Non-ionizing tomographic imaging modalities for bedside lung monitoring
| dc.contributor.author | Vieira Pigatto, Andre, author | |
| dc.contributor.author | Mueller, Jennifer L., advisor | |
| dc.contributor.author | Wilson, Jesse, committee member | |
| dc.contributor.author | Rezende, Marlis, committee member | |
| dc.contributor.author | Wang, Zhijie, committee member | |
| dc.date.accessioned | 2023-06-01T23:55:53Z | |
| dc.date.available | 2024-05-26T23:55:53Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | The need for an accurate and non-ionizing imaging modality for pulmonary assessment of patients undergoing mechanical ventilation due to respiratory failure has increased due to COVID. The ability to quickly detect the development of pathologies at an early stage is highly desirable and could help reduce the incidence of complications. It is also clear that mechanical ventilation can cause ventilator-induced lung injuries, which can be avoided by adequately optimizing the positive end-expiratory pressure to induce alveolar recruitment while preventing hyperinflation. Here, I will explore two non-ionizing pulmonary imaging systems that could be used as monitoring systems in the intensive care unit: Ultrasound Computed Tomography (USCT) and Electrical Impedance Tomography (EIT). The most comprehensive part of this research is the development of a Low-Frequency USCT system, which was motivated by recent studies demonstrating that acoustic waves transmitted at frequencies between 10 kHz and 750 kHz penetrate the lungs and may be useful for thoracic imaging. A novel transducer based on Tonpilz was designed, characterized, and calibrated through vibrational, electrical, and acoustic measurements, and a flexible belt that holds up to 32 transducers was constructed. A Verasonics Vantage 64 Low-frequency Research Ultrasound system was programmed to collect data by transmitting and receiving signals at frequencies of 125 and 156 kHz. The data collection and processing algorithms were developed in MATLAB, and the system was tested on phantom and vertebrate animal experiments; image reconstructions were conducted using a Time-Of-Flight algorithm. As a secondary study, SMA-1, COVID, and regular patients were imaged and analyzed using EIT technology; these results are shown through journal and conference articles presented in the Appendix A and C of this document. | |
| dc.format.medium | born digital | |
| dc.format.medium | doctoral dissertations | |
| dc.identifier | VieiraPigatto_colostate_0053A_17643.pdf | |
| dc.identifier.uri | https://hdl.handle.net/10217/236662 | |
| dc.language | English | |
| dc.language.iso | eng | |
| dc.publisher | Colorado State University. Libraries | |
| dc.relation.ispartof | 2020- | |
| dc.rights | Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright. | |
| dc.title | Non-ionizing tomographic imaging modalities for bedside lung monitoring | |
| dc.type | Text | |
| dcterms.embargo.expires | 2024-05-26 | |
| dcterms.embargo.terms | 2024-05-26 | |
| dcterms.rights.dpla | This Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). | |
| thesis.degree.discipline | Biomedical Engineering | |
| thesis.degree.grantor | Colorado State University | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Doctor of Philosophy (Ph.D.) |
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