Model-based computation of total stressed blood volume from a preload reduction manoeuvre

peer reviewedTotal stressed blood volume is an important parameter for both doctors and engineers. From a medical point of view, it has been associated with the success or failure of fluid therapy, a primary treatment to manage acute circulatory failure. From an engineering point of view, it dictates the cardiovascular system’s behavior in changing physiological situations. Current methods to determine this parameter involve repeated phases of circulatory arrests followed by fluid administration. In this work, a more straightforward method is developed using data from a preload reduction manoeuvre. A simple six-chamber cardiovascular system model is used and its parameters are adjusted to pig experimental data. The parameter adjustment process has three steps: (1) compute nominal values for all model parameters; (2) determine the five most sensitive parameters; and (3) adjust only these five parameters. Stressed blood volume was selected by the algorithm, which emphasizes the importance of this parameter. The model was able to track experimental trends with a maximal root mean squared error of 29.2%. Computed stressed blood volume equals 486 ± 117 ml or 15.7 ± 3.6 ml/kg, which matches previous independent experiments on pigs, dogs and humans. The method proposed in this work thus provides a simple way to compute total stressed blood volume from usual hemodynamic data

Parameter Identification Methods in a Model of the Cardiovascular System

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

Improved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement.

peer reviewedBACKGROUND: Pressure contour analysis is commonly used to estimate cardiac performance for patients suffering from cardiovascular dysfunction in the intensive care unit. However, the existing techniques for continuous estimation of stroke volume (SV) from pressure measurement can be unreliable during hemodynamic instability, which is inevitable for patients requiring significant treatment. For this reason, pressure contour methods must be improved to capture changes in vascular properties and thus provide accurate conversion from pressure to flow. METHODS: This paper presents a novel pressure contour method utilizing pulse wave velocity (PWV) measurement to capture vascular properties. A three-element Windkessel model combined with the reservoir-wave concept are used to decompose the pressure contour into components related to storage and flow. The model parameters are identified beat-to-beat from the water-hammer equation using measured PWV, wave component of the pressure, and an estimate of subject-specific aortic dimension. SV is then calculated by converting pressure to flow using identified model parameters. The accuracy of this novel method is investigated using data from porcine experiments (N = 4 Pietrain pigs, 20-24.5 kg), where hemodynamic properties were significantly altered using dobutamine, fluid administration, and mechanical ventilation. In the experiment, left ventricular volume was measured using admittance catheter, and aortic pressure waveforms were measured at two locations, the aortic arch and abdominal aorta. RESULTS: Bland-Altman analysis comparing gold-standard SV measured by the admittance catheter and estimated SV from the novel method showed average limits of agreement of +/-26% across significant hemodynamic alterations. This result shows the method is capable of estimating clinically acceptable absolute SV values according to Critchely and Critchely. CONCLUSION: The novel pressure contour method presented can accurately estimate and track SV even when hemodynamic properties are significantly altered. Integrating PWV measurements into pressure contour analysis improves identification of beat-to-beat changes in Windkessel model parameters, and thus, provides accurate estimate of blood flow from measured pressure contour. The method has great potential for overcoming weaknesses associated with current pressure contour methods for estimating SV

Development and Identification of a Closed-Loop Model of the Cardiovascular System Including the Atria

peer reviewe

Minimally invasive, patient specific, beat-by-beat estimation of left ventricular time varying elastance.

peer reviewedBACKGROUND: The aim of this paper was to establish a minimally invasive method for deriving the left ventricular time varying elastance (TVE) curve beat-by-beat, the monitoring of which's inter-beat evolution could add significant new data and insight to improve diagnosis and treatment. The method developed uses the clinically available inputs of aortic pressure, heart rate and baseline end-systolic volume (via echocardiography) to determine the outputs of left ventricular pressure, volume and dead space volume, and thus the TVE curve. This approach avoids directly assuming the shape of the TVE curve, allowing more effective capture of intra- and inter-patient variability. RESULTS: The resulting TVE curve was experimentally validated against the TVE curve as derived from experimentally measured left ventricular pressure and volume in animal models, a data set encompassing 46,318 heartbeats across 5 Pietrain pigs. This simulated TVE curve was able to effectively approximate the measured TVE curve, with an overall median absolute error of 11.4% and overall median signed error of -2.5%. CONCLUSIONS: The use of clinically available inputs means there is potential for real-time implementation of the method at the patient bedside. Thus the method could be used to provide additional, patient specific information on intra- and inter-beat variation in heart function

Méthodes d'identification des paramètres dans un modèle du système cardiovasculaire

Les dysfonctions du système cardiovasculaire sont une origine majeure des admissions dans les unités de soins intensifs. Dans ces unités, les patients sont très instables et les cliniciens disposent d’un nombre limité de mesures pour prendre rapidement les bonnes décisions. L’utilisation de modèles patient-spécifiques pour guider les clini- ciens offre alors des perspectives réelles. Un modèle simple à six compartiments du système cardiovasculaire a été développé par Smith et al. et une méthode d’identification des paramètres de ce modèle a été développée par Revie et al. Ce modèle a été étendu en y ajoutant deux compartiments représentant les oreillettes, dont le comportement est décrit par un modèle inspiré de travaux existants. Une méthode d’identification similaire à celle utilisée par Revie et al. a été développée pour les nouveaux paramètres. Pour ne pas devoir recourir à la pression auriculaire, difficile à mesurer expérimentalement, une méthode permettant de déduire la pression auriculaire à partir de la pression ventriculaire a également été introduite. L’application du modèle étendu et de la méthode d’identification correspondante à des données expérimentales montre que l’introduction des oreillettes dans le modèle ne cause pas de trop grandes erreurs et que la méthode d’estimation de la pression auriculaire est correcte. En conclusion, la valeur ajoutée de la méthode développée dans ce travail est grande, puisqu’elle permet d’obtenir des informations supplémentaires sans introduire de grandes erreurs et sans imposer le besoin de recourir à de nouvelles mesures

Calculez l'âge de vos artères

Poster présenté lors de la Nuit des Chercheurs, édition 2013. L'activité consistait à calculer la résistance et la compliance (élasticité) des artères des visiteurs, sur base des mesures suivantes : taille, poids, pression artérielle et fréquence cardiaque

Model-Based Prediction of the Response to Vascular Filling Therapy

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.Le remplissage vasculaire est l’une des interventions les plus fréquentes dans les unités de soins intensifs, l’effet attendu étant une augmentation du débit car- diaque. Cependant, cette réponse est observée dans seulement environ 50 % des cas. De plus, un remplissage vasculaire trop important peut mener à des effets délétères, comme l’œdème pulmonaire, qui augmentent la durée de la respiration mécanique, de l’hospitalisation, la mortalité et les coûts. Les médecins sont donc à la recherche d’indices fournissant a priori une information sur les effets du rem- plissage vasculaire. Cette thèse présente une méthode de prédiction de la réponse au remplissage vasculaire basée sur un modèle mathématique. Un modèle math- ématique est un ensemble d’équations représentant le comportement d’un sys- tème donné, par exemple le système cardio-vasculaire. Des éléments de base d’anatomie et de physiologie cardio-vasculaire sont présentés dans la première partie de cette thèse, car ils sont nécessaires à la com- préhension des principes du remplissage vasculaire. Ensuite, des détails supplé- mentaires sont fournis sur la thérapie de remplissage vasculaire, ainsi que sur les indices actuellement utilisés par les médecins pour en prédire les effets. Les indices dits statiques sont faciles à obtenir, mais peu efficaces. Les indices dits dy- namiques, basés sur les interactions cardio-pulmonaires, sont plus performants, mais sont invasifs et difficiles à implémenter en clinique. Un nouvel indice, le volume total de sang sous pression, pourrait s’avérer utile, mais est également difficile à obtenir en clinique. Ce travail développe et utilise des modèles du sys- tème cardio-vasculaire pour rendre ce paramètre disponible aux médecins. Sur base des éléments de physiologie développés dans la première partie, la seconde partie de cette thèse décrit comment modéliser les composants actifs et passifs du système cardio-vasculaire sous forme d’éléments agrégés, comme des compartiments, des valves et des résistances. Deux modèles du système cardio- vasculaire, comptant respectivement trois et six compartiments, sont ensuite con- struits à partir de tels éléments. Ces deux modèles impliquent un petit nombre de paramètres, représentant notamment le volume total sous pression dans le modèle. La troisième partie de cette thèse explique comment identifier les paramètres des deux modèles du système cardio-vasculaire. L’identification des paramètres a pour but de trouver les valeurs des paramètres qui rendent les simulations du modèle aussi proches que possible des données mesurées. Les données dispo- nibles sont donc décrites en premier lieu, en fonction de l’endroit où elles sont mesurées : dans un laboratoire expérimental ou une unité de soins intensifs. En- suite, il est mathématiquement démontré que tous les paramètres du modèle peu- vent théoriquement être identifiés à partir de données disponibles dans une unité de soins intensifs. Cependant, d’un point de vue pratique, certains paramètres ne peuvent être identifiés, car ils ont peu d’influence sur les simulations, ou ont le même effet que d’autres paramètres. En dernier lieu, des méthodes numériques pour identifier les paramètres à partir d’un ensemble de données cliniques sont présentées et comparées. La dernière partie de cette thèse présente deux applications des modèles du système cardio-vasculaire à des données expérimentales. Premièrement, tous les paramètres du modèle du système cardio-vasculaire à six compartiments sont identifiés à partir de données provenant d’une expérience de réduction de pré- charge. Ce résultat constitue la première validation quantitative du modèle à six compartiments en situation transitoire. Deuxièmement, tous les paramètres du modèle à trois compartiments, y compris le volume total sous pression, sont identifiés à partir de données provenant d’expériences de remplissage vasculaire. Les résultats montrent que le volume total sous pression est systématiquement lié au changement de débit cardiaque après remplissage. Ce dernier indice fournit donc, pour la première fois, une méthode basée sur un modèle pour prédire la réponse au remplissage vasculaire

The influence of the student employment contract reform on the labor market actors

Background: The reform of the law on the student employment contract became effective January 1st 2012. This reform widely affects the way student employment takes place in Belgium. In this study, I evaluate the influence of this change on the behavior of the labor market actors at different points: (1) their knowledge of the law, (2) their interest for student employment, (3) the periods during which students work, (4) the competition between students and job seekers and (5) moonlighting. Methods: I carried out a qualitative study on 42 labor market actors belonging to the following categories: students, employers, representatives of temporary work agencies and union representatives. I interviewed these persons with a questionnaire based on the five points mentioned above. I analyzed the gathered data using techniques suited for qualitative data. Results: It first appears that the law is well known by the labor market actors. Second, the reform caused an increased interest for students employment through a cost decrease and an increase in flexibility, both on the employers’ and the students’ sides. Third, there seems to exist a link between school underperformance and a student’s amount of working days. Fourth, I observe that there exists an actual competition between students and job seekers, in particular because student employment bears a strategic aspect. Finally, I observe that 7 out of 10 students already moonlighted. The more the students like to work and the older they are, the more likely they moonlight. Conclusion: This work allowed me to answer some questions that remained open and to provide a first qualitative evaluation of the new system. The first problem of this system is that it could elicit school underperformance by allowing students to work during terms. Next, this system does not discourage some employers to resort to moonlighting because they still need more flexibility from the students. These two thoughts will have to be part of the debate when the authorities will assess the system