Flow disturbances in stent-related coronary evaginations: a computational fluid-dynamic simulation study

Aims: Angiographic ectasias and aneurysms in stented segments have been associated with late stent thrombosis. Using optical coherence tomography (OCT), some stented segments show coronary evaginations reminiscent of ectasias. The purpose of this study was to explore, using computational fluid-dynamic (CFD) simulations, whether OCT-detected coronary evaginations can induce local changes in blood flow. Methods and results: OCT-detected evaginations are defined as outward bulges in the luminal vessel contour between struts, with the depth of the bulge exceeding the actual strut thickness. Evaginations can be characterised cross ectionally by depth and along the stented segment by total length. Assuming an ellipsoid shape, we modelled 3-D evaginations with different sizes by varying the depth from 0.2-1.0 mm, and the length from 1-9 mm. For the flow simulation we used average flow velocity data from non-diseased coronary arteries. The change in flow with varying evagination sizes was assessed using a particle tracing test where the particle transit time within the segment with evagination was compared with that of a control vessel. The presence of the evagination caused a delayed particle transit time which increased with the evagination size. The change in flow consisted locally of recirculation within the evagination, as well as flow deceleration due to a larger lumen - seen as a deflection of flow towards the evagination. Conclusions: CFD simulation of 3-D evaginations and blood flow suggests that evaginations affect flow locally, with a flow disturbance that increases with increasing evagination size.

State-of-the-art aortic imaging: Part II - applications in transcatheter aortic valve replacement and endovascular aortic aneurysm repair.

Transcatheter aortic valve replacement (TAVR) as well as thoracic and abdominal endovascular aortic repair (TEVAR and EVAR) rely on accurate pre- and postprocedural imaging. This review article discusses the application of imaging, including preprocedural assessment and measurements as well as postprocedural imaging of complications. Furthermore, the exciting perspective of computational fluid dynamics (CFD) based on cross-sectional imaging is presented. TAVR is a minimally invasive alternative for treatment of aortic valve stenosis in patients with high age and multiple comorbidities who cannot undergo traditional open surgical repair. Given the lack of direct visualization during the procedure, pre- and peri-procedural imaging forms an essential part of the intervention. Computed tomography angiography (CTA) is the imaging modality of choice for preprocedural planning. Routine postprocedural follow-up is performed by echocardiography to confirm treatment success and detect complications. EVAR and TEVAR are minimally invasive alternatives to open surgical repair of aortic pathologies. CTA constitutes the preferred imaging modality for both preoperative planning and postoperative follow-up including detection of endoleaks. Magnetic resonance imaging is an excellent alternative to CT for postoperative follow-up, and is especially beneficial for younger patients given the lack of radiation. Ultrasound is applied in screening and postoperative follow-up of abdominal aortic aneurysms, but cross-sectional imaging is required once abnormalities are detected. Contrast-enhanced ultrasound may be as sensitive as CTA in detecting endoleaks.

Review of recent results using computational fluid dynamics simulations in patients receiving mechanical assist devices for end-stage heart failure

Many end-stage heart failure patients are not eligible to undergo heart transplantation due to organ shortage, and even those under consideration for transplantation might suffer long waiting periods. A better understanding of the hemodynamic impact of left ventricular assist devices (LVAD) on the cardiovascular system is therefore of great interest. Computational fluid dynamics (CFD) simulations give the opportunity to study the hemodynamics in this patient population using clinical imaging data such as computed tomographic angiography. This article reviews a recent study series involving patients with pulsatile and constant-flow LVAD devices in which CFD simulations were used to qualitatively and quantitatively assess blood flow dynamics in the thoracic aorta, demonstrating its potential to enhance the information available from medical imaging.

Computational fluid dynamics modelling in cardiovascular medicine.

This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges.