NEW TOOLS FOR MONITORING GAMMA CAMERA UNIFORMITY

Detector uniformity is a fundamental performance characteristic of all modern gamma camera systems, and ensuring a stable, uniform detector response is critical for maintaining clinical images that are free of artifact. For these reasons, the assessment of detector uniformity is one of the most common activities associated with a successful clinical quality assurance program in gamma camera imaging. The evaluation of this parameter, however, is often unclear because it is highly dependent upon acquisition conditions, reviewer expertise, and the application of somewhat arbitrary limits that do not characterize the spatial location of the non-uniformities. Furthermore, as the goal of any robust quality control program is the determination of significant deviations from standard or baseline conditions, clinicians and vendors often neglect the temporal nature of detector degradation (1). This thesis describes the development and testing of new methods for monitoring detector uniformity. These techniques provide more quantitative, sensitive, and specific feedback to the reviewer so that he or she may be better equipped to identify performance degradation prior to its manifestation in clinical images. The methods exploit the temporal nature of detector degradation and spatially segment distinct regions-of-non-uniformity using multi-resolution decomposition. These techniques were tested on synthetic phantom data using different degradation functions, as well as on experimentally acquired time series floods with induced, progressively worsening defects present within the field-of-view. The sensitivity of conventional, global figures-of-merit for detecting changes in uniformity was evaluated and compared to these new image-space techniques. The image-space algorithms provide a reproducible means of detecting regions-of-non-uniformity prior to any single flood image’s having a NEMA uniformity value in excess of 5%. The sensitivity of these image-space algorithms was found to depend on the size and magnitude of the non-uniformities, as well as on the nature of the cause of the non-uniform region. A trend analysis of the conventional figures-of-merit demonstrated their sensitivity to shifts in detector uniformity. The image-space algorithms are computationally efficient. Therefore, the image-space algorithms should be used concomitantly with the trending of the global figures-of-merit in order to provide the reviewer with a richer assessment of gamma camera detector uniformity characteristics.

Health impacts of extreme weather: Flood fatalities in Texas

Floods are the leading cause of fatalities related to natural disasters in Texas. Texas leads the nation in flash flood fatalities. From 1959 through 2009 there were three times more fatalities in Texas (840) than the following state Pennsylvania (265). Texas also leads the nation in flood-related injuries (7753). Flood fatalities in Texas represent a serious public health problem. This study addresses several objectives of Healthy People 2010 including reducing deaths from motor vehicle accidents (Objective 15-15), reducing nonfatal motor vehicle injuries (Objective 15-17), and reducing drownings (Objective 15-29). The study examined flood fatalities that occurred in Texas between 1959 and 2008. Flood fatality statistics were extracted from three sources: flood fatality databases from the National Climatic Data Center, the Spatial Hazard Event and Loss Database for the United States, and the Texas Department of State Health Services. The data collected for flood fatalities include the date, time, gender, age, location, and type of flood. Inconsistencies among the three databases were identified and discussed. Analysis reveals that most fatalities result from driving into flood water (77%). Spatial analysis indicates that more fatalities occurred in counties containing major urban centers – some of the Flash Flood Alley counties (Bexar, Dallas, Travis, and Tarrant), Harris County (Houston), and Val Verde County (Del Rio). An intervention strategy targeting the behavior of driving into flood water is proposed. The intervention is based on the Health Belief model. The main recommendation of the study is that flood fatalities in Texas can be reduced through a combination of improved hydrometeorological forecasting, educational programs aimed at enhancing the public awareness of flood risk and the seriousness of flood warnings, and timely and appropriate action by local emergency and safety authorities.^