Annals of Biomedical Engineering

, Volume 43, Issue 6, pp 1335–1347

Computational Modeling of Pathophysiologic Responses to Exercise in Fontan Patients

  • Ethan Kung
  • James C. Perry
  • Christopher Davis
  • Francesco Migliavacca
  • Giancarlo Pennati
  • Alessandro Giardini
  • Tain-Yen Hsia
  • Alison Marsden
Article

DOI: 10.1007/s10439-014-1131-4

Cite this article as:
Kung, E., Perry, J.C., Davis, C. et al. Ann Biomed Eng (2015) 43: 1335. doi:10.1007/s10439-014-1131-4

Abstract

Reduced exercise capacity is nearly universal among Fontan patients. Although many factors have emerged as possible contributors, the degree to which each impacts the overall hemodynamics is largely unknown. Computational modeling provides a means to test hypotheses of causes of exercise intolerance via precisely controlled virtual experiments and measurements. We quantified the physiological impacts of commonly encountered, clinically relevant dysfunctions introduced to the exercising Fontan system via a previously developed lumped-parameter model of Fontan exercise. Elevated pulmonary arterial pressure was observed in all cases of dysfunction, correlated with lowered cardiac output (CO), and often mediated by elevated atrial pressure. Pulmonary vascular resistance was not the most significant factor affecting exercise performance as measured by CO. In the absence of other dysfunctions, atrioventricular valve insufficiency alone had significant physiological impact, especially under exercise demands. The impact of isolated dysfunctions can be linearly summed to approximate the combined impact of several dysfunctions occurring in the same system. A single dominant cause of exercise intolerance was not identified, though several hypothesized dysfunctions each led to variable decreases in performance. Computational predictions of performance improvement associated with various interventions should be weighed against procedural risks and potential complications, contributing to improvements in routine patient management protocol.

Keywords

Lumped-parameter model Dysfunction Single-ventricle Closed-loop Simulation Pulmonary pressure Regurgitation 

Abbreviations

APVR

Abnormal pulmonary vascular response

AV

Atrio-ventricular

AVB

1st degree AV block

AVVI

AV valve insufficiency

ChI

Chronotropic insufficiency

CO

Cardiac output in L/min

DR

Disordered respiration

DiasD

Diastolic dysfunction

MET

Metabolic equivalent in units of 3.5 mL O2 kg−1 min−1

PA

Pulmonary arterial

PVR

Pulmonary vascular resistance

SysD

Systolic dysfunction

SV

Stroke volume

Supplementary material

10439_2014_1131_MOESM1_ESM.docx (61 kb)
Supplementary material 1 (DOCX 62 kb)
10439_2014_1131_MOESM2_ESM.docx (3.2 mb)
Supplementary material 2 (DOCX 3234 kb)

Copyright information

© Biomedical Engineering Society 2014

Authors and Affiliations

  • Ethan Kung
    • 1
    • 2
  • James C. Perry
    • 3
  • Christopher Davis
    • 3
  • Francesco Migliavacca
    • 4
  • Giancarlo Pennati
    • 4
  • Alessandro Giardini
    • 5
  • Tain-Yen Hsia
    • 5
  • Alison Marsden
    • 2
  1. 1.Mechanical Engineering DepartmentClemson UniversityClemsonUSA
  2. 2.Mechanical and Aerospace Engineering DepartmentUniversity of California San DiegoLa JollaUSA
  3. 3.Rady Children’s Hospital/University of California San DiegoSan DiegoUSA
  4. 4.Department of Chemistry, Material and Chemical Engineering “Giulio Natta”Politecnico di MilanoMilanItaly
  5. 5.Great Ormond Street Hospital for ChildrenLondonUK

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