• Comput Methods Programs Biomed · Jul 2018

    Development of an adaptive pulmonary simulator for in vitro analysis of patient populations and patient-specific data.

    • Jacob M King, Clint A Bergeron, and Charles E Taylor.
    • Cajun Artificial Heart Laboratory, Mechanical Engineering Department, University of Louisiana at Lafayette, 241 E. Lewis St. RM320, Lafayette, LA 70503, United States.
    • Comput Methods Programs Biomed. 2018 Jul 1; 161: 93-102.

    Background And ObjectivePatient-specific modeling (PSM) is gaining more attention from researchers due to its ability to potentially improve diagnostic capabilities, guide the design of intervention procedures, and optimize clinical management by predicting the outcome of a particular treatment and/or surgical intervention. Due to the hemodynamic diversity of specific patients, an adaptive pulmonary simulator (PS) would be essential for analyzing the possible impact of external factors on the safety, performance, and reliability of a cardiac assist device within a mock circulatory system (MCS). In order to accurately and precisely replicate the conditions within the pulmonary system, a PS should not only account for the ability of the pulmonary system to supply blood flow at specific pressures, but similarly consider systemic outflow dynamics. This would provide an accurate pressure and flow rate return supply back into the left ventricular section of the MCS (i.e. the initial conditions of the left heart).MethodsEmploying an embedded Windkessel model, a control system model was developed utilizing MathWorks' Simulink® Simscape™. Following a verification and validation (V&V) analysis approach, a PI-controlled closed-loop hydraulic system was developed using Simscape™. This physical system modeling tool was used to (1) develop and control the in silico system during verification studies and (2) simulate pulmonary performance for validation of this control architecture.ResultsThe pulmonary Windkessel model developed is capable of generating the left atrial pressure (LAP) waveform from given pulmonary factors, aortic conditions, and systemic variables. Verification of the adaptive PS's performance and validation of this control architecture support this modeling methodology as an effective means of reproducing pulmonary pressure waveforms and systemic outflow conditions, unique to a particular patient. Adult and geriatric with and without Heart Failure and a Normal Ejection Fraction (HFNEF) are presented.ConclusionsThe adaptability of this modelling approach allows for the simulation of pulmonary conditions without the limitations of a dedicated hardware platform for use in in vitro investigations.Copyright © 2018 Elsevier B.V. All rights reserved.

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