Walz‐Flannigan, Alisa

AbstractReject rate analysis is considered an integral part of a diagnostic radiography quality control (QC) program. A rejected image is a patient radiograph that was not presented to a radiologist for diagnosis and that contributes unnecessary radiation dose to the patient. Reject rates that are either too high or too low may suggest systemic department shortcomings in QC mechanisms. Due to the lack of standardization, reject data often cannot be easily compared between radiography systems from different vendors. The purpose of this report is to provide guidance to help standardize data elements that are required for comprehensive reject analysis and to propose data reporting and workflows to enable an effective and comprehensive reject rate monitoring program. Essential data elements, a proposed schema for classifying reject reasons, and workflow implementation options are recommended in this task group report.

AbstractBackgroundDigital radiography (DR) still presents many challenges and could have complex imaging acquisition and processing patterns in a clinical practice hindering quality standardization.PurposeThis technical note aims to report the 4‐year experience with utilizing a custom DICOM metadata analytics program in clinical DR at a large institution.MethodsThirty‐eight DR systems of three vendors at multiple locations were configured to automatically send clinical DICOM images to a DICOM receiver. A suite of custom MATLAB programs was established to extract and store public and private header data weekly. Specific use cases are provided for systematic image acquisition investigation, image processing harmonization, exposure index (EI) longitudinal monitoring and EI target optimization.ResultsFor systematic acquisition investigation, an example of adult lumbar spine exam analysis was provided with statistics on manual acquisition versus the use of automatic exposure control (AEC, including AEC dose level, active cell, and backup timer), grid usage, and collimation for various projections. For processing harmonization, up to 12.6% of protocols were revealed to have processing parameter differences in an example of a mobile radiography fleet. In addition, inconsistent use of a post‐acquisition image size function was also demonstrated, which resulted in anatomy size display variations. Bimonthly monitoring of median EI values showed expected trends, including changes after an AEC dose level adjustment for adult posterior‐anterior chest imaging on a scanner system. An example of adult axillary shoulder EI target refinement was shared using the median value, eμ, based on the lognormal EI data distribution after parsing down to acquisitions with appropriate techniques.ConclusionsThis analytics program enables systematic analysis of image acquisition and processing details. The information provides invaluable insights into real practice patterns, which can support data‐driven quality standardization and optimization.

PurposeWe summarize the AAPM TG248 Task Group report on interoperability assessment for the commissioning of medical imaging acquisition systems in order to bring needed attention to the value and role of quality assurance testing throughout the imaging chain.MethodsTo guide the clinical physicist involved in commissioning of imaging systems, we describe a framework and tools for incorporating interoperability assessment into imaging equipment commissioning.ResultsWhile equipment commissioning may coincide with equipment acceptance testing, its scope may extend beyond validation of product or purchase specifications. Equipment commissioning is meant to provide assurance that a system is ready for clinical use, and system interoperability plays an essential role in the clinical use of an imaging system.ConclusionThe functionality of a diagnostic imaging system extends beyond the acquisition console and depends on interoperability with a host of other systems such as the Radiology Information System, a Picture Archive and Communication System, post‐processing software, treatment planning software, and clinical viewers.