A pipeline for image based intracardiac CFD modeling and application to the evaluation of the PISA method

• Published in: Computer methods in applied mechanics and engineering 2020-01, Vol.358, p.112627, Article 112627
• Main Authors: This, Alexandre, Morales, Hernán G., Bonnefous, Odile, Fernández, Miguel A., Gerbeau, Jean-Frédéric
• Format: Article
• Language: English
• Subjects: Aliasing; Computer Science; Computer simulation; Echocardiography; Electrocardiography; Evaluation; Heart diseases; Heart valves; Hemodynamics; Mathematical models; Mitral regurgitation; Numerical Analysis; Numerical simulation; Patient-specific; Pipelines; Spatial resolution
• ISSN: 0045-7825; 1879-2138
• DOI: 10.1016/j.cma.2019.112627

Mitral regurgitation is one of the most prevalent valvular heart disease. Proper evaluation of its severity is necessary to choose appropriate treatment. The PISA method, based on Color Doppler echocardiography, is widely used in the clinical setting to estimate various relevant quantities related to the severity of the disease. In this paper, the use of a pipeline to quickly generate image-based numerical simulation of intracardiac hemodynamics is investigated. The pipeline capabilities are evaluated on a database of twelve volunteers. Full pre-processing is achieved completely automatically in 55 min, on average, with small registration errors compared to the image spatial resolution. This pipeline is then used to study the intracardiac hemodynamics in the presence of diseased mitral valve. A strong variability among the simulated cases, mainly due to the valve geometry and regurgitation specifics, is found. The results from those numerical simulations are used to assess the potential limitations of the PISA method with respect to different MR types. While the PISA method provides reasonable estimates in the case of a simple circular regurgitation, it is shown that unsatisfying estimates are obtained in the case of non-circular leakage. Moreover, it is shown that the choice of high aliasing velocities can lead to difficulties in quantifying MR. •Automatic and fast generation of personalized CFD models.•Generation of a library of pathological cases based on a database of sequences.•Confirmation that the PISA method is adapted in simple mitral regurgitation cases.•Description of pathological situations in which PISA might not be adapted.