Development of a cohort of patient-specific models of lung mechanical ventilation and gas exchange
Author: Win, Zay Yar
Link to this item using this URL: http://hdl.handle.net/2292/52485
Oxygen is essential for every living cell, tissue and organ, and the lung is the only organ that can provide oxygen to the human body. The lung is composed of approximately 8 million airways and approximately 300-500 million air sacs (alveoli) with a surface area of 11,800 cm² at the level of the alveoli. Dealing with the complexity of the lung is challenging, especially for clinicians, when there is a problem (or a disease) in the lungs. It becomes even more complicated when a patient cannot breathe by themselves and requires assisted ventilation (mechanical ventilation, MV). MV is usually given to patients who cannot maintain adequate oxygenation. The main goal of MV is to drive air into the lungs to achieve adequate gas transfer between the air and the blood. Although MV is the most frequently used therapy in the intensive care unit, it itself can also cause injury to the lungs throughout the course of its operation. One of the main reasons is because of the complex physical structure of the lungs meaning that the machine has no control over the direction and the distribution of air inside the lungs. Therefore, treating the lungs is like dealing with a black box. Currently, no technology can provide a detailed information on the response of individual structures. Therefore, clinicians have to rely on their experience or the information available at the bedside (pressure, flow, and oxygen saturation) to optimise or adjust the machine settings to improve tissue oxygenation and to prevent injury to the lungs. Computational models of the lungs have the potential to aid clinicians in optimising MV strategies. This thesis aims to adapt existing ventilation and gas transfer models previously applied in normally breathing lungs to represent mechanically ventilated lungs with different underlying pathologies and to evaluate the appropriateness of the model. First, a structure-based ventilation model is parameterised such that the positive pressure recorded from MV can be used to drive the air into the lungs. In the ventilation model, patient-specific parameters and pathology-specific parameters (for example different pathological conditions, recruitment and de-recruitment) are initialised to represent the patho-physiological condition of the ventilated lungs. The primary function of the lungs is to provide adequate oxygenation (gas transfer) to the body. Therefore, the ventilation model and the gas transfer model are both used to study the effect of patho-physiological mechanics of the lungs on gas transfer. In the MV patients, pathological shunts were created in some regions of the lungs that were assumed to not transfer gases (despite being perfused) due to the damage caused by the pathology and the MV itself. Therefore, pathological shunt was added to the gas transfer model. At the bedside, the final goal of MV is to improve gas transfer and to prevent lung injury at the same time. Therefore, the ventilation and gas transfer models were used to determine whether the model could provide the information required to achieve both improved gas transfer and reduced lung injury without requiring invasive procedures. Since the lungs are enclosed within the chest wall, it is also important to couple the mechanics of the chest wall to the model. Moreover, the endo-tracheal tube is universally used in invasive MV procedures. Therefore, the mechanics of endo-tracheal tube, which serves a connection between the patient and the machine, also needs to be considered in MV patients to reasonably represent the mechanics of MV lungs. Therefore, the contribution of the mechanics of the chest wall and the endo-tracheal tube on the ventilation model are evaluated. The models proposed here show that clinically plausible differences in the regional mechanics of pathological conditions (different pathological conditions and recruitment/ derecruitment) are not apparent from the pressure and flow at the bedside. In addition, the mechanics of endo-tracheal tube is also important in determining the risk of lung injury in MV patients. In addition to parameterising the model to the regional mechanics of the pathological conditions, it is also important for a model to be able to relate the effect of the former on the gas transfer function. The model shows that correlating the regional mechanics to the gas transfer could provide important information to determine the optimal MV setting to both improve gas transfer and also not increase the risk of lung injury at the bedside. In this thesis, a model of patient cohort that simulates MV and gas transfer for the ventilated lungs with no injury and with three pathologies was established. Therefore, the model could be used to test the design of optimal treatment strategies when imaging is not available to confirm suspected injury to the lungs.