Target-specific multiphysics modeling for thermal medicine applications

Dissertation to obtain the degree of Doctor of Philosophy in Biomedical EngineeringThis thesis addresses thermal medicine applications on murine bladder hyperthermia and brain temperature monitoring. The two main objectives are interconnected by the key physics in thermal medicine: heat transfer. The first goal is to develop an analytical solution to characterize the heat transfer in a multi-layer perfused tissue. This analytical solution accounts for important thermoregulation mechanisms and is essential to understand the fundamentals underlying the physical and biological processes associated with heat transfer in living tissues. The second objective is the development of target-specific models that are too complex to be solved by analytical methods. Thus, the software for image segmentation and model simulation is based on numerical methods and is used to optimize non-invasive microwave antennas for specific targets. Two examples are explored using antennas in the passive mode (probe) and active mode (applicator). The passive antenna consists of a microwave radiometric sensor developed for rapid non-invasive feedback of critically important brain temperature. Its design parameters are optimized using a power-based algorithm. To demonstrate performance of the device, we build a realistic model of the human head with separate temperaturecontrolled brain and scalp regions. The sensor is able to track brain temperature with 0.4 °C accuracy in a 4.5 hour long experiment where brain temperature is varied in a 37 °C, 27 °C and 37 °C cycle. In the second study, a microwave applicator with an integrated cooling system is used to develop a new electro-thermo-fluid (multiphysics) model for murine bladder hyperthermia studies. The therapy procedure uses a temperature-based optimization algorithm to maintain the bladder at a desired therapeutic level while sparing remaining tissues from dangerous temperatures. This model shows that temperature dependent biological properties and the effects of anesthesia must be accounted to capture the absolute and transient temperature fields within murine tissues. The good agreement between simulation and experimental results demonstrates that this multiphysics model can be used to predict internal temperatures during murine hyperthermia studies

An integrative computational model for intestinal tissue renewal

Objectives\ud \ud The luminal surface of the gut is lined with a monolayer of epithelial cells that acts as a nutrient absorptive engine and protective barrier. To maintain its integrity and functionality, the epithelium is renewed every few days. Theoretical models are powerful tools that can be used to test hypotheses concerning the regulation of this renewal process, to investigate how its dysfunction can lead to loss of homeostasis and neoplasia, and to identify potential therapeutic interventions. Here we propose a new multiscale model for crypt dynamics that links phenomena occurring at the subcellular, cellular and tissue levels of organisation.\ud \ud Methods\ud \ud At the subcellular level, deterministic models characterise molecular networks, such as cell-cycle control and Wnt signalling. The output of these models determines the behaviour of each epithelial cell in response to intra-, inter- and extracellular cues. The modular nature of the model enables us to easily modify individual assumptions and analyse their effects on the system as a whole.\ud \ud Results\ud \ud We perform virtual microdissection and labelling-index experiments, evaluate the impact of various model extensions, obtain new insight into clonal expansion in the crypt, and compare our predictions with recent mitochondrial DNA mutation data. \ud \ud Conclusions\ud \ud We demonstrate that relaxing the assumption that stem-cell positions are fixed enables clonal expansion and niche succession to occur. We also predict that the presence of extracellular factors near the base of the crypt alone suffices to explain the observed spatial variation in nuclear beta-catenin levels along the crypt axis

A COMPUTATIONAL STUDY OF PATCH IMPLANTATION AND MITRAL VALVE MECHANICS

Myocardial infarction (i.e., a heart attack) is the most common heart disease in the United States. Mitral valve regurgitation, or the backflow of blood into the atrium from the left ventricle, is one of the complications associated with myocardial infarction. In this dissertation, a validated model of a sheep heart that has suffered myocardial infarction has been employed to study mitral valve regurgitation. The model was rebuilt with the knowledge of geometrical changes captured with MRI technique and is assigned with anisotropic, inhomogeneous, nearly incompressible and highly non-linear material properties. Patch augmentation was performed on its anterior leaflet, using a simplified approach, and its posterior leaflet, using a more realistic approach. In this finite element simulation, we virtually installed an elliptical patch within the central portion of the posterior leaflet. To the best of the author’s knowledge, this type of simulation has not been performed previously. In another simulation, the effect of patch within the anterior leaflet was simulated. The results from the two different surgical simulations show that patch implantation helps the free edges of the leaflets come close to one another, which leads to improved coaptation. Additionally, the changes in chordal force distributions are also reported. Finally, this study answers a few questions regarding mitral valve patch augmentation surgeries and emphasizes the importance of further investigations on the influence of patch positioning and material properties on key outcomes. The ultimate goal is to use the proposed techniques to assess human models that are patient-specific

On Simultaneous Localization and Mapping inside the Human Body (Body-SLAM)

Wireless capsule endoscopy (WCE) offers a patient-friendly, non-invasive and painless investigation of the entire small intestine, where other conventional wired endoscopic instruments can barely reach. As a critical component of the capsule endoscopic examination, physicians need to know the precise position of the endoscopic capsule in order to identify the position of intestinal disease after it is detected by the video source. To define the position of the endoscopic capsule, we need to have a map of inside the human body. However, since the shape of the small intestine is extremely complex and the RF signal propagates differently in the non-homogeneous body tissues, accurate mapping and localization inside small intestine is very challenging. In this dissertation, we present an in-body simultaneous localization and mapping technique (Body-SLAM) to enhance the positioning accuracy of the WCE inside the small intestine and reconstruct the trajectory the capsule has traveled. In this way, the positions of the intestinal diseases can be accurately located on the map of inside human body, therefore, facilitates the following up therapeutic operations. The proposed approach takes advantage of data fusion from two sources that come with the WCE: image sequences captured by the WCE\u27s embedded camera and the RF signal emitted by the capsule. This approach estimates the speed and orientation of the endoscopic capsule by analyzing displacements of feature points between consecutive images. Then, it integrates this motion information with the RF measurements by employing a Kalman filter to smooth the localization results and generate the route that the WCE has traveled. The performance of the proposed motion tracking algorithm is validated using empirical data from the patients and this motion model is later imported into a virtual testbed to test the performance of the alternative Body-SLAM algorithms. Experimental results show that the proposed Body-SLAM technique is able to provide accurate tracking of the WCE with average error of less than 2.3cm