DUAL ENERGY COMPUTED TOMOGRAPHY FOR PROTON THERAPY TREATMENT PLANNING

Proton radiation therapy is gaining popularity because of the unique characteristics of its dose distribution, e.g., high dose-gradient at the distal end of the percentage-depth-dose curve (known as the Bragg peak). The high dose-gradient offers the possibility of delivering high dose to the target while still sparing critical organs distal to the target. However, the high dose-gradient is a double-edged sword: a small shift of the highly conformal high-dose area can cause the target to be substantially under-dosed or the critical organs to be substantially over-dosed. Because of that, large margins are required in treatment planning to ensure adequate dose coverage of the target, which prevents us from realizing the full potential of proton beams. Therefore, it is critical to reduce uncertainties in the proton radiation therapy. One major uncertainty in a proton treatment is the range uncertainty related to the estimation of proton stopping power ratio (SPR) distribution inside a patient. The SPR distribution inside a patient is required to account for tissue heterogeneities when calculating dose distribution inside the patient. In current clinical practice, the SPR distribution inside a patient is estimated from the patient’s treatment planning computed tomography (CT) images based on the CT number-to-SPR calibration curve. The SPR derived from a single CT number carries large uncertainties in the presence of human tissue composition variations, which is the major drawback of the current SPR estimation method. We propose to solve this problem by using dual energy CT (DECT) and hypothesize that the range uncertainty can be reduced by a factor of two from currently used value of 3.5%. A MATLAB program was developed to calculate the electron density ratio (EDR) and effective atomic number (EAN) from two CT measurements of the same object. An empirical relationship was discovered between mean excitation energies and EANs existing in human body tissues. With the MATLAB program and the empirical relationship, a DECT-based method was successfully developed to derive SPRs for human body tissues (the DECT method). The DECT method is more robust against the uncertainties in human tissues compositions than the current single-CT-based method, because the DECT method incorporated both density and elemental composition information in the SPR estimation. Furthermore, we studied practical limitations of the DECT method. We found that the accuracy of the DECT method using conventional kV-kV x-ray pair is susceptible to CT number variations, which compromises the theoretical advantage of the DECT method. Our solution to this problem is to use a different x-ray pair for the DECT. The accuracy of the DECT method using different combinations of x-ray energies, i.e., the kV-kV, kV-MV and MV-MV pair, was compared using the measured imaging uncertainties for each case. The kV-MV DECT was found to be the most robust against CT number variations. In addition, we studied how uncertainties propagate through the DECT calculation, and found general principles of selecting x-ray pairs for the DECT method to minimize its sensitivity to CT number variations. The uncertainties in SPRs estimated using the kV-MV DECT were analyzed further and compared to those using the stoichiometric method. The uncertainties in SPR estimation can be divided into five categories according to their origins: the inherent uncertainty, the DECT modeling uncertainty, the CT imaging uncertainty, the uncertainty in the mean excitation energy, and SPR variation with proton energy. Additionally, human body tissues were divided into three tissue groups – low density (lung) tissues, soft tissues and bone tissues. The uncertainties were estimated separately because their uncertainties were different under each condition. An estimate of the composite range uncertainty (2s) was determined for three tumor sites – prostate, lung, and head-and-neck, by combining the uncertainty estimates of all three tissue groups, weighted by their proportions along typical beam path for each treatment site. In conclusion, the DECT method holds theoretical advantages in estimating SPRs for human tissues over the current single-CT-based method. Using existing imaging techniques, the kV-MV DECT approach was capable of reducing the range uncertainty from the currently used value of 3.5% to 1.9%-2.3%, but it is short to reach our original goal of reducing the range uncertainty by a factor of two. The dominant source of uncertainties in the kV-MV DECT was the uncertainties in CT imaging, especially in MV CT imaging. Further reduction in beam hardening effect, the impact of scatter, out-of-field object etc. would reduce the Hounsfeld Unit variations in CT imaging. The kV-MV DECT still has the potential to reduce the range uncertainty further.

HPV vaccine coverage in Texas counties: An application of multilevel, small area estimation

Health departments, research institutions, policy-makers, and healthcare providers are often interested in knowing the health status of their clients/constituents. Without the resources, financially or administratively, to go out into the community and conduct health assessments directly, these entities frequently rely on data from population-based surveys to supply the information they need. Unfortunately, these surveys are ill-equipped for the job due to sample size and privacy concerns. Small area estimation (SAE) techniques have excellent potential in such circumstances, but have been underutilized in public health due to lack of awareness and confidence in applying its methods. The goal of this research is to make model-based SAE accessible to a broad readership using clear, example-based learning. Specifically, we applied the principles of multilevel, unit-level SAE to describe the geographic distribution of HPV vaccine coverage among females aged 11-26 in Texas.^ Multilevel (3 level: individual, county, public health region) random-intercept logit models of HPV vaccination (receipt of ≥ 1 dose Gardasil® ) were fit to data from the 2008 Behavioral Risk Factor Surveillance System (outcome and level 1 covariates) and a number of secondary sources (group-level covariates). Sampling weights were scaled (level 1) or constructed (levels 2 & 3), and incorporated at every level. Using the regression coefficients (and standard errors) from the final models, I simulated 10,000 datasets for each regression coefficient from the normal distribution and applied them to the logit model to estimate HPV vaccine coverage in each county and respective demographic subgroup. For simplicity, I only provide coverage estimates (and 95% confidence intervals) for counties.^ County-level coverage among females aged 11-17 varied from 6.8-29.0%. For females aged 18-26, coverage varied from 1.9%-23.8%. Aggregated to the state level, these values translate to indirect state estimates of 15.5% and 11.4%, respectively; both of which fall within the confidence intervals for the direct estimates of HPV vaccine coverage in Texas (Females 11-17: 17.7%, 95% CI: 13.6, 21.9; Females 18-26: 12.0%, 95% CI: 6.2, 17.7).^ Small area estimation has great potential for informing policy, program development and evaluation, and the provision of health services. Harnessing the flexibility of multilevel, unit-level SAE to estimate HPV vaccine coverage among females aged 11-26 in Texas counties, I have provided (1) practical guidance on how to conceptualize and conduct modelbased SAE, (2) a robust framework that can be applied to other health outcomes or geographic levels of aggregation, and (3) HPV vaccine coverage data that may inform the development of health education programs, the provision of health services, the planning of additional research studies, and the creation of local health policies.^

THE DECLINE OF ISCHEMIC HEART DISEASE MORTALITY IN TEXAS: HEALTH PLANNING IMPLICATIONS

This is a report on an empirical study of the decline of ischemic heart disease mortality in the State of Texas. The study period was from 1970 to 1977. The data was collected and analyzed at three different levels of analysis: state, health service area (HSA), and county. The study was designed to test five main hypotheses. They serve to test the role of the medical care system as a possible factor associated with the changing ischemic heart disease mortality trends.^ The principal findings of the study were that a reasonable relationship could be found between the number of emergency medical care personnel, the number of icu-ccu beds, the number of medical specialists and the percent of hospitals with icu-ccu and the decline in ischemic heart disease mortality for the State of Texas. However, non significant relationships were found between variables in the medical care system and ischemic heart disease mortality trends, at the health service area level of analysis. More specifically, the number of coronary care unit beds was found to be negatively correlated with the decline in ischemic heart disease mortality at the county level.^ While being limited in its scope, the study suggests that certain factors (emergency medical service, icu-ccu beds, percent of icu-ccu units, and medical specialists) have been shown to be associated with the observed decline in ischemic heart disease mortality. The study also suggests many avenues of future research that need to be explored. ^

THE APPLICATION OF CIRRHOSIS MORTALITY AND SUICIDE MORTALITY AS INDICATORS FOR ALCOHOLISM PLANNING

This study provides a review of the current alcoholism planning process of the Houston-Galveston planning process of the Houston-Galveston Area Council, an agency carrying out planning for a thirteen county region in surrounding Houston, Texas. The four central groups involved in this planning are identified, and the role that each plays and how it effects the planning outcomes is discussed.^ The most substantive outcome of the Houston-Galveston Area Council's alcoholism planning, the Regional Alcoholism/Alcohol Abuse Plan is examined. Many of the shortcomings in the data provided, and the lack of other data necessary for planning are offered.^ A problem oriented planning model is presented as an alternative to the Houston-Galveston Area Council's current service oriented approach to alcoholism planning. Five primary phases of the model, identification of the problem, statement of objectives, selection of alternative programs, implementation, and evaluation, are presented, and an overview of the tasks involved in the application of this model to alcoholism planning is offered.^ A specific aspect of the model, the use of problem status indicators is explored using cirrhosis and suicide mortality data. A review of the literature suggests that based on five criteria, availability, subgroup identification, validity, reliability, and sensitivity, both suicide and cirrhosis are suitable as indicators of the alcohol problem when combined with other indicators.^ Cirrhosis and suicide mortality data are examined for the thirteen county Houston-Galveston Region for the years 1969 through 1976. Data limitations preclude definite conclusions concerning the alcohol problem in the region. Three hypotheses about the nature of the regional alcohol problem are presented. First, there appears to be no linear trend in the number of alcoholics that are at risk of suicide and cirrhosis mortality. Second, the number of alcoholics in the metropolitan areas seems to be greater than the number of rural areas. Third, the number of male alcoholics at risk of cirrhosis and suicide mortality is greater than the number of female alcoholics.^