The epidemiology of prostate cancer among multiethnic men

The research goal was to document differences in the epidemiology of prostate cancer among multicultural men [non-Hispanic White (NHW), Hispanic (H), non-Hispanic Black (NHB)], and Black subgroups, particularly among NHB subgroups [US-born (USB) and Caribbean-born (CBB)]. Study findings will be useful in supporting further research into Black subgroups. Aim 1 explored changes over time in reported prostate cancer prevalence, by race/ethnicity and by birthplace (within the Black subgroups). Aim 2 investigated relationships between observed and latent variables. The analytical approaches included confirmatory factor analysis (CFA for measurement models) and structural equation modeling (SEM for regression models). National Center for Health Statistics, National Health Interview Survey (NHIS) data from 1999–2008 were used. The study sample included men aged 18 and older, grouped by race/ethnicity. Among the CBB group, survey respondents were limited to the English-speaking Caribbean. Prostate cancer prevalence, by race showed a higher trend among NHB men than NHW men overall, however differences over time were not significant. CBB men reported a higher proportion of prostate cancer among cancers diagnosed than USB men overall. Due to small sample sizes, stable prostate cancer prevalence trends could not be assessed over time nor could trends in the receipt of a PSA exam among NHB men when stratified by birthplace. USB and CBB men differ significantly in their screening behavior. The effect of SES on PSA screening adjusted for risk factors was statistically significant while latent variable lifestyle was not. Among risk factors, family history of cancer exhibited a consistent positive effect on PSA screening for both USB and CBB men. Among the CBB men, the number of years lived in the US did not significantly affect PSA screening behavior. When NHB men are stratified by birthplace, CBB men had a higher overall prevalence of prostate cancer diagnoses than USB men although not statistically significant. USB men were 2 to 3 times more likely to have had a PSA exam compared to CBB men, but among CBB men birthplace did not make a significant difference in screening behavior. Latent variable SES, but not lifestyle, significantly affected the likelihood of a PSA exam.

A novel 3-D segmentation algorithm for anatomic liver and tumor volume calculations for liver cancer treatment planning

Three-Dimensional (3-D) imaging is vital in computer-assisted surgical planning including minimal invasive surgery, targeted drug delivery, and tumor resection. Selective Internal Radiation Therapy (SIRT) is a liver directed radiation therapy for the treatment of liver cancer. Accurate calculation of anatomical liver and tumor volumes are essential for the determination of the tumor to normal liver ratio and for the calculation of the dose of Y-90 microspheres that will result in high concentration of the radiation in the tumor region as compared to nearby healthy tissue. Present manual techniques for segmentation of the liver from Computed Tomography (CT) tend to be tedious and greatly dependent on the skill of the technician/doctor performing the task. ^ This dissertation presents the development and implementation of a fully integrated algorithm for 3-D liver and tumor segmentation from tri-phase CT that yield highly accurate estimations of the respective volumes of the liver and tumor(s). The algorithm as designed requires minimal human intervention without compromising the accuracy of the segmentation results. Embedded within this algorithm is an effective method for extracting blood vessels that feed the tumor(s) in order to plan effectively the appropriate treatment. ^ Segmentation of the liver led to an accuracy in excess of 95% in estimating liver volumes in 20 datasets in comparison to the manual gold standard volumes. In a similar comparison, tumor segmentation exhibited an accuracy of 86% in estimating tumor(s) volume(s). Qualitative results of the blood vessel segmentation algorithm demonstrated the effectiveness of the algorithm in extracting and rendering the vasculature structure of the liver. Results of the parallel computing process, using a single workstation, showed a 78% gain. Also, statistical analysis carried out to determine if the manual initialization has any impact on the accuracy showed user initialization independence in the results. ^ The dissertation thus provides a complete 3-D solution towards liver cancer treatment planning with the opportunity to extract, visualize and quantify the needed statistics for liver cancer treatment. Since SIRT requires highly accurate calculation of the liver and tumor volumes, this new method provides an effective and computationally efficient process required of such challenging clinical requirements.^