Antonio Albanese

Noninvasive Estimation of Respiratory Mechanics in Spontaneously Breathing Ventilated Patients: A Constrained Optimization Approach

This paper presents a method for breath-by-breath noninvasive estimation of respiratory resistance and elastance in mechanically ventilated patients. For passive patients, well-established approaches exist. However, when patients are breathing spontaneously, taking into account the diaphragmatic effort in the estimation process is still an open challenge. Mechanical ventilators require maneuvers to obtain reliable estimates for respiratory mechanics parameters. Such maneuvers interfere with the desired ventilation pattern to be delivered to the patient. Alternatively, invasive procedures are needed. The method presented in this paper is a noninvasive way requiring only measurements of airway pressure and flow that are routinely available for ventilated patients. It is based on a first-order single-compartment model of the respiratory system, from which a cost function is constructed as the sum of squared errors between model-based airway pressure predictions and actual measurements. Physiological considerations are translated into mathematical constraints that restrict the space of feasible solutions and make the resulting optimization problem strictly convex. Existing quadratic programming techniques are used to efficiently find the minimizing solution, which yields an estimate of the respiratory system resistance and elastance. The method is illustrated via numerical examples and experimental data from animal tests. Results show that taking into account the patient effort consistently improves the estimation of respiratory mechanics. The method is suitable for real-time patient monitoring, providing clinicians with noninvasive measurements that could be used for diagnosis and therapy optimization.

An integrated mathematical model of the human cardiopulmonary system: model development

Several cardiovascular and pulmonary models have been proposed in the last few decades. However, very few have addressed the interactions between these two systems. Our group has developed an integrated cardiopulmonary model (CP Model) that mathematically describes the interactions between the cardiovascular and respiratory systems, along with their main short-term control mechanisms. The model has been compared with human and animal data taken from published literature. Due to the volume of the work, the paper is divided in two parts. The present paper is on model development and normophysiology, whereas the second is on the models validation on hypoxic and hypercapnic conditions. The CP Model incorporates cardiovascular circulation, respiratory mechanics, tissue and alveolar gas exchange, as well as short-term neural control mechanisms acting on both the cardiovascular and the respiratory functions. The model is able to simulate physiological variables typically observed in adult humans under normal and pathological conditions and to explain the underlying mechanisms and dynamics.

Constrained optimization for noninvasive estimation of work of breathing.

This paper presents a technique for noninvasive estimation of respiratory muscle effort (also known as work of breathing, WOB) in mechanically ventilated patients. Continual and real-time assessment of the patient WOB is desirable, as it helps the clinician make decisions about increasing or decreasing mechanical respiratory support. The technique presented is based on a physiological model of the respiratory system, from which a cost function is constructed as the sum of squared errors between model-based airway pressure predictions and actual measurements. Quadratic programming methods are used to minimize this cost function. An experimental example on animal data shows the effectiveness of the technique.

An integrated mathematical model of the human cardiopulmonary system: model validation under hypercapnia and hypoxia

A novel integrated physiological model of the interactions between the cardiovascular and respiratory systems has been in development for the past few years. The model has hundreds of parameters and variables representing the physical and physiological properties of the human cardiopulmonary system. It can simulate many dynamic states and scenarios. The description of the model and the results in normal resting conditions were presented in a companion paper (Albanese A, Cheng L, Ursino M, Chbat NW.Am J Physiol Heart Circ Physiol 310: 2016; doi:10.1152/ajpheart.00230.2014), where model predictions were compared against average population data from literature. However, it is also essential to test the model in abnormal or pathological conditions to prove its consistency. Hence, in this paper, we concentrate on testing the cardiopulmonary model under hypercapnic and hypoxic conditions, by comparing models outputs to population-averaged cardiorespiratory data reported in the literature. The utility of this comprehensive model is demonstrated by testing the internal consistency of the simulated responses of a significant number of cardiovascular variables (heart rate, arterial pressure, and cardiac output) and respiratory variables (tidal volume, respiratory rate, minute ventilation, alveolar O2 and CO2 partial pressures) over a wide range of perturbations and conditions; namely, hypercapnia at 3-7% CO2 levels and hypoxia at 7-9% O2 levels with controlled CO2(isocapnic hypoxia) and without controlled CO2(hypocapnic hypoxia). Finally, a sensitivity analysis is performed to analyze the role of the main cardiorespiratory control mechanisms triggered by hypercapnia and hypoxia.

Patient emulator: A tool for testing mechanical ventilation therapies

Several modes of mechanical ventilation are clinically available. The differences among them in terms of efficacy and patient outcomes are not clear yet. Testing and comparison of mechanical ventilation modes via human or animal trials is a very challenging and costly process. In this paper, we present the patient emulator (PE), a novel system that can be used as a platform for in-silico testing of mechanical ventilation therapies. The system is based on a large-scale integrated mathematical model of the human cardiopulmonary system interfaced with a physical ventilator via a controlled piston-cylinder actuator. The performance of the proposed PE is demonstrated by simulating a realistic pressure support ventilation step protocol. The PE-simulated patients response is then compared against averaged data from 33 human subjects. The agreement between the simulated data and their experimental counterparts shows the potential of the proposed PE to be used as a substitute for or in addition to conventional animal and human trials.

Simultaneous Parameter and Input Estimation of a Respiratory Mechanics Model

Real-time noninvasive estimation of respiratory mechanics in spontaneously breathing patients is still an open problem in the field of critical care. Even assuming that the system is a simplistic first-order single-compartment model, the presence of unmeasured patient effort still makes the problem complex since both the parameters and part of the input are unknown. This paper presents an approach to overcome the underdetermined nature of the mathematical problem by infusing physiological knowledge into the estimation process and using it to construct an optimization problem subject to physiological constraints. As it relies only on measurements available on standard ventilators, namely the flow and pressure at the patient’s airway opening, the approach is noninvasive. Additionally, breath by breath, it continually provides estimates of the patient respiratory resistance and elastance as well as of the muscle effort waveform without requiring maneuvers that would interfere with the desired ventilation pattern.

Effects of septum and pericardium on heart-lung interactions in a cardiopulmonary simulation model

Mechanical heart-lung interactions are often overlooked in clinical settings. However, their impact on cardiac function can be quite significant. Mechanistic physiology-based models can provide invaluable insights into such cardiorespiratory interactions, which occur not only under external mechanical ventilatory support but in normal physiology as well. In this work, we focus on the cardiac component of a previously developed mathematical model of the human cardiopulmonary system, aiming to improve the models response to the intrathoracic pressure variations that are associated with the respiratory cycle. Interventricular septum and pericardial membrane are integrated into the existing model. Their effect on the overall cardiac response is explained by means of comparison against simulation results from the original model as well as experimental data from literature.

Cardiorespiratory adaptation to breath-holding in air: Analysis via a cardiopulmonary simulation model

Apnea via breath-holding (BH) in air induces cardiorespiratory adaptation that involves the activation of several reflex mechanisms and their complex interactions. Hence, the effects of BH in air on cardiorespiratory function can become hardly predictable and difficult to be interpreted. Particularly, the effect on heart rate is not yet completely understood because of the contradicting results of different physiological studies. In this paper we apply our previously developed cardiopulmonary model (CP Model) to a scenario of BH with a twofold intent: (1) further validating the CP Model via comparison against experimental data; (2) gaining insights into the physiological reasoning for such contradicting experimental results. Model predictions agreed with published experimental animal and human data and indicated that heart rate increases during BH in air. Changes in the balance between sympathetic and vagal effects on heart rate within the model proved to be effective in inverting directions of the heart rate changes during BH. Hence, the model suggests that intra-subject differences in such sympatho-vagal balance may be one of the reasons for the contradicting experimental results.