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.

Importance of realistic LVAD profiles for assisted aortic simulations: evaluation of optimal outflow anastomosis locations.

Left ventricular assist devices (LVADs) are carefully designed, but the significance of the implantation configuration and interaction with the vasculature is complex and not fully determined. The present study employs computational fluid dynamics to investigate the importance of applying a realistic LVAD profile when evaluating assisted aortic flow fields and subsequently compares a number of potential anastomosis locations in a patient-specific aortic geometry. The outflow profile of the Berlin Heart INCOR® device was provided by Berlin Heart GmbH (Berlin, Germany) and the cannula was attached at a number of locations on the aorta. Simulations were conducted to compare a flat profile against the real LVAD profile. The results illustrate the importance of applying an LVAD profile. It not only affects the magnitude and distribution of oscillatory shear index, but also the distribution of flow to the great arteries. The ascending aorta was identified as the optimal location for the anastomosis.

A framework for the modeling of gut blood flow regulation and postprandial hyperaemia.

After a meal the activity of the gut increases markedly as digestion takes place. Associated with this increase in activity is an increase in blood flow, which has been shown to be dependent on factors such as caloric content and constitution of the meal. Much qualitative work has been carried out regarding mechanisms for the presence of food in a section of gut producing increased blood flow to that section, but there are still many aspects of this process that are not fully understood. In this paper we briefly review current knowledge on several relevant areas relating to gut blood flow, focusing on quantitative data where available and highlighting areas where further research is needed. We then present new data on the effect of feeding on flow in the superior mesenteric artery. Finally, we describe a framework for combining this data to produce a single model describing the mechanisms involved in postprandial hyperaemia. For a section of the model, where appropriate data are available, preliminary results are presented.

Fundamental mechanics of aortic heart valve closure.

Stresses in a prosthetic heart valve at closure are determined by its geometrical and structural characteristics, by the mechanical support environment, and by the momentum of the valve leaflets or occluder and of the blood at the instant of closure. The mass of blood to be arrested is significantly greater than that of the leaflets or occluder, and is therefore likely to dominate the closure impulse. The kinetic energy of the blood must be transduced into potential energy in the structural components (valve leaflets, aortic root and aorta). This paper presents a methodology for computation and parameterisation of the blood momentum associated with a valve in the aortic position. It is suggested that the influence of physiological parameters, such as systolic waveform and systemic impedance, on the closure characteristics can be investigated based on the fluid dynamic implications. Detailed results are presented for a single leaflet mechanical valve (Bjork-Shiley 60 degrees Convexo-Concave). It is demonstrated that a simple analytical method can yield results that might be adequate for the purposes of valve design.