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See detailModel-Based Prediction of the Response to Vascular Filling Therapy
Pironet, Antoine ULg

Doctoral thesis (2016)

Vascular filling is one of the most frequent interventions in intensive care units. Its expected effect is to increase cardiac output. However, this increase is only observed in approximately 50 % of ... [more ▼]

Vascular filling is one of the most frequent interventions in intensive care units. Its expected effect is to increase cardiac output. However, this increase is only observed in approximately 50 % of cases. In addition, excessive vascular filling can lead to deleterious effects, such as pulmonary oedema, which increase length of ventilation, stay, mortality and cost. Clinicians are thus looking for indices to provide a priori knowledge of the effect of vascular filling. This thesis focuses on a mathematical model-based approach to predict the response to vascular filling. Mathematical models are sets of equations representing the behaviour of a given system as, for instance, the cardiovascular system. To understand the concept of vascular filling, basic elements of cardio-vascular anatomy and physiology are presented in the first part of this thesis. Then, fur- ther details about vascular filling therapy are given, as well as the current indices used by clinicians to predict its effects. The static indices are easy to obtain, but do not perform well. The dynamic indices, based on cardio-pulmonary interac- tions, perform better, but are difficult and highly invasive to implement clinically. A new index, total stressed blood volume, also seems to perform well, but is not easy to obtain clinically. This work develops and then uses models of the cardio- vascular system to make this parameter available to clinicians. Building on the elements of physiology provided in the first part, the second part of this thesis describes ways to model the components of the cardio-vascular system as lumped elements, such as chambers, valves and resistances. Two mod- els of the cardio-vascular system, comprising respectively three and six cham- bers, are built from such elements. These two models involve a small number of parameters, including the total stressed volume in the model. The third part of this thesis describes the potential and methods to identify the parameters of the two cardio-vascular system models. Parameter identifica- tion aims at finding the parameter values that make model simulations as close as possible to measured data. The available data is thus first described, accord- ing to whether it is collected in an experimental laboratory or an intensive care unit. Then, it is mathematically demonstrated that all model parameters can the- oretically be identified from data available in an intensive care unit. However, practically speaking, some parameters are difficult to identify, because they have little influence on the simulations, or have the same effect as other parameters. Fi- nally, computational methods to perform parameter identification are presented and compared. The last part of this thesis presents two applications of the cardio-vascular system models to experimental data. First, all parameters of the six-chamber cardio-vascular system model are identified from data recorded during a preload reduction experiment. This result provides the first quantitative validation of the six-chamber model in transient conditions. Second, all parameters of the three-chamber cardio-vascular system model, including total stressed volume, are identified from data recorded during vascular filling experiments. The total stressed volume parameter is shown to be systematically related to the change in cardiac output after vascular filling. This last index thus provides, for the first time, a model-based means of predicting the response to vascular filling. [less ▲]

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See detailCardio-pulmonary mechanics and minimal modelling in critical care
de Bournonville, Sébastien; Pironet, Antoine ULg; Desaive, Thomas ULg et al

Poster (2016, March 04)

Detailed reference viewed: 9 (1 ULg)
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See detailCardio-pulmonary mechanics and minimal modelling in critical care
de Bournonville, Sébastien; Pironet, Antoine ULg; Desaive, Thomas ULg et al

in 14th Belgian Day on Biomedical Engineering (2016, March 04)

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See detailParameter Correlation Analysis in Four Mathematical Models of Left Ventricular Relaxation
Pironet, Antoine ULg; MORIMONT, Philippe ULg; Dauby, Pierre ULg et al

in 14th Belgian Day on Biomedical Engineering (2016, March 04)

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See detailStructural identifiability analysis of a cardiovascular system model
Pironet, Antoine ULg; Dauby, Pierre ULg; Chase, J. Geoffrey et al

in Medical engineering & physics (2016)

The six-chamber cardiovascular system model of Burkhoff and Tyberg has been used in several theoretical and experimental studies. However, this cardiovascular system model (and others derived from it) are ... [more ▼]

The six-chamber cardiovascular system model of Burkhoff and Tyberg has been used in several theoretical and experimental studies. However, this cardiovascular system model (and others derived from it) are not identifiable from any output set. In this work, two such cases of structural non-identifiability are first presented. These cases occur when the model output set only contains a single type of information (pressure or volume). A specific output set is thus chosen, mixing pressure and volume information and containing only a limited number of clinically available measurements. Then, by manipulating the model equations involving these outputs, it is demonstrated that the six-chamber cardiovascular system model is structurally globally identifiable. A further simplification is made, assuming known cardiac valve resistances. Because of the poor practical identifiability of these four parameters, this assumption is usual. Under this hypothesis, the six-chamber cardiovascular system model is structurally identifiable from an even smaller dataset. As a consequence, parameter values computed from limited but well-chosen datasets are theoretically unique. This means that the parameter identification procedure can safely be performed on the model from such a well-chosen dataset. Thus, the model may be considered suitable for use in diagnosis. [less ▲]

Detailed reference viewed: 26 (5 ULg)
See detailCardio-pulmonary mechanics and minimal modelling in critical care
de Bournonville, Sébastien; Pironet, Antoine ULg; Desaive, Thomas ULg et al

Poster (2015, November 26)

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See detailCardio-pulmonary mechanics and minimal modelling in critical care
de Bournonville, Sébastien; Pironet, Antoine ULg; Desaive, Thomas ULg et al

in Proceedings of the IEEE-EMBS Benelux chapter 2015 meeting (2015, November 26)

Detailed reference viewed: 13 (3 ULg)
Peer Reviewed
See detailParameter Correlation Analysis in Four Mathematical Models of Left Ventricular Relaxation
Pironet, Antoine ULg; MORIMONT, Philippe ULg; Dauby, Pierre ULg et al

in Proceedings of the IEEE-EMBS Benelux chapter 2015 meeting (2015, November 26)

Detailed reference viewed: 13 (5 ULg)
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See detailParameter Identification Methods in a Model of the Cardiovascular System
Pironet, Antoine ULg; Desaive, Thomas ULg; Dauby, Pierre ULg et al

Poster (2015, September 01)

To be clinically relevant, mathematical models have to be patient-specific, meaning that their parameters have to be identified from patient data. To achieve real time monitoring, it is important to ... [more ▼]

To be clinically relevant, mathematical models have to be patient-specific, meaning that their parameters have to be identified from patient data. To achieve real time monitoring, it is important to select the best parameter identification method, in terms of speed, efficiency and reliability. This work presents a comparison of seven parameter identification methods applied to a lumped-parameter cardiovascular system model. The seven methods are tested using in silico and experimental reference data. To do so, precise formulae for initial parameter values first had to be developed. The test results indicate that the trust-region reflective method seems to be the best method for the present model. This method (and the proportional method) are able to perform parameter identification in two to three minutes, and will thus benefit cardiac and vascular monitoring applications. [less ▲]

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See detailModel-Based Stressed Blood Volume is an Index of Fluid Responsiveness
Pironet, Antoine ULg; Dauby, Pierre ULg; Chase, J. Geoffrey et al

Conference (2015, September 01)

Fluid therapy is frequently used to manage acute circulatory failure. This therapy aims to restore cardiac output by fluid administration, which increases the quantity of fluid in the circulation. However ... [more ▼]

Fluid therapy is frequently used to manage acute circulatory failure. This therapy aims to restore cardiac output by fluid administration, which increases the quantity of fluid in the circulation. However, it has been shown to be effective only in certain cases, leading to the need for indices of fluid responsiveness. Total stressed blood volume has recently been shown to be such an index of fluid responsiveness. However, the current methods to determine this parameter require specific procedures. In this work, a more straightforward method is developed using data available in the intensive care unit. A simple three-chamber cardiovascular system model is used, of which total stressed blood volume is a parameter. All model parameters (including total stressed blood volume) are adjusted to pig experimental data during fluid administrations. The resulting value of total stressed blood volume is always negatively associated with the relative change in cardiac output after fluid administration. This finding confirms that total stressed blood volume is an index of fluid responsiveness. Another finding of this study is that the response curves are subject-specific. The method developed in this work can be applied to humans, since the data required is typically available in an intensive care unit. [less ▲]

Detailed reference viewed: 22 (1 ULg)
See detailRelationship between Stroke Volume and Pulse Wave Velocity
Kamoi, Shun; Pretty, Christopher; Chiew, Yeong Shiong et al

Conference (2015, September 01)

Stroke Volume (SV) measurements are essential for evaluating patient hemodynamic status and response to therapy. However, current methods for monitoring SV require either invasive or non- invasive ... [more ▼]

Stroke Volume (SV) measurements are essential for evaluating patient hemodynamic status and response to therapy. However, current methods for monitoring SV require either invasive or non- invasive additional measurements. This study investigates the relationship between SV and Pulse Wave Velocity (PWV) to examine whether the value of PWV can capture the changes in SV. The analysis was performed using data from six porcine experiments (N=6 Pietrain Pigs, 20-29 kg) in which left ventricular volume, aortic arc pressure, and descending aortic pressure waveforms were measured simultaneously. From the measured data, correlation coefficients were determined between absolute value of aortic PWV, SV and trend value ‘PWV – mean PWV’, ‘SV – mean SV’ during periods when changes in SV were induced from preload changes, as well as infusion of dobutamine. The results showed good correlation (r = 0.59) for trend value, however, the correlation coefficient were poor with r = 0.028 for absolute value across all pigs. The analysis showed that value of PWV is reliable for capturing trend value of SV in preload changes. However, it is unreliable for capturing absolute value of SV or changes in SV made from dobutamine. [less ▲]

Detailed reference viewed: 59 (0 ULg)
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Peer Reviewed
See detailParameter Identification Methods in a Model of the Cardiovascular System
Pironet, Antoine ULg; Desaive, Thomas ULg; Dauby, Pierre ULg et al

in IFAC PapersOnLine (2015, September)

To be clinically relevant, mathematical models have to be patient-specific, meaning that their parameters have to be identified from patient data. To achieve real time monitoring, it is important to ... [more ▼]

To be clinically relevant, mathematical models have to be patient-specific, meaning that their parameters have to be identified from patient data. To achieve real time monitoring, it is important to select the best parameter identification method, in terms of speed, efficiency and reliability. This work presents a comparison of seven parameter identification methods applied to a lumped-parameter cardiovascular system model. The seven methods are tested using in silico and experimental reference data. To do so, precise formulae for initial parameter values first had to be developed. The test results indicate that the trust-region reflective method seems to be the best method for the present model. This method (and the proportional method) are able to perform parameter identification in two to three minutes, and will thus benefit cardiac and vascular monitoring applications. [less ▲]

Detailed reference viewed: 60 (5 ULg)
Full Text
Peer Reviewed
See detailModel-Based Stressed Blood Volume is an Index of Fluid Responsiveness
Pironet, Antoine ULg; Dauby, Pierre ULg; Chase, J. Geoffrey et al

in IFAC PapersOnLine (2015, September)

Fluid therapy is frequently used to manage acute circulatory failure. This therapy aims to restore cardiac output by fluid administration, which increases the quantity of fluid in the circulation. However ... [more ▼]

Fluid therapy is frequently used to manage acute circulatory failure. This therapy aims to restore cardiac output by fluid administration, which increases the quantity of fluid in the circulation. However, it has been shown to be effective only in certain cases, leading to the need for indices of fluid responsiveness. Total stressed blood volume has recently been shown to be such an index of fluid responsiveness. However, the current methods to determine this parameter require specific procedures. In this work, a more straightforward method is developed using data available in the intensive care unit. A simple three-chamber cardiovascular system model is used, of which total stressed blood volume is a parameter. All model parameters (including total stressed blood volume) are adjusted to pig experimental data during fluid administrations. The resulting value of total stressed blood volume is always negatively associated with the relative change in cardiac output after fluid administration. This finding confirms that total stressed blood volume is an index of fluid responsiveness. Another finding of this study is that the response curves are subject-specific. The method developed in this work can be applied to humans, since the data required is typically available in an intensive care unit. [less ▲]

Detailed reference viewed: 25 (2 ULg)
Peer Reviewed
See detailRelationship between Stroke Volume and Pulse Wave Velocity
Kamoi, Shun; Pretty, Christopher; Chiew, Yeong Shiong et al

in Preprints of the 9th IFAC Symposium on Biological and Medical Systems (2015, September)

Stroke Volume (SV) measurements are essential for evaluating patient hemodynamic status and response to therapy. However, current methods for monitoring SV require either invasive or non- invasive ... [more ▼]

Stroke Volume (SV) measurements are essential for evaluating patient hemodynamic status and response to therapy. However, current methods for monitoring SV require either invasive or non- invasive additional measurements. This study investigates the relationship between SV and Pulse Wave Velocity (PWV) to examine whether the value of PWV can capture the changes in SV. The analysis was performed using data from six porcine experiments (N=6 Pietrain Pigs, 20-29 kg) in which left ventricular volume, aortic arc pressure, and descending aortic pressure waveforms were measured simultaneously. From the measured data, correlation coefficients were determined between absolute value of aortic PWV, SV and trend value ‘PWV – mean PWV’, ‘SV – mean SV’ during periods when changes in SV were induced from preload changes, as well as infusion of dobutamine. The results showed good correlation (r = 0.59) for trend value, however, the correlation coefficient were poor with r = 0.028 for absolute value across all pigs. The analysis showed that value of PWV is reliable for capturing trend value of SV in preload changes. However, it is unreliable for capturing absolute value of SV or changes in SV made from dobutamine. [less ▲]

Detailed reference viewed: 43 (1 ULg)
Peer Reviewed
See detailStroke Volume Estimation using Aortic Pressure Measurements and Aortic Cross Sectional Area: Proof of Concept
Kamoi, Shun; Pretty, Christopher G.; Chiew, Yeong Shiong et al

in Proceedings of the 37th International Conference of the IEEE Engineering in Medicine and Biology Society (2015, August)

Accurate Stroke Volume (SV) monitoring is essential for patient with cardiovascular dysfunction patients. However, direct SV measurements are not clinically feasible due to the highly invasive nature of ... [more ▼]

Accurate Stroke Volume (SV) monitoring is essential for patient with cardiovascular dysfunction patients. However, direct SV measurements are not clinically feasible due to the highly invasive nature of measurement devices. Current devices for indirect monitoring of SV are shown to be inaccurate during sudden hemodynamic changes. This paper presents a novel SV estimation using readily available aortic pressure measurements and aortic cross sectional area, using data from a porcine experiment where medical interventions such as fluid replacement, dobutamine infusions, and recruitment maneuvers induced SV changes in a pig with circulatory shock. Measurement of left ventricular volume, proximal aortic pressure, and descending aortic pressure waveforms were made simultaneously during the experiment. From measured data, proximal aortic pressure was separated into reservoir and excess pressures. Beat-to-beat aortic characteristic impedance values were calculated using both aortic pressure measurements and an estimate of the aortic cross sectional area. SV was estimated using the calculated aortic characteristic impedance and excess component of the proximal aorta. The median difference between directly measured SV and estimated SV was -1.4ml with 95% limit of agreement +/- 6.6ml. This method demonstrates that SV can be accurately captured beat-to-beat during sudden changes in hemodynamic state. This novel SV estimation could enable improved cardiac and circulatory treatment in the critical care environment by titrating treatment to the effect on SV. [less ▲]

Detailed reference viewed: 56 (5 ULg)
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See detailModelling of the Nonlinear End-Systolic Pressure-Volume Relation and Volume-at-Zero-Pressure in Porcine Experiments
Davidson, Shaun M.; Kannangara, D. Oliver; Pretty, Christopher G. et al

in Proceedings of the 37th International Conference of the IEEE Engineering in Medicine and Biology Society (2015, August)

The End-Systolic Pressure-Volume Relation (ESPVR) is generally modelled as a linear relationship between P and V as cardiac reflexes, such as the baroreflex, are typically suppressed in experiments ... [more ▼]

The End-Systolic Pressure-Volume Relation (ESPVR) is generally modelled as a linear relationship between P and V as cardiac reflexes, such as the baroreflex, are typically suppressed in experiments. However, ESPVR has been observed to behave in a curvilinear fashion when cardiac reflexes are not supressed, suggesting the curvilinear function may be more clinically appropriate. Data was gathered from 41 vena cava occlusion manoeuvres performed experimentally at a variety of PEEPs across 6 porcine specimens, and ESPVR determined for each pig. An exponential model of ESPVR was found to provide a higher correlation coefficient than a linear model in 6 out of 7 cases, and a lower Akaike Information Criterion (AIC) value in all cases. Further, the exponential ESPVR provided positive V0 values in a physiological range in6 out of 7 cases analysed, while the linear ESPVR produced positive V0 values in only 3 out of 7 cases, suggesting linear extrapolation of ESPVR to determine V0 may be flawed. [less ▲]

Detailed reference viewed: 21 (4 ULg)
Full Text
See detailStroke Volume Estimation using Aortic Pressure Measurements and Aortic Cross Sectional Area
Kamoi, Shun; Pretty, Christopher G.; Chiew, Yeong Shiong et al

Poster (2015, August)

Accurate Stroke Volume (SV) monitoring is essential for patient with cardiovascular dysfunction patients. However, direct SV measurements are not clinically feasible due to the highly invasive nature of ... [more ▼]

Accurate Stroke Volume (SV) monitoring is essential for patient with cardiovascular dysfunction patients. However, direct SV measurements are not clinically feasible due to the highly invasive nature of measurement devices. Current devices for indirect monitoring of SV are shown to be inaccurate during sudden hemodynamic changes. This paper presents a novel SV estimation using readily available aortic pressure measurements and aortic cross sectional area, using data from a porcine experiment where medical interventions such as fluid replacement, dobutamine infusions, and recruitment maneuvers induced SV changes in a pig with circulatory shock. Measurement of left ventricular volume, proximal aortic pressure, and descending aortic pressure waveforms were made simultaneously during the experiment. From measured data, proximal aortic pressure was separated into reservoir and excess pressures. Beat-to-beat aortic characteristic impedance values were calculated using both aortic pressure measurements and an estimate of the aortic cross sectional area. SV was estimated using the calculated aortic characteristic impedance and excess component of the proximal aorta. The median difference between directly measured SV and estimated SV was -1.4ml with 95% limit of agreement +/- 6.6ml. This method demonstrates that SV can be accurately captured beat-to-beat during sudden changes in hemodynamic state. This novel SV estimation could enable improved cardiac and circulatory treatment in the critical care environment by titrating treatment to the effect on SV. [less ▲]

Detailed reference viewed: 54 (3 ULg)