Currently in our clinic, a mega-voltage cone beam computed tomography (MVCBCT) scan is performed before each treatment for patient localization. For non-small cell lung cancer (NSCLC) patients, a strain gauge is used as an external surrogate to indicate tumor motion in both the planning stage and the treatment stage. However, it is likely that the amplitude of tumor motion varies between treatment fractions without a corresponding change in the surrogate signal. Motion amplitude larger than what was planned may underdose the tumor and overexpose normal tissues.
The overall objective of this project is to extend the capabilities of MVCBCT for respiratory motion management by taking advantage of 2D projection images. First, a new method was developed to detect ipsi-lateral hemi-diaphragm apex (IHDA) motion along superior-inferior (SI) direction in 3D. Then a respiratory correlated reconstruction method was implemented and verified. This method is able to create MVCBCT volume in the full exhale (FE) and the full inhale (FI) phases, respectively. The diaphragm to tumor motion ratio (DTMR) was derived by quantifying the absolute position of the tumor and IHDA in these two volumes. The DTMR and the extracted IHDA motion were further used to calibrate the strain gauge signal.
Second, an organ motion detection approach was developed, in which the detection is converted into an optimal interrelated surface detection problem. The framework was first applied to tumor motion extraction, which enables accurate detection for large tumors (with a diameter not smaller than 1.9cm). The framework was then applied to lung motion extraction and the extracted lung motion model was used to create a series of displacement vector fields for a motion compensated (MC) reconstruction. The accuracy of both tumor extraction and the MC approach was validated, which shows their clinical feasibility.
Last but not least, a novel enhancement framework was developed. The aim of this approach is to eliminate the overlapping tissues and organs in the CBCT projection images. Though scattering and noise is the major problem, the proposed method is able to achieve enhanced projection images with a higher contrast to noise ratio (CNR) without compromising detection accuracy on tumors and IHDA.
| Identifer | oai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-3277 |
| Date | 01 July 2012 |
| Creators | Chen, Mingqing |
| Contributors | Siochi, R. Alfredo C. (Ramon Alfredo Carvalho) |
| Publisher | University of Iowa |
| Source Sets | University of Iowa |
| Language | English |
| Detected Language | English |
| Type | dissertation |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | Copyright 2012 Mingqing Chen |
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