Semi-Automatic Reconstruction of Patient-Specific Stented Coronaries based on Data Assimilation and Computer Aided Design

Purpose The interplay between geometry and hemodynamics is a significant factor in the development of cardiovascular diseases. This is particularly true for stented coronary arteries. To elucidate this factor, an accurate patient-specific analysis requires the reconstruction of the geometry following the stent deployment for a computational fluid dynamics (CFD) investigation. The image-based reconstruction is troublesome for the different possible positions of the stent struts in the lumen and the coronary wall. However, the accurate inclusion of the stent footprint in the hemodynamic analysis is critical for detecting abnormal stress conditions and flow disturbances, particularly for thick struts like in bioresorbable scaffolds. Here, we present a novel reconstruction methodology that relies on Data Assimilation and Computer Aided Design. Methods The combination of the geometrical model of the undeployed stent and image-based data assimilated by a variational approach allows the highly automated reconstruction of the skeleton of the stent. A novel approach based on computational mechanics defines the map between the intravascular frame of reference (called L-view) and the 3D geometry retrieved from angiographies. Finally, the volumetric expansion of the stent skeleton needs to be self-intersection free for the successive CFD studies; this is obtained by using implicit representations based on the definition of Nef-polyhedra. Results We assessed our approach on a vessel phantom, with less than 10% difference (properly measured) vs. a customized manual (and longer) procedure previously published, yet with a significant higher level of automation and a shorter turnaround time. Computational hemodynamics results were even closer. We tested the approach on two patient-specific cases as well. Conclusions The method presented here has a high level of automation and excellent accuracy performances, so it can be used for larger studies involving patient-specific geometries

On a fictitious domain method with distributed Lagrange multiplier for interface problems

In this paper we propose a new variational formulation for an elliptic interface problem and discuss its finite element approximation. Our formulation fits within the framework of fictitious domain methods with distributed Lagrange multipliers. For the underlying mixed scheme we prove stability and convergence. Some preliminary numerical tests confirm the theoretical investigations

Patient-specific CFD modelling in the thoracic aorta with PC-MRI–based boundary conditions: A least-square three-element Windkessel approach

The increasing use of computational fluid dynamics for simulating blood flow in clinics demands the identification of appropriate patient-specific boundary conditions for the customization of the mathematical models. These conditions should ideally be retrieved from measurements. However, finite resolution of devices as well as other practical/ethical reasons prevent the construction of complete data sets necessary to make the mathematical problems well posed. Available data need to be completed by modelling assumptions, whose impact on the final solution has to be carefully addressed. Focusing on aortic vascular districts and related pathologies, we present here a method for efficiently and robustly prescribing phase contrast MRI-based patient-specific data as boundary conditions at the domain of interest. In particular, for the outlets, the basic idea is to obtain pressure conditions from an appropriate elaboration of available flow rates on the basis of a 3D/0D dimensionally heterogeneous modelling. The key point is that the parameters are obtained by a constrained optimization procedure. The rationale is that pressure conditions have a reduced impact on the numerical solution compared with velocity conditions, yielding a simulation framework less exposed to noise and inconsistency of the data, as well as to the arbitrariness of the underlying modelling assumptions. Numerical results confirm the reliability of the approach in comparison with other patient-specific approaches adopted in the literature

Computational study of aortic hemodynamics: From simplified to patient-specific geometries

The investigation of aortic hemodynamics in physiological and pathological conditions by computational fluid dynamics is still one of the major topic of vascular biomechanics. In particular,thanks to the developments of new endovascular technologies such as Thoracic EndoVAscular Repair (TEVAR),a lot of attention is paid to the hemodynamics analysis of thoracic aorta. In this work,we aim at performing a sensitivity analysis of morphological aspects by comparing numerical results about three cases: (i) an idealized aortic arch with a candy cane shape; (ii) a patient-specific healthy arch; and (iii) a patient-specific dissected aorta. For the idealized aortic arch case we also compare the obtained results with respect to the theoretical and experimental literature dedicated to curved pipes

Assessment of a Black-Box Approach for a Parallel Finite Elements Solver in Computational Hemodynamics

Numerical approximation of blood flow has emerged in the last 20 years as a tool to investigate physiopathology of the circulation, moving from a proof-of-concept to a clinical stage. By merging medical images with numerical models it is possible to support the decision-making process of surgeons and doctors in general. In particular, the iCardioCloud project aims at establishing a framework to perform a complete patient-specific hemodynamics analysis for aortic diseases such as dissections, occlusions and aneurysms. From a computer science standpoint, such a project faces multiple challenges. First of all the dimension of the problem in terms of number of equations to be solved for each patient is in general huge and thus it requires massively parallel methods. In addition, clinical timeline demands for efficiency, since availability of results – at least in an emergency scenario – should be granted in few hours from data retrieval. Therefore it is mandatory to develop a good implementation on high-end parallel systems, such as large clusters or even supercomputers. Unfortunately, it is not straightforward to obtain an efficient implementation on such machines. In this paper we discuss a parallel implementation obtained with a black-box approach, that is set up by assembling existing packages and libraries and in particular LifeV, a finite element library developed for Computational Fluid Dynamics. The ultimate goal is to assess if the application can be solved efficiently and which is the parallel paradigm that best matches the computational requirements

Computational methods in cardiovascular mechanics

The introduction of computational models in cardiovascular sciences has been progressively bringing new and unique tools for the investigation of the physiopathology. Together with the dramatic improvement of imaging and measuring devices on one side, and of computational architectures on the other one, mathematical and numerical models have provided a new, clearly noninvasive, approach for understanding not only basic mechanisms but also patient-specific conditions, and for supporting the design and the development of new therapeutic options. The terminology in silico is, nowadays, commonly accepted for indicating this new source of knowledge added to traditional in vitro and in vivo investigations. The advantages of in silico methodologies are basically the low cost in terms of infrastructures and facilities, the reduced invasiveness and, in general, the intrinsic predictive capabilities based on the use of mathematical models. The disadvantages are generally identified in the distance between the real cases and their virtual counterpart required by the conceptual modeling that can be detrimental for the reliability of numerical simulation

Benchmarking a hemodynamics application on Intel based HPC systems

Three different INTEL based HPC systems are used to benchmark an application of the LifeV library for running simulations of patient-specific cardiovascular hemodynamics. The targeted INTEL architectures rely on the Hashwell-Broadwell family of processors. Running times and scalability measures are collected with two real-size experiments. A third small-size test case is used to profile the code, exposing the effect of compiler vectorization, MPI efficiency and memory footprint. Profiling showed an unexpected low degree of floating point functional units usage, and a low percentage of effective vectorization. Extensive code redesign is likely necessary to best exploit the architectural features available in INTEL Knight Landing processors

Aortic hemodynamics after thoracic endovascular aortic repair, with particular attention to the bird-beak configuration

Purpose: To quantitatively evaluate the impact of thoracic endovascular aortic repair (TEVAR) on aortic hemodynamics, focusing on the implications of a bird-beak configuration. Methods: Pre- and postoperative CTA images from a patient treated with TEVAR for post-dissecting thoracic aortic aneurysm were used to evaluate the anatomical changes induced by the stent-graft and to generate the computational network essential for computational fluid dynamics (CFD) analysis. These analyses focused on the bird-beak configuration, flow distribution into the supra-aortic branches, and narrowing of the distal descending thoracic aorta. Three different CFD analyses (A: preoperative lumen, B: postoperative lumen, and C: postoperative lumen computed without stenosis) were compared at 3 time points during the cardiac cycle (maximum acceleration of blood flow, systolic peak, and maximum deceleration of blood flow). Results: Postoperatively, disturbance of flow was reduced at the bird-beak location due to boundary conditions and change of geometry after TEVAR. Stent-graft protrusion with partial coverage of the origin of the left subclavian artery produced a disturbance of flow in this vessel. Strong velocity increase and flow disturbance were found at the aortic narrowing in the descending thoracic aorta when comparing B and C, while no effect was seen on aortic arch hemodynamics. Conclusion: CFD may help physicians to understand aortic hemodynamic changes after TEVAR, including the change in aortic arch geometry, the effects of a bird-beak configuration, the supra-aortic flow distribution, and the aortic true lumen dynamics. This study is the first step in establishing a computational framework that, when completed with patient-specific data, will allow us to study thoracic aortic pathologies and their endovascular management