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.

Devices in heart failure: potential methods for device-based monitoring of congestive heart failure.

Congestive heart failure has long been one of the most serious medical conditions in the United States; in fact, in the United States alone, heart failure accounts for 6.5 million days of hospitalization each year. One important goal of heart-failure therapy is to inhibit the progression of congestive heart failure through pharmacologic and device-based therapies. Therefore, there have been efforts to develop device-based therapies aimed at improving cardiac reserve and optimizing pump function to meet metabolic requirements. The course of congestive heart failure is often worsened by other conditions, including new-onset arrhythmias, ischemia and infarction, valvulopathy, decompensation, end-organ damage, and therapeutic refractoriness, that have an impact on outcomes. The onset of such conditions is sometimes heralded by subtle pathophysiologic changes, and the timely identification of these changes may promote the use of preventive measures. Consequently, device-based methods could in the future have an important role in the timely identification of the subtle pathophysiologic changes associated with congestive heart failure.

Characterization of fecal contamination targeting 16S rRNA bacteroides molecular markers in the Santa Cruz River, Arizona

Understanding the origins, transport and fate of contamination is essential to effective management of water resources and public health. Individuals and organizations with management responsibilities need to understand the risks to ecosystems and to humans from contact with contamination. Managers also need to understand how key contaminants vary over time and space in order to design and prioritize mitigation strategies. Tumacacori National Historic Park (NHP) is responsible for management of its water resources for the benefit of the park and for the health of its visitors. The existence of microbial contaminants in the park poses risks that must be considered in park planning and operations. The water quality laboratory at the Maricopa Agricultural Center (in collaboration with stakeholder groups and individuals located in the ADEQ-targeted watersheds) identified biological changes in surface water quality in impaired reaches rivers to determine the sources of Escherichia coli (E. coli); bacteria utilizing innovative water quality microbial/bacterial source tracking methods. The end goal was to support targeted watershed groups and ADEQ towards E. coli reductions. In the field monitoring was conducted by the selected targeted watershed groups in conjunction with The University of Arizona Maricopa Agricultural Center Water Quality Laboratory. This consisted of collecting samples for Bacteroides testing from multiple locations on select impaired reaches, to determine contamination resulting from cattle, human recreation, and other contributions. Such testing was performed in conjunction with high flow and base flow conditions in order to accurately portray water quality conditions and variations. Microbial monitoring was conducted by The University of Arizona Water Quality Laboratory at the Maricopa Agricultural Center using genetic typing to differentiate among two categories of Bacteroides: human and all (total). Testing used microbial detection methodologies and molecular source tracking techniques.^