Improving Cervical Cancer Nodal Boost Radiation Therapy by Quantifying Uncertainties and Exploring Advanced Radiation Therapy Modalities

Radiation therapy for patients with intact cervical cancer is frequently delivered using primary external beam radiation therapy (EBRT) followed by two fractions of intracavitary brachytherapy (ICBT). Although the tumor is the primary radiation target, controlling microscopic disease in the lymph nodes is just as critical to patient treatment outcome. In patients where gross lymphadenopathy is discovered, an extra EBRT boost course is delivered between the two ICBT fractions. Since the nodal boost is an addendum to primary EBRT and ICBT, the prescription and delivery must be performed considering previously delivered dose. This project aims to address the major issues of this complex process for the purpose of improving treatment accuracy while increasing dose sparing to the surrounding normal tissues. Because external beam boosts to involved lymph nodes are given prior to the completion of ICBT, assumptions must be made about dose to positive lymph nodes from future implants. The first aim of this project was to quantify differences in nodal dose contribution between independent ICBT fractions. We retrospectively evaluated differences in the ICBT dose contribution to positive pelvic nodes for ten patients who had previously received external beam nodal boost. Our results indicate that the mean dose to the pelvic nodes differed by up to 1.9 Gy between independent ICBT fractions. The second aim is to develop and validate a volumetric method for summing dose of the normal tissues during prescription of nodal boost. The traditional method of dose summation uses the maximum point dose from each modality, which often only represents the worst case scenario. However, the worst case is often an exaggeration when highly conformal therapy methods such as intensity modulated radiation therapy (IMRT) are used. We used deformable image registration algorithms to volumetrically sum dose for the bladder and rectum and created a voxel-by-voxel validation method. The mean error in deformable image registration results of all voxels within the bladder and rectum were 5 and 6 mm, respectively. Finally, the third aim explored the potential use of proton therapy to reduce normal tissue dose. A major physical advantage of protons over photons is that protons stop after delivering dose in the tumor. Although theoretically superior to photons, proton beams are more sensitive to uncertainties caused by interfractional anatomical variations, and must be accounted for during treatment planning to ensure complete target coverage. We have demonstrated a systematic approach to determine population-based anatomical margin requirements for proton therapy. The observed optimal treatment angles for common iliac nodes were 90° (left lateral) and 180° (posterior-anterior [PA]) with additional 0.8 cm and 0.9 cm margins, respectively. For external iliac nodes, lateral and PA beams required additional 0.4 cm and 0.9 cm margins, respectively. Through this project, we have provided radiation oncologists with additional information about potential differences in nodal dose between independent ICBT insertions and volumetric total dose distribution in the bladder and rectum. We have also determined the margins needed for safe delivery of proton therapy when delivering nodal boosts to patients with cervical cancer.

Validation of an instrument for assessing the medicolegal death investigation system: A public health approach

Background. This study validated the content of an instrument designed to assess the performance of the medicolegal death investigation system. The instrument was modified from Version 2.0 of the Local Public Health System Performance Assessment Instrument (CDC) and is based on the 10 Essential Public Health Services. ^ Aims. The aims were to employ a cognitive testing process to interview a randomized sample of medicolegal death investigation office leaders, qualitatively describe the results, and revise the instrument accordingly. ^ Methods. A cognitive testing process was used to validate the survey instrument's content in terms of the how well participants could respond to and interpret the questions. Twelve randomly selected medicolegal death investigation chiefs (or equivalent) that represented the seven types of medicolegal death investigation systems and six different state mandates were interviewed by telephone. The respondents also were representative of the educational diversity within medicolegal death investigation leadership. Based on respondent comments, themes were identified that permitted improvement of the instrument toward collecting valid and reliable information when ultimately used in a field survey format. ^ Results. Responses were coded and classified, which permitted the identification of themes related to Comprehension/Interpretation, Retrieval, Estimate/Judgment, and Response. The majority of respondent comments related to Comprehension/Interpretation of the questions. Respondents identified 67 questions and 6 section explanations that merited rephrasing, adding, or deleting examples or words. In addition, five questions were added based on respondent comments. ^ Conclusion. The content of the instrument was validated by cognitive testing method design. The respondents agreed that the instrument would be a useful and relevant tool for assessing system performance. ^

A novel method for evaluating an interaction effect of correlated continuous covariates in a linear model

Interaction effect is an important scientific interest for many areas of research. Common approach for investigating the interaction effect of two continuous covariates on a response variable is through a cross-product term in multiple linear regression. In epidemiological studies, the two-way analysis of variance (ANOVA) type of method has also been utilized to examine the interaction effect by replacing the continuous covariates with their discretized levels. However, the implications of model assumptions of either approach have not been examined and the statistical validation has only focused on the general method, not specifically for the interaction effect.^ In this dissertation, we investigated the validity of both approaches based on the mathematical assumptions for non-skewed data. We showed that linear regression may not be an appropriate model when the interaction effect exists because it implies a highly skewed distribution for the response variable. We also showed that the normality and constant variance assumptions required by ANOVA are not satisfied in the model where the continuous covariates are replaced with their discretized levels. Therefore, naïve application of ANOVA method may lead to an incorrect conclusion. ^ Given the problems identified above, we proposed a novel method modifying from the traditional ANOVA approach to rigorously evaluate the interaction effect. The analytical expression of the interaction effect was derived based on the conditional distribution of the response variable given the discretized continuous covariates. A testing procedure that combines the p-values from each level of the discretized covariates was developed to test the overall significance of the interaction effect. According to the simulation study, the proposed method is more powerful then the least squares regression and the ANOVA method in detecting the interaction effect when data comes from a trivariate normal distribution. The proposed method was applied to a dataset from the National Institute of Neurological Disorders and Stroke (NINDS) tissue plasminogen activator (t-PA) stroke trial, and baseline age-by-weight interaction effect was found significant in predicting the change from baseline in NIHSS at Month-3 among patients received t-PA therapy.^

The relationship between supermarket nutrient movements and the mortality rates from fat-associated and non-fat-associated cardiovascular disease: Development of an ecologic method for determining community food patterns

Supermarket nutrient movement, a community food consumption measure, aggregated 1,023 high-fat foods, representing 100% of visible fats and approximately 44% of hidden fats in the food supply (FAO, 1980). Fatty acid and cholesterol content of foods shipped from the warehouse to 47 supermarkets located in the Houston area were calculated over a 6 month period. These stores were located in census tracts with over 50% of a given ethnicity: Hispanic, black non-Hispanic, or white non-Hispanic. Categorizing the supermarket census tracts by predominant ethnicity, significant differences were found by ANOVA in the proportion of specific fatty acids and cholesterol content of the foods examined. Using ecological regression, ethnicity, income, and median age predicted supermarket lipid movements while residential stability did not. No associations were found between lipid movements and cardiovascular disease mortality, making further validation necessary for epidemiological application of this method. However, it has been shown to be a non-reactive and cost-effective method appropriate for tracking target foods in populations of groups, and for assessing the impact of mass media nutrition education, legislation, and fortification on community food and nutrient purchase patterns. ^

Advanced Protein Modeling Method: Benchmarking and Applications in Computer-Aided Drug Discovery

Development of homology modeling methods will remain an area of active research. These methods aim to develop and model increasingly accurate three-dimensional structures of yet uncrystallized therapeutically relevant proteins e.g. Class A G-Protein Coupled Receptors. Incorporating protein flexibility is one way to achieve this goal. Here, I will discuss the enhancement and validation of the ligand-steered modeling, originally developed by Dr. Claudio Cavasotto, via cross modeling of the newly crystallized GPCR structures. This method uses known ligands and known experimental information to optimize relevant protein binding sites by incorporating protein flexibility. The ligand-steered models were able to model, reasonably reproduce binding sites and the co-crystallized native ligand poses of the β2 adrenergic and Adenosine 2A receptors using a single template structure. They also performed better than the choice of template, and crude models in a small scale high-throughput docking experiments and compound selectivity studies. Next, the application of this method to develop high-quality homology models of Cannabinoid Receptor 2, an emerging non-psychotic pain management target, is discussed. These models were validated by their ability to rationalize structure activity relationship data of two, inverse agonist and agonist, series of compounds. The method was also applied to improve the virtual screening performance of the β2 adrenergic crystal structure by optimizing the binding site using β2 specific compounds. These results show the feasibility of optimizing only the pharmacologically relevant protein binding sites and applicability to structure-based drug design projects.