Inverse problem and multi-compartment lung model for the estimation of lung airway resistance throughout the bronchial tree, An

Includes bibliographical references.2022 Fall.Mechanical ventilation is a vital treatment for patients with respiratory failure, but mechanically ventilated patients are also at risk of ventilator-induced lung injury. Optimal ventilator settings to prevent such injury could be guided by knowledge of the airway resistance throughout the lung. While the ventilator provides a single value estimating the total airway resistance of the patient, in reality the airway resistance varies along the bronchial tree. Multiple literature sources reveal a wide range of clinically used values for airway resistance along the bronchial tree, motivating an investigation to estimate the values of airway resistance in the alveolar tree and the relationship to disease state. In this work, we introduce a multi-compartment asymmetric lung model based on resistor-capacitor circuits by using an analogy between electric circuits and the human lungs. A method for solving the inverse problem of computing the vector of airway resistance values in the alveolar tree is presented. The method uses a linear least squares optimization approach with several constraints. First, a symmetric lung model that makes use of parameters supplied by the mechanical ventilator of patients with acute respiratory distress syndrome (ARDS) is used. We then generalize the model to an asymmetric lung model. The asymmetric model takes regional information data from electrical impedance tomography, a medical imaging technique, and converts them to time dependent lung airway volumes. The linear least squares optimization inverse problem is embedded in an iterative method to update unknown parameters of the forward problem for the asymmetric case

Modelling and Optimisation of Mechanical Ventilation for Critically Ill Patients

This thesis is made up of three parts: i) the development of a comprehensive computational model of the pulmonary (patho)physiology of healthy and diseased lungs, ii) the application of a novel optimisation-based approach to validate this computational model, and iii) the use of this model to optimise mechanical ventilator settings for patients with diseased lungs. The model described in this thesis is an extended implementation of the Nottingham Physiological Simulator (NPS) in MATLAB. An iterative multi-compartmental modelling approach is adopted, and modifications (based on physiological mechanisms) are proposed to characterise healthy as well as diseased states. In the second part of the thesis, an optimisation-based approach is employed to validate the robustness of this model. The model is subjected to simultaneous variations in the values of multiple physiologically relevant uncertain parameters with respect to a set of specified performance criteria, based on expected levels of variation in arterial blood gas values found in the patient population. Performance criteria are evaluated using computer simulations. Local and global optimisation algorithms are employed to search for the worst-case parameter combination that could cause the model outputs to deviate from their expected range of operation, i.e. violate the specified model performance criteria. The optimisation-based analysis is proposed as a useful complement to current statistical model validation techniques, which are reliant on matching data from in vitro and in vivo studies. The last section of the thesis considers the problem of optimising settings of mechanical ventilation in an Intensive Therapy Unit (ITU) for patients with diseased lungs. This is a challenging task for physicians who have to select appropriate mechanical ventilator settings to satisfy multiple, sometimes conflicting, objectives including i) maintaining adequate oxygenation, ii) maintaining adequate carbon dioxide clearance and iii) minimising the risks of ventilator associated lung injury (VALI). Currently, physicians are reliant on guidelines based on previous experience and recommendations from a very limited number of in vivo studies which, by their very nature, cannot form the basis of personalised, disease-specific treatment protocols. This thesis formulates the choice of ventilator settings as a constrained multi-objective optimisation problem, which is solved using a hybrid optimisation algorithm and a validated physiological simulation model, to optimise the settings of mechanical ventilation for a healthy lung and for several pulmonary disease cases. The optimal settings are shown to satisfy the conflicting clinical objectives, to improve the ventilation perfusion matching within the lung, and, crucially, to be disease-specific.College of Engineering, Mathematics and Physical Sciences, University of Exete

Spacecraft Fire Safety 1956 to 1999: An Annotated Bibliography

Knowledge of fire safety in spacecraft has resulted from over 50 years of investigation and experience in space flight. Current practices and procedures for the operation of the Space Transportation System (STS) shuttle and the International Space Station (ISS) have been developed from this expertise, much of which has been documented in various reports. Extending manned space exploration from low Earth orbit to lunar or Martian habitats and beyond will require continued research in microgravity combustion and fire protection in low gravity. This descriptive bibliography has been produced to document and summarize significant work in the area of spacecraft fire safety that was published between 1956 and July 1999. Although some important work published in the late 1990s may be missing, these citations as well as work since 2000 can generally be found in Web-based resources that are easily accessed and searched. In addition to the citation, each reference includes a short description of the contents and conclusions of the article. The bibliography contains over 800 citations that are cross-referenced both by topic and the authors and editors. There is a DVD that accompanies this bibliography (available by request from the Center for Aerospace Information) containing the full-text articles of selected citations as well as an electronic version of this report that has these citations as active links to their corresponding full-text article