Model-Based Indices of Early-Stage Cardiovascular Failure and Its Therapeutic Management in Fontan Patients

Ruijsink, Bram; Zugaj, Konrad; Pushparajah, Kuberan; Chabiniok, Radomí­r

doi:10.1007/978-3-030-21949-9_41

Cited by 5 publications

(5 citation statements)

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“…Patient-specific CV modeling provides a numerical representation of the CV system in individual patients-a "numerical avatar"-which is becoming a powerful diagnostic or therapeutic tool. For example, it allows to access the PV loop [8][9][10], predict the success of cardiac resynchronization therapy [11,12], or estimate myocardial stiffness and contractility or vascular resistance [13][14][15] including under various physiological conditions [16,17], see also reviews [18,19] and references therein. However, a requirement of fast analysis alongside with restricted data availability make its implementation within CV monitoring rather challenging.…”

Section: Introductionmentioning

confidence: 99%

Monitoring of cardiovascular physiology augmented by a patient-specific biomechanical model during general anesthesia. A proof of concept study

et al. 2020

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During general anesthesia (GA), direct analysis of arterial pressure or aortic flow waveforms may be inconclusive in complex situations. Patient-specific biomechanical models, based on data obtained during GA and capable to perform fast simulations of cardiac cycles, have the potential to augment hemodynamic monitoring. Such models allow to simulate Pressure-Volume (PV) loops and estimate functional indicators of cardiovascular (CV) system, e.g. ventricular-arterial coupling (V va), cardiac efficiency (CE) or myocardial contractility, evolving throughout GA. In this prospective observational study, we created patient-specific biomechanical models of heart and vasculature of a reduced geometric complexity for n = 45 patients undergoing GA, while using transthoracic echocardiography and aortic pressure and flow signals acquired in the beginning of GA (baseline condition). If intraoperative hypotension (IOH) appeared, diluted norepinephrine (NOR) was administered and the model readjusted according to the measured aortic pressure and flow signals. Such patients were a posteriori assigned into a so-called hypotensive group. The accuracy of simulated mean aortic pressure (MAP) and stroke volume (SV) at baseline were in accordance with the guidelines for the validation of new devices or reference measurement methods in all patients. After NOR administration in the hypotensive group, the percentage of concordance with 10% exclusion zone between measurement and simulation was >95% for both MAP and SV. The modeling results showed a decreased V va (0.64±0.37 vs 0.88±0.43; p = 0.039) and an increased CE (0.8±0.1 vs 0.73±0.11; p = 0.042) in hypotensive vs normotensive patients. Furthermore, V va increased by 92±101%, CE decreased by 13±11% (p < 0.001 for both) and contractility increased by 14±11% (p = 0.002) in the hypotensive group post-NOR administration. In this work we demonstrated the application of fast-running patient-specific biophysical models to estimate PV loops and functional indicators of CV system using

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Section: Introductionmentioning

confidence: 99%

Monitoring of cardiovascular physiology augmented by a patient-specific biomechanical model during general anesthesia. A proof of concept study

et al. 2020

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“…In the future, we can anticipate a fast CFD model suggesting the optimal positioning of the measurement slice, prior to performing a high-fidelity 2D-flow measurement. The superior spatio-temporal resolution or fast acquistions may be crucial (and advantageous even to 4D flow acquisitions) in some applications, e.g., for flow measurement under pharmacological or exercise stress [32,31]. Indeed, the highest flow rate in our experiment corresponds to the situation of increased cardiac output.…”

Section: Perspectives Of the Workmentioning

confidence: 90%

Investigation of phase-contrast magnetic resonance imaging underestimation of turbulent flow through the aortic valve phantom: experimental and computational study using lattice Boltzmann method

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Galabov

Pauš

et al. 2020

Magn Reson Mater Phy

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“…While separating the response of systemic and pulmonary vascular resistance is not essential in estimating the contractile reserve, the role of the pulmonary vasculature and its reactivity to pulmonary vasodilation are of vital importance in investigating Fontan failure and optimizing patient management. The presented work is already introducing some key components to address these important clinical questions and further investigation of the vascular behavior, including separation of the systemic and pulmonary circulations, is a part of our ongoing work [44].…”

Section: Reaction Of Vascular Resistance To Dobutaminementioning

confidence: 99%

Dobutamine stress testing in patients with Fontan circulation augmented by biomechanical modeling

et al. 2020

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Understanding (patho)physiological phenomena and mechanisms of failure in patients with Fontan circulation-a surgically established circulation for patients born with a functionally single ventricle-remains challenging due to the complex hemodynamics and high interpatient variations in anatomy and function. In this work, we present a biomechanical model of the heart and circulation to augment the diagnostic evaluation of Fontan patients with early-stage heart failure. The proposed framework employs a reduced-order model of heart coupled with a simplified circulation including venous return, creating a closed-loop system. We deploy this framework to augment the information from data obtained during combined cardiac catheterization and magnetic resonance exams (XMR), performed at rest and during dobutamine stress in 9 children with Fontan circulation and 2 biventricular controls. We demonstrate that our modeling framework enables patient-specific investigation of myocardial stiffness, contractility at rest, contractile reserve during stress and changes in vascular resistance. Hereby, the model allows to identify key factors underlying the pathophysiological response to stress in these patients. In addition, the rapid personalization of the model to patient data and fast simulation of cardiac cycles make our framework directly applicable in a clinical workflow. We conclude that the proposed modeling framework is a valuable addition to the current clinical diagnostic XMR exam that helps to explain patient-specific stress hemodynamics and can identify potential mechanisms of failure in patients with Fontan circulation.

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Model-Based Indices of Early-Stage Cardiovascular Failure and Its Therapeutic Management in Fontan Patients

Cited by 5 publications

References 10 publications

Monitoring of cardiovascular physiology augmented by a patient-specific biomechanical model during general anesthesia. A proof of concept study

Monitoring of cardiovascular physiology augmented by a patient-specific biomechanical model during general anesthesia. A proof of concept study

Investigation of phase-contrast magnetic resonance imaging underestimation of turbulent flow through the aortic valve phantom: experimental and computational study using lattice Boltzmann method

Dobutamine stress testing in patients with Fontan circulation augmented by biomechanical modeling

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