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Quantifying and Modeling Radiation Therapy-induced Ventilation Changes and Investigating the Robustness of 4DCT-based Functional Avoidance
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Quantifying and Modeling Radiation Therapy-induced Ventilation Changes and Investigating the Robustness of 4DCT-based Functional Avoidance. |
| 개인저자 | Patton, Taylor J. |
| 단체저자명 | The University of Wisconsin - Madison. Medical Physics. |
| 발행사항 | [S.l.]: The University of Wisconsin - Madison., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 151 p. |
| 기본자료 저록 | Dissertation Abstracts International 80-01B(E). Dissertation Abstract International |
| ISBN | 9780438354586 |
| 학위논문주기 | Thesis (Ph.D.)--The University of Wisconsin - Madison, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
Adviser: John E. Bayouth. |
| 요약 | Four-dimensional computed tomography-based ventilation is a developing method for estimating the lung function of patients. The response of 4DCT-based ventilation to radiation therapy (RT) has remained largely uncharacterized. The purpose of thi |
| 요약 | Pre-RT and post-RT ventilation estimations were acquired, and the voxel-wise response of the post-RT ventilation to dose and pre-RT ventilation was determined. High-dose regions sustained more ventilation decline than low-dose regions. Increased |
| 요약 | A polynomial regression model was created using pre-RT ventilation and dose to predict post-RT ventilation. This model showed significant predictive power on the cross-validation dataset as measured by gamma pass rates. The model was applied to |
| 요약 | Predictive models were created to include the average heart dose and average lobe dose using linear regression and regression neural networks. The linear regression model including heart and lobe dose had the highest predictive power as measured |
| 요약 | The impact of respiratory motion on functional avoidance was investigated using three representative dose distributions. The worst-case scenario dose distribution represented the patient at end-inspiration for the entirety of treatment. However, |
| 일반주제명 | Medical imaging. Physics. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
