CFD as treatment support in cardiology

CFD as Non-Invasive Tool for Patient-Specific Diagnosis and Treatment Planning in Cardiology

Patient-specific treatment planning is a new mile stone in cardiology. By means of imaging modalities and segmentation tools, a patient’s heart geometry is extracted and integrated into a CFD model. Thus, flow patterns as well as pressure drops, maximum velocity and vortex formation are calculated and then compared with medical 4D flow MRI data of the patient, allowing validation against the actual hemodynamic outcome of the intervention. Furthermore, the current state of the heart geometry can be manipulated by implanting heart valves prostheses virtually into the original ventricle geometry. Therefore, the current hemodynamic state of a patient’s cardiovascular system can be assessed and diagnosed as well as the expected outcome of a chosen treatment. To simulate different exercise levels, different flow rates are simulated during a short part of the cardiac cycle.

To meet the challenge of limited computational time in clinical routine, two models are compared with regard to time efficiency and quality of results. The first model uses grid deformation analogously to the ventricle movement. This approach mimics real ventricular function and is commonly used, even though it is computationally expensive. The second model compensates volume changes using source and sink terms in porous walls. This approach allows the ventricle to remain stationary, saving computing time. Furthermore, it is justified by the results, which show good consistency with the medical data. Thus, multiple treatment modalities might be tested in-silico, so that the ideal treatment of a patient can be determined, leading to an overall better outcome of surgical or interventional treatment.

Presenter(s): 
Charité Berlin - Biofluid Mechanics Lab
Katharina Vellguth
Session Time Slot(s): 
Time: 
07/03/2017 - 9:20am-07/03/2017 - 9:45am
Room: 
Room I
Presentation Image: 
Session Track: 

Session Tracks (STAR Global Conference 2017)