Bias and Variability In Image-Based Volumetric Yttrium-90 Dosimetry

<p>90Y-microsphere therapy has been widely accepted as a treatment option for both primary and metastatic liver tumors where the patients are ineligible for surgical resection and external beam radiation therapy. The prognosis of untreated patient having liver cancer is very poor with life expectancy less than a year at advance stage. Hence the ability to predict treatment efficacy right after the treatment from post-therapy imaging will help personalize treatment strategies and achieve better outcome. Such prediction can be modeled from correlation of dose and tumor response metrics.</p> <p>It has been shown that local dose deposition method can generate dose map from 90Y emission images with accuracy comparable to dose-point kernel and Monte Carlo simulation methods. The bias and variability of the input images remain to be the weakest link in volumetric dosimetry. The objectives of this dissertation project were to improve image-based volumetric 90Y dose quantification using current commercially available systems and to determine its limitation (bias/variability).</p> <p>We have developed a practical image reconstruction method for 90Y bremsstrahlung SPECT/CT (bSPECT/CT) images with CT attenuation correction and energy-window based background compensation. Although the volumetric quantitative accuracy of our bSPECT/CT images is limited by partial volume effect, the images can be used to accurately quantify the total 90Y activity delivered to the patient, which allow gross treatment delivery verification and limited outcome prediction.</p> <p>We have also characterized the accuracy and variability of volumetric 90Y dosimetry calculated from count-limited 90Y-PET/CT images. Knowledge of overall errors (systematic and random) in volumetric 90Y dosimetry is important to derive statistically significant dose-response model, which in turn allowing prediction of treatment outcome and personalization of treatment strategy.</p>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation (PhD)

Year dc:date.available

2016

Author dc:creator

• Siman, Wendy

Contributors dc:contributor

• S. Cheenu Kappadath
• Veera Baladandayuthapani
• Peter A. Balter

• Y90
• microsphere
• dosimetry
• PET/CT
• SPECT/CT
• quantitative
• bias
• variability
• Medicine and Health Sciences

Repository record dc:identifier

https://digitalcommons.library.tmc.edu/utgsbs_dissertations/703

OAI identifier oai:identifier

oai:digitalcommons.library.tmc.edu:utgsbs_dissertations-1748