Three-dimensional electron beam dose calculations

The MDAH pencil-beam algorithm developed by Hogstrom et al (1981) has been widely used in clinics for electron beam dose calculations for radiotherapy treatment planning. The primary objective of this research was to address several deficiencies of that algorithm and to develop an enhanced version. Two enhancements have been incorporated into the pencil-beam algorithm; one models fluence rather than planar fluence, and the other models the bremsstrahlung dose using measured beam data. Comparisons of the resulting calculated dose distributions with measured dose distributions for several test phantoms have been made. From these results it is concluded (1) that the fluence-based algorithm is more accurate to use for the dose calculation in an inhomogeneous slab phantom, and (2) the fluence-based calculation provides only a limited improvement to the accuracy the calculated dose in the region just downstream of the lateral edge of an inhomogeneity. The source of the latter inaccuracy is believed primarily due to assumptions made in the pencil beam's modeling of the complex phantom or patient geometry.^ A pencil-beam redefinition model was developed for the calculation of electron beam dose distributions in three dimensions. The primary aim of this redefinition model was to solve the dosimetry problem presented by deep inhomogeneities, which was the major deficiency of the enhanced version of the MDAH pencil-beam algorithm. The pencil-beam redefinition model is based on the theory of electron transport by redefining the pencil beams at each layer of the medium. The unique approach of this model is that all the physical parameters of a given pencil beam are characterized for multiple energy bins. Comparisons of the calculated dose distributions with measured dose distributions for a homogeneous water phantom and for phantoms with deep inhomogeneities have been made. From these results it is concluded that the redefinition algorithm is superior to the conventional, fluence-based, pencil-beam algorithm, especially in predicting the dose distribution downstream of a local inhomogeneity. The accuracy of this algorithm appears sufficient for clinical use, and the algorithm is structured for future expansion of the physical model if required for site specific treatment planning problems. ^

BENCHMARKING AND IMPLEMENTATION OF A NEW INDEPENDENT MONTE CARLO DOSE CALCULATION QUALITY ASSURANCE AUDIT TOOL FOR CLINICAL TRIALS

Introduction Commercial treatment planning systems employ a variety of dose calculation algorithms to plan and predict the dose distributions a patient receives during external beam radiation therapy. Traditionally, the Radiological Physics Center has relied on measurements to assure that institutions participating in the National Cancer Institute sponsored clinical trials administer radiation in doses that are clinically comparable to those of other participating institutions. To complement the effort of the RPC, an independent dose calculation tool needs to be developed that will enable a generic method to determine patient dose distributions in three dimensions and to perform retrospective analysis of radiation delivered to patients who enrolled in past clinical trials. Methods A multi-source model representing output for Varian 6 MV and 10 MV photon beams was developed and evaluated. The Monte Carlo algorithm, know as the Dose Planning Method (DPM), was used to perform the dose calculations. The dose calculations were compared to measurements made in a water phantom and in anthropomorphic phantoms. Intensity modulated radiation therapy and stereotactic body radiation therapy techniques were used with the anthropomorphic phantoms. Finally, past patient treatment plans were selected and recalculated using DPM and contrasted against a commercial dose calculation algorithm. Results The multi-source model was validated for the Varian 6 MV and 10 MV photon beams. The benchmark evaluations demonstrated the ability of the model to accurately calculate dose for the Varian 6 MV and the Varian 10 MV source models. The patient calculations proved that the model was reproducible in determining dose under similar conditions described by the benchmark tests. Conclusions The dose calculation tool that relied on a multi-source model approach and used the DPM code to calculate dose was developed, validated, and benchmarked for the Varian 6 MV and 10 MV photon beams. Several patient dose distributions were contrasted against a commercial algorithm to provide a proof of principal to use as an application in monitoring clinical trial activity.

3D visualization of HIV virions by cryoelectron tomography.

The structure of the human immunodeficiency virus (HIV) and some of its components have been difficult to study in three-dimensions (3D) primarily because of their intrinsic structural variability. Recent advances in cryoelectron tomography (cryo-ET) have provided a new approach for determining the 3D structures of the intact virus, the HIV capsid, and the envelope glycoproteins located on the viral surface. A number of cryo-ET procedures related to specimen preservation, data collection, and image processing are presented in this chapter. The techniques described herein are well suited for determining the ultrastructure of bacterial and viral pathogens and their associated molecular machines in situ at nanometer resolution.

Interrelationships between the structural and functional aspects of social relationships, comorbidity and health related quality of life in breast cancer survivors

It is widely acknowledged in theoretical and empirical literature that social relationships, comprising of structural measures (social networks) and functional measures (perceived social support) have an undeniable effect on health outcomes. However, the actual mechanism of this effect has yet to be clearly understood or explicated. In addition, comorbidity is found to adversely affect social relationships and health related quality of life (a valued outcome measure in cancer patients and survivors). ^ This cross sectional study uses selected baseline data (N=3088) from the Women's Healthy Eating and Living (WHEL) study. Lisrel 8.72 was used for the latent variable structural equation modeling. Due to the ordinal nature of the data, Weighted Least Squares (WLS) method of estimation using Asymptotic Distribution Free covariance matrices was chosen for this analysis. The primary exogenous predictor variables are Social Networks and Comorbidity; Perceived Social Support is the endogenous predictor variable. Three dimensions of HRQoL, physical, mental and satisfaction with current quality of life were the outcome variables. ^ This study hypothesizes and tests the mechanism and pathways between comorbidity, social relationships and HRQoL using latent variable structural equation modeling. After testing the measurement models of social networks and perceived social support, a structural model hypothesizing associations between the latent exogenous and endogenous variables was tested. The results of the study after listwise deletion (N=2131) mostly confirmed the hypothesized relationships (TLI, CFI >0.95, RMSEA = 0.05, p=0.15). Comorbidity was adversely associated with all three HRQoL outcomes. Strong ties were negatively associated with perceived social support; social network had a strong positive association with perceived social support, which served as a mediator between social networks and HRQoL. Mental health quality of life was the most adversely affected by the predictor variables. ^ This study is a preliminary look at the integration of structural and functional measures of social relationships, comorbidity and three HRQoL indicators using LVSEM. Developing stronger social networks and forming supportive relationships is beneficial for health outcomes such as HRQoL of cancer survivors. Thus, the medical community treating cancer survivors as well as the survivor's social networks need to be informed and cognizant of these possible relationships. ^

THE MEASUREMENT OF HUMANISTIC AND DEHUMANISTIC BEHAVIORS IN HOSPITAL NURSING ENVIRONMENTS

The purpose of this investigation was to develop a reliable scale to measure the social environment of hospital nursing units according to the degree of humanistic and dehumanistic behaviors as perceived by nursing staff in hospitals. The study was based on a conceptual model proposed by Jan Howard, a sociologist. After reviewing the literature relevant to personalization of care, analyzing interviews with patients in various settings, and studying biological, psychological, and sociological frames of reference, Howard proposed the following necessary conditions for humanized health care. They were the dimensions of Irreplaceability, Holistic Selves, Freedom of Action, Status Equality, Shared Decision Making and Responsibility, Empathy, and Positive Affect.^ It was proposed that a scale composed of behaviors which reflected Howard's dimensions be developed within the framework of the social environment of nursing care units in hospitals. Nursing units were chosen because hospitals are traditionally organized around nursing care units and because patients spend the majority of their time in hospitals interacting with various levels of nursing personnel.^ Approximately 180 behaviors describing both patient and nursing staff behaviors which occur on nursing units were developed. Behaviors which were believed to be humanistic as well as dehumanistic were included. The items were classified under the dimensions of Howard's model by a purposively selected sample of 42 nurses representing a broad range of education, experience, and clinical areas. Those items with a high degree of agreement, at least 50%, were placed in the questionnaire. The questionnaire consisted of 169 items including six items from the Marlowe Crowne Social Desirability Scale (Short Form).^ The questionnaire, the Social Environment Scale, was distributed to the entire 7 to 3 shift nursing staff (603) of four hospitals including a public county specialty hospital, a public county general and acute hospital, a large university affiliated hospital with all services, and a small general community hospital. Staff were asked to report on a Likert type scale how often the listed behaviors occurred on their units. Three hundred and sixteen respondents (52% of the population) participated in the study.^ An item analysis was done in which each item was examined in relationship to its correlation to its own dimension total and to the totals of the other dimensions. As a result of this analysis, three dimensions, Positive Affect, Irreplaceability, and Freedom of Action were deleted from the scale. The final scale consisted of 70 items with 26 in Shared Decision Making and Responsibility, 25 in Holistic Selves, 12 in Status Equality, and seven in Empathy. The alpha coefficient was over .800 for all scales except Empathy which was .597.^ An analysis of variance by hospital was performed on the means of each dimension of the scale. There was a statistically significant difference between hospitals with a trend for the public hospitals to score lower on the scale than the university or community hospitals. That the scale scores should be lower in crowded, understaffed public hospitals was not unexpected and reflected that the scale had some discriminating ability. These differences were still observed after adjusting for the effect of Social Desirability.^ In summary, there is preliminary evidence based on this exploratory investigation that a reliable scale based on at least four dimensions from Howard's model could be developed to measure the concept of humanistic health care in hospital settings. ^