Show simple item record

dc.contributor.advisorSchowengerdt, Robert A.en_US
dc.contributor.authorXu, Qianyi
dc.creatorXu, Qianyien_US
dc.date.accessioned2011-12-06T13:43:28Z
dc.date.available2011-12-06T13:43:28Z
dc.date.issued2007en_US
dc.identifier.urihttp://hdl.handle.net/10150/195222
dc.description.abstractLung cancer is the most deadly cancer in the United States. Radiation therapy uses ionizing radiation with high energy to destroy lung tumor cells by damaging their genetic material, preventing those cells from reproducing. The most challenging aspect of modern radiation therapy for lung cancer is the motion of lung tumors caused by patient breathing during treatment. Most gating based radiotherapy derives the tumor motion from external surrogates and generates a respiratory signal to trigger the beam. We propose a method that monitors internal diaphragm motion, which can provide a respiratory signal that is more highly correlated to lung tumor motion compared to the external surrogates. We also investigate direct tracking of the tumor in fluoroscopic video imagery. We tracked fixed tumor contours in fluoroscopic videos for 5 patients. The predominant tumor displacements are well tracked based on optical flow. Some tumors or nearby anatomy features exhibit severe nonrigid deformation, especially in the supradiaphragmatic region. By combining Active Shape Models and the respiratory signal, the deformed contours are tracked within a range defined in the training period. All the tracking results are validated by a human expert and the proposed methods are promising for applications in radiotherapy. Another important aspect of lung patient treatment is patient setup verification, which is needed to reduce inter- and intra-fractions geometry uncertainties and ensure precise dose delivery. Currently, there is no universally accepted method for lung patient verification. We propose to register 4DCT and 2D x-ray images taken before treatment to derive the couch shifts necessary for precise radiotherapy. The proposed technique leads to improved patient care.
dc.language.isoENen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectRadiation Therapyen_US
dc.subjectTumor Trackingen_US
dc.subjectRegistrationen_US
dc.subjectRespiratory Gatingen_US
dc.subjectSetup Verificationen_US
dc.titleTowards Intelligent Tumor Tracking and Setup Verification in Radiation Therapy For Lung Canceren_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.contributor.chairSchowengerdt, Robert A.en_US
dc.identifier.oclc659747124en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.contributor.committeememberHamilton, Russell J.en_US
dc.contributor.committeememberStrickland, Robin N.en_US
dc.identifier.proquest2041en_US
thesis.degree.disciplineElectrical & Computer Engineeringen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.namePhDen_US
refterms.dateFOA2018-07-01T02:31:32Z
html.description.abstractLung cancer is the most deadly cancer in the United States. Radiation therapy uses ionizing radiation with high energy to destroy lung tumor cells by damaging their genetic material, preventing those cells from reproducing. The most challenging aspect of modern radiation therapy for lung cancer is the motion of lung tumors caused by patient breathing during treatment. Most gating based radiotherapy derives the tumor motion from external surrogates and generates a respiratory signal to trigger the beam. We propose a method that monitors internal diaphragm motion, which can provide a respiratory signal that is more highly correlated to lung tumor motion compared to the external surrogates. We also investigate direct tracking of the tumor in fluoroscopic video imagery. We tracked fixed tumor contours in fluoroscopic videos for 5 patients. The predominant tumor displacements are well tracked based on optical flow. Some tumors or nearby anatomy features exhibit severe nonrigid deformation, especially in the supradiaphragmatic region. By combining Active Shape Models and the respiratory signal, the deformed contours are tracked within a range defined in the training period. All the tracking results are validated by a human expert and the proposed methods are promising for applications in radiotherapy. Another important aspect of lung patient treatment is patient setup verification, which is needed to reduce inter- and intra-fractions geometry uncertainties and ensure precise dose delivery. Currently, there is no universally accepted method for lung patient verification. We propose to register 4DCT and 2D x-ray images taken before treatment to derive the couch shifts necessary for precise radiotherapy. The proposed technique leads to improved patient care.


Files in this item

Thumbnail
Name:
azu_etd_2041_sip1_m.pdf
Size:
2.528Mb
Format:
PDF
Description:
azu_etd_2041_sip1_m.pdf

This item appears in the following Collection(s)

Show simple item record