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Modeling Aortic Insufficiency in the Scranton Cardiovascular Model
Author(s) -
Graham Michelle Theresa
Publication year - 2016
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.30.1_supplement.553.32
Subject(s) - contractility , hemodynamics , cardiology , medicine , mean arterial pressure , aortic valve , cardiac output , pulse pressure , aortic pressure , blood pressure , heart rate
The effects of aortic insufficiency (AI) on cardiovascular hemodynamics are well known. Mean arterial pressure (MAP) decreases, driving compensatory mechanisms to reestablish MAP within a normal range. However, there are few pedagogical models designed to address instruction in the cardiovascular ramifications of valvular dysfunction. The Scranton Cardiovascular Model (SCM), a computer‐driven, fluid pumping, mechanical model of the cardiovascular system, was developed to improve cardiovascular physiology education1. We have extended the capabilities of the SCM to enable modeling of the hemodynamics of valvular dysfunction. A new component was fabricated to allow the normal SCM aortic valve to be quickly and reversibly replaced by a dysfunctional aortic valve. Insufficient valves of quantifiable regurgitant orifice area were designed and implemented to demonstrate systemic effects of progressive dysfunction, comparable to clinical data. The capability to model acute uncompensated AI and acute compensated AI was demonstrated through analysis of cardiac parameters such as mean arterial pressure, cardiac output, pulse pressure, and left ventricular end diastolic pressure. To simulate acute compensated AI, total peripheral resistance (TPR), contractility, and central venous tone were manipulated in the SCM until normal MAP was reestablished. Corresponding forward cardiac output (CO) reflected cardiovascular system efficacy. In uncompensated severe AI, MAP and CO, respectively, decreased to 66% and 73% of basal values. Multiple compensatory settings successfully reestablished normal MAP. The magnitude of the individual contributions of TPR and contractility to the restoration of MAP differentially impacted CO. Increased TPR restored MAP while decreasing CO. Increased contractility restored MAP while improving CO. We continue to fine‐tune SCM AI to more closely match clinical data. This “proof of concept” opens up a new pedagogical application for the SCM. Support or Funding Information Supported by the University of Scranton