFR on average by 0.05, and a high MVR increased it by 0.03. Conclusion: Using computational modelling, we have produced an analysis of vFFR that relates stenosis characteristics to haemodynamic significance. The strongest predictor of a positive vFFR was a concentric, ≥80% diameter stenosis. The importance of MVR was quantified. Other lesion characteristics have a limited impact

Incorporating clinical parameters to improve the accuracy of angiography-derived computed fractional flow reserve

Aims Angiography-derived fractional flow reserve (angio-FFR) permits physiological lesion assessment without the need for an invasive pressure wire or induction of hyperaemia. However, accuracy is limited by assumptions made when defining the distal boundary, namely coronary microvascular resistance (CMVR). We sought to determine whether machine learning (ML) techniques could provide a patient-specific estimate of CMVR and therefore improve the accuracy of angio-FFR. Methods and results Patients with chronic coronary syndromes underwent coronary angiography with FFR assessment. Vessel-specific CMVR was computed using a three-dimensional computational fluid dynamics simulation with invasively measured proximal and distal pressures applied as boundary conditions. Predictive models were created using non-linear autoregressive moving average with exogenous input (NARMAX) modelling with computed CMVR as the dependent variable. Angio-FFR (VIRTUheart™) was computed using previously described methods. Three simulations were run: using a generic CMVR value (Model A); using ML-predicted CMVR based upon simple clinical data (Model B); and using ML-predicted CMVR also incorporating echocardiographic data (Model C). The diagnostic (FFR ≤ or >0.80) and absolute accuracies of these models were compared. Eighty-four patients underwent coronary angiography with FFR assessment in 157 vessels. The mean measured FFR was 0.79 (±0.15). The diagnostic and absolute accuracies of each personalized model were: (A) 73% and ±0.10; (B) 81% and ±0.07; and (C) 89% and ±0.05, P < 0.001. Conclusion The accuracy of angio-FFR was dependent in part upon CMVR estimation. Personalization of CMVR from standard clinical data resulted in a significant reduction in angio-FFR error

Time-variability in the Interstellar Boundary Conditions of the Heliosphere: Effect of the Solar Journey on the Galactic Cosmic Ray Flux at Earth

During the solar journey through galactic space, variations in the physical properties of the surrounding interstellar medium (ISM) modify the heliosphere and modulate the flux of galactic cosmic rays (GCR) at the surface of the Earth, with consequences for the terrestrial record of cosmogenic radionuclides. One phenomenon that needs studying is the effect on cosmogenic isotope production of changing anomalous cosmic ray fluxes at Earth due to variable interstellar ionizations. The possible range of interstellar ram pressures and ionization levels in the low density solar environment generate dramatically different possible heliosphere configurations, with a wide range of particle fluxes of interstellar neutrals, their secondary products, and GCRs arriving at Earth. Simple models of the distribution and densities of ISM in the downwind direction give cloud transition timescales that can be directly compared with cosmogenic radionuclide geologic records. Both the interstellar data and cosmogenic radionuclide data are consistent with cloud transitions during the Holocene, with large and assumption-dependent uncertainties. The geomagnetic timeline derived from cosmic ray fluxes at Earth may require adjustment to account for the disappearance of anomalous cosmic rays when the Sun is immersed in ionized gas.Comment: Submitted to Space Sciences Review

Modelling the hemodynamics of coronary ischemia

Acting upon clinical patient data, acquired in the pathway of percutaneous intervention, we deploy hierarchical, multi-stage, data-handling protocols and interacting low- and high-order mathematical models (chamber elastance, state-space system and CFD models), to establish and then validate a framework to quantify the burden of ischaemia. Our core tool is a compartmental, zero-dimensional model of the coupled circulation with four heart chambers, systemic and pulmonary circulations and an optimally adapted windkessel model of the coronary arteries that reflects the diastolic dominance of coronary flow. We guide the parallel development of protocols and models by appealing to foundational physiological principles of cardiac energetics and a parameterisation (stenotic Bernoulli resistance and micro-vascular resistance) of patients’ coronary flow. We validate our process first with results which substantiate our protocols and, second, we demonstrate good correspondence between model operation and patient data. We conclude that our core model is capable of representing (patho)physiological states and discuss how it can potentially be deployed, on clinical data, to provide a quantitative assessment of the impact, on the individual, of coronary artery disease

Quantifying myocardial blood flow and resistance using 4D-flow cardiac magnetic resonance imaging

Background. Ischaemia with nonobstructive coronary arteries is most commonly caused by coronary microvascular dysfunction but remains difcult to diagnose without invasive testing. Myocardial blood fow (MBF) can be quantifed noninvasively on stress perfusion cardiac magnetic resonance (CMR) or positron emission tomography but neither is routinely used in clinical practice due to practical and technical constraints. Quantifcation of coronary sinus (CS) fow may represent a simpler method for CMR MBF quantifcation. 4D fow CMR ofers comprehensive intracardiac and transvalvular fow quantifcation. However, it is feasibility to quantify MBF remains unknown. Methods. Patients with acute myocardial infarction (MI) and healthy volunteers underwent CMR. Te CS contours were traced from the 2-chamber view. A reformatted phase contrast plane was generated through the CS, and fow was quantifed using 4D fow CMR over the cardiac cycle and normalised for myocardial mass. MBF and resistance (MyoR) was determined in ten healthy volunteers, ten patients with myocardial infarction (MI) without microvascular obstruction (MVO), and ten with known MVO. Results. MBF was quantifed in all 30 subjects. MBF was highest in healthy controls (123.8 ± 48.4 mL/min), signifcantly lower in those with MI (85.7 ± 30.5 mL/min), and even lower in those with MI and MVO (67.9 ± 29.2 mL/min/) (P < 0.01 for both diferences). Compared with healthy controls, MyoR was higher in those with MI and even higher in those with MI and MVO (0.79 (±0.35) versus 1.10 (±0.50) versus 1.50 (±0.69), P = 0.02). Conclusions. MBF and MyoR can be quantifed from 4D fow CMR. Resting MBF was reduced in patients with MI and MVO

Indicadores de qualidade do solo em sistemas de cultivo orgânico e convencional no semi-árido Cearense.

A qualidade do solo pode mudar com o passar do tempo, em decorrência de eventos naturais ou ações antrópicas. A adoção de práticas de cultivo orgânico reduz o revolvimento do solo, favorecendo a recuperação de suas propriedades físicas e químicas. Este trabalho teve como objetivo comparar propriedades físicas,químicas e biológicas de solos cultivados com algodão em bases orgânicas e no sistema convencional, assim como identificar as que possam ser utilizadas como indicadores de qualidade do solo. Selecionaram-se seis áreas submetidas ao cultivo orgânico e três ao cultivo convencional para coleta de amostras de solo deformadas e indeformadas, nas camadas de 0–10, 10–20 e 20–30 cm. Técnicas de estatística univariada e multivariada foram utilizadas para análise dos dados. Os resultados mostraram que os indicadores físicos e químicos testados individualmente não foram sensíveis para diferenciar as áreas sob sistema de cultivo orgânico daquelas sob cultivo convencional. No entanto, a aplicação de técnicas de análise multivariada – no caso, componentes principais e a discriminante de Anderson – permitiu a distinção entre algumas áreas cultivadas sob cultivo orgânico comparativamente às convencionais, até mesmo as que estavam em transição.Dos indicadores biológicos, a fauna edáfica mostrou-se mais precisa na avaliação da qualidade do solo, distinguindo de forma satisfatória as áreas sob sistema de cultivo orgânico das que estavam sob sistema convencional

The Physical Processes of CME/ICME Evolution

As observed in Thomson-scattered white light, coronal mass ejections (CMEs) are manifest as large-scale expulsions of plasma magnetically driven from the corona in the most energetic eruptions from the Sun. It remains a tantalizing mystery as to how these erupting magnetic fields evolve to form the complex structures we observe in the solar wind at Earth. Here, we strive to provide a fresh perspective on the post-eruption and interplanetary evolution of CMEs, focusing on the physical processes that define the many complex interactions of the ejected plasma with its surroundings as it departs the corona and propagates through the heliosphere. We summarize the ways CMEs and their interplanetary CMEs (ICMEs) are rotated, reconfigured, deformed, deflected, decelerated and disguised during their journey through the solar wind. This study then leads to consideration of how structures originating in coronal eruptions can be connected to their far removed interplanetary counterparts. Given that ICMEs are the drivers of most geomagnetic storms (and the sole driver of extreme storms), this work provides a guide to the processes that must be considered in making space weather forecasts from remote observations of the corona.Peer reviewe