000 05161nam a22004577a 4500
008 210218s20212021 xxu||||| |||| 00| 0 eng d
022 _a1058-2916
024 _a00002480-900000000-98359 [pii]
024 _a10.1097/MAT.0000000000001341 [doi]
040 _aOvid MEDLINE(R)
099 _a33528162
245 _aLeft Ventricular Assist Device Flow Pattern Analysis Using a Novel Model Incorporating Left Ventricular Pulsatility.
251 _aASAIO Journal. 67(7):724-732, 2021 07 01.
252 _aASAIO J. 67(7):724-732, 2021 07 01.
252 _zASAIO J. 2021 Jan 28
253 _aASAIO journal (American Society for Artificial Internal Organs : 1992)
260 _c2021
260 _fFY2021
265 _saheadofprint
265 _sppublish
266 _d2021-02-18
268 _aASAIO Journal. 2021 Jan 28
501 _aAvailable online from MWHC library: 2000 - present, Available in print through MWHC library: 1999 - 2003
520 _aOur current understanding of flow through the circuit of left ventricular assist device (LVAD), left ventricle and ascending aorta remains incompletely understood. Computational fluid dynamics, which allow for analysis of flow in the cardiovascular system, have been used for this purpose, although current simulation models have failed to fully incorporate the interplay between the pulsatile left ventricle and continuous-flow generated by the LVAD. Flow-through the LVAD is dependent on the interaction between device and patient-specific factors with suboptimal flow patterns evoking increased risk of LVAD-related complications. Computational fluid dynamics can be used to analyze how different pump and patient factors affect flow patterns in the left ventricle and the aorta. Computational fluid dynamics simulations were carried out on a patient with a HeartMate II. Simulations were also conducted for theoretical scenarios substituting HeartWare HVAD, HeartMate 3 (HM3) in continuous mode and HM3 with Artificial Pulse. An anatomical model of the patient was reconstructed from computed tomography (CT) images, and the LVAD outflow was used as the inflow boundary condition. The LVAD outflow was calculated separately using a lumped-parameter-model of the systemic circulation, which was calibrated to the patient based on the patient-specific ventricular volume change reconstructed from 4 dimensional computed tomography and pulmonary capillary wedge pressure tracings. The LVADs were implemented in the lumped-parameter-model via published pressure head versus flow (H-Q) curves. To quantify the flushing effect, virtual contrast agent was released in the ascending aorta and its flushing over the cycles was quantified. Shear stress acting on the aortic endothelium and shear rate in the bloodstream were also quantified as indicators of normal/abnormal blood flow, especially the latter being a biomarker of platelet activation and hemolysis. LVAD speeds for the HVAD and HM3 were selected to match flow rates for the patient's HMII (9,000 RPM for HMII, 5,500 RPM for HM3, and 2,200 RPM for HVAD), the cardiac outputs were 5.81 L/min, 5.83 L/min, and 5.92 L/min, respectively. The velocity of blood flow in the outflow cannula was higher in the HVAD than in the two HeartMate pumps with a cycle average (range) of 0.92 m/s (0.78-1.19 m/s), 0.91 m/s (0.86-1.00 m/s), and 1.74 m/s (1.40-2.24 m/s) for HMII, HM3, and HVAD, respectively. Artificial pulse increased the peak flow rate to 9.84 L/min for the HM3 but the overall cardiac output was 5.96 L/min, which was similar to the continuous mode. Artificial pulse markedly decreased blood stagnation in the ascending aorta; after six cardiac cycles, 48% of the blood was flushed out from the ascending aorta under the continuous operation mode while 60% was flushed under artificial pulse. Shear stress and shear rate in the aortic arch were higher with the HVAD compared to the HMII and HM3, respectively (shear stress: 1.76 vs. 1.33 vs. 1.33 Pa, shear rate: 136 vs. 91.5 vs. 89.4 s-1). Pump-specific factors such as LVAD type and programmed flow algorithms lead to unique flow patterns which influence blood stagnation, shear stress, and platelet activation. The pump-patient interaction can be studied using a novel computational fluid dynamics model to better understand and potentially mitigate the risk of downstream LVAD complications. Copyright (c) 2021 by the American Society for Artificial Internal Organs.
546 _aEnglish
650 _a*Heart-Assist Devices
650 _aComputer Simulation
650 _aHeart Failure/su [Surgery]
650 _aHeart Ventricles/dg [Diagnostic Imaging]
650 _aHeart Ventricles/su [Surgery]
650 _aHeart-Assist Devices/ae [Adverse Effects]
650 _aHemodynamics
650 _aHumans
650 _aHydrodynamics
651 _aMedStar Heart & Vascular Institute
657 _aJournal Article
700 _aGarcia-Garcia, Hector M
790 _aBourantas CV, Garcia-Garcia HM, Grinstein J, Torii R
856 _uhttps://dx.doi.org/10.1097/MAT.0000000000001341
_zhttps://dx.doi.org/10.1097/MAT.0000000000001341
942 _cART
_dArticle
999 _c6154
_d6154