A semi-automated method for patient-specific computational flow modelling of left ventricles.
Patient-specific computational fluid dynamics (CFD) modelling of the left ventricle (LV) is a promising technique for the visualisation of ventricular flow patterns throughout a cardiac cycle. While significant progress has been made in improving the physiological quality of such simulations, the methodologies involved for several key steps remain significantly operator-dependent to this day. This dependency limits both the efficiency of the process as well as the consistency of CFD results due to the labour-intensive nature of current methods as well as operator introduced uncertainties in the modelling process. In order to mitigate this dependency, we propose a semi-automated method for patient-specific computational flow modelling of the LV. Using magnetic resonance imaging derived coarse geometry data of a patient's LV endocardium shape throughout a cardiac cycle, we then proceed to refine the geometry to eliminate rough edges before reconstructing meshes for all time frames and finally numerically solving for the intra-ventricular flow. Using a sample of patient-specific volunteer data, we demonstrate that our semi-automated, minimal operator involvement approach is capable of yielding CFD results of the LV that are comparable to other clinically validated LV flow models in the literature.
a Institute of High Performance Computing , 1 Fusionopolis Way, Connexis Tower, Singapore 138632 , Singapore.
Vinh-Tan
VT
Nguyen
Chong Jia
CJ
Loon
Hoang Huy
HH
Nguyen
Zhong
Z
Liang
Hwa Liang
HL
Leo
D001331:Automation; D006352:Heart Ventricles / Q000503:physiopathology*; D006801:Humans; D057446:Hydrodynamics; D008279:Magnetic Resonance Imaging; D008955:Models, Cardiovascular; D009716:Numerical Analysis, Computer-Assisted; D066230:Patient-Specific Modeling; D011312:Pressure; D012039:Regional Blood Flow
cardiac cycle; computational fluid dynamics; geometry reconstruction; left ventricles; patient-specific