Radiation Dose Tracking in Digital Mammography: Evaluation of Population Profiles through Automatic Data Extraction from the DICOM Header

Abstract

International regulatory organizations for quality control of X-ray systems, such as the International Atomic Energy Agency (IAEA), have implemented protocols for acceptance testing of digital mammography and breast tomosynthesis equipment, aiming to establish quality standards in radiology services. However, these guidelines are usually based on tests with breast phantoms with standardizedthicknesses and compositions, often not representative of the patient population profiles at those services. In a prior study, we developed a computational system designed to automatically tracking and managing data extracted from the image acquisition processes of digital mammography and breast tomosynthesis, stored on a DICOM SCP (Service Class Provider) server. This approach enables obtaining technical reports characterizing exposure parameters and tests have shown that the reference levels outlined in international standards for breast composition and radiation dose do not accurately reflect the characteristics of the actual patient population. Thus this study describes data collection and corresponding analysis for the dose tracking process primarily on three digital mammography systems of different radiological services. Extensive image datasets from these systems were obtained using a new application described previously, with a focus on dose profiles generated during exposures. Graphical representations resultingfrom the datasets are presented, along with analysis of skin entrance and mean glandular doses distributions, average kV and mAs applied during the exams together with the target/filter combinations, radiographic density distribution, as well as the age and breast thickness characteristic of the respective population submitted to exposures in each of those mammography services. Additionally, the extent of information and ease of acquisition provided by the tool for performance evaluation of digital mammography services is discussed