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CT-PET Image Fusion and PET Image Segmentation for Radiation Therapy

Zheng, Yiran
http://rave.ohiolink.edu/etdc/view?acc_num=case1283542509

Abstract Details

2011, Doctor of Philosophy, Case Western Reserve University, Biomedical Engineering.
PET imaging system delivers abundant functional information which is complementary to the anatomical information provided by CT images. The purpose of this research is to improve the physician's ability to localize and delineate the extent of the tumor by incorporation of the PET images into radiation therapy treatment planning. A machine-based CT-PET fiducial fusion method was implemented for head and neck carcinoma radiation therapy. In this method, the field arrangements are aligned relative to the fixed treatment machine isocenter and patients are imaged in actual treatment positions. A fiducial registration error (FRE) of 1 mm was found for this fiducial fusion method. The target registration error (TRE) of seven anatomical landmarks was measured to evaluate the accuracy of this method. The results were compared with a manual and a mutual information based automatic fusion method. Statistical analysis showed there was no significant difference of TREs between the fiducial fusion method and the manual method which is considered to be most accurate in this research. In addition, a new thresholding PET image segmentation method was proposed using a lookup table which consists of the recovered activity concentration ratios and the initial estimates of target volume. To validate the proposed segmentation method, a Jaszczak phantom containing hollow spheres with variable size and FDG concentration contrast ratio was scanned in different PET scanners. The average uncertainty of the volume estimation by the proposed method was 11.2% for spheres greater than 2.5 mL, which were comparable or superior to those determined by contrast-oriented method and iterative threshold method (ITM). This new segmentation method was also applied to the PET images of ten patients with solitary lung metastases. The average segmented PET volume was within 8.0% of the CT volumes. These combined methodologies as outlined above are expected to decrease the conformality index of the tumor dose (tumor volume/target volume) and spare the normal tissue, which will result in an overall improvement in the effective delivery of therapeutic radiation to patients. The suggested future work includes further validation of the proposed methods at different PET scanners and clinical application of these methods.
Barry Wessels, PhD (Advisor)
Andrew Rollins, PhD (Committee Chair)
Xin Yu, PhD (Committee Member)
Syed Akber, PhD (Committee Member)
119 p.
Biomedical Research
CT-PET image fusion; fiducial fusion; PET image segmentation; target delineation; radiation therapy treatment planning

Recommended Citations

Citations

  • Zheng, Y. (2011). CT-PET Image Fusion and PET Image Segmentation for Radiation Therapy [Doctoral dissertation, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1283542509

    APA Style (7th edition)

  • Zheng, Yiran. CT-PET Image Fusion and PET Image Segmentation for Radiation Therapy. 2011. Case Western Reserve University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1283542509.

    MLA Style (8th edition)

  • Zheng, Yiran. "CT-PET Image Fusion and PET Image Segmentation for Radiation Therapy." Doctoral dissertation, Case Western Reserve University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=case1283542509

    Chicago Manual of Style (17th edition)

case1283542509
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© 2010, all rights reserved.
This open access ETD is published by Case Western Reserve University School of Graduate Studies and OhioLINK.