title: Towards patient-specific cardiovascular modeling system using the immersed boundary technique.
abstract: BACKGROUND
  Previous research shows that the flow dynamics in the left ventricle (LV) reveal important information about cardiac health. This information can be used in early diagnosis of patients with potential heart problems. The current study introduces a patient-specific cardiovascular-modelling system (CMS) which simulates the flow dynamics in the LV to facilitate physicians in early diagnosis of patients before heart failure.
  
  
  METHODS
  The proposed system will identify possible disease conditions and facilitates early diagnosis through hybrid computational fluid dynamics (CFD) simulation and time-resolved magnetic resonance imaging (4-D MRI). The simulation is based on the 3-D heart model, which can simultaneously compute fluid and elastic boundary motions using the immersed boundary method. At this preliminary stage, the 4-D MRI is used to provide an appropriate comparison. This allows flexible investigation of the flow features in the ventricles and their responses.
  
  
  RESULTS
  The results simulate various flow rates and kinetic energy in the diastole and systole phases, demonstrating the feasibility of capturing some of the important characteristics of the heart during different phases. However, some discrepancies exist in the pulmonary vein and aorta flow rate between the numerical and experimental data. Further studies are essential to investigate and solve the remaining problems before using the data in clinical diagnostics.
  
  
  CONCLUSIONS
  The results show that by using a simple reservoir pressure boundary condition (RPBC), we are able to capture some essential variations found in the clinical data. Our approach establishes a first-step framework of a practical patient-specific CMS, which comprises a 3-D CFD model (without involving actual hemodynamic data yet) to simulate the heart and the 4-D PC-MRI system. At this stage, the 4-D PC-MRI system is used for verification purpose rather than input. This brings us closer to our goal of developing a practical patient-specific CMS, which will be pursued next. We anticipate that in the future, this hybrid system can potentially identify possible disease conditions in LV through comprehensive analysis and facilitates physicians in early diagnosis of probable cardiac problems.
authors.affiliation: High Performance Computing & Environmental Fluid Dynamic Laboratory, Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan.
authors.forename: Wee-Beng
authors.initials: WB
authors.lastname: Tay
authors.forename: Yu-Heng
authors.initials: YH
authors.lastname: Tseng
authors.forename: Liang-Yu
authors.initials: LY
authors.lastname: Lin
authors.forename: Wen-Yih
authors.initials: WY
authors.lastname: Tseng
mesh_terms: D000328:Adult; D001783:Blood Flow Velocity / Q000502:physiology; D002319:Cardiovascular System / Q000378:metabolism*; D003198:Computer Simulation; D005260:Female; D006331:Heart Diseases / Q000175:diagnosis*; D006352:Heart Ventricles / Q000378:metabolism; D006439:Hemodynamics; D006801:Humans; D057446:Hydrodynamics; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007700:Kinetics; D008279:Magnetic Resonance Imaging / Q000379:methods; D008955:Models, Cardiovascular; D011312:Pressure