AAPM task group report 305: Guidance for standardization of vendor-neutral reject analysis in radiography.

Reject 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.

Technical note: Four-year experience with utilization of DICOM metadata analytics in clinical digital radiography practice.

BACKGROUND: Digital radiography (DR) still presents many challenges and could have complex imaging acquisition and processing patterns in a clinical practice hindering quality standardization. PURPOSE: This technical note aims to report the 4-year experience with utilizing a custom DICOM metadata analytics program in clinical DR at a large institution. METHODS: Thirty-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. RESULTS: For 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. CONCLUSIONS: This 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.

Practical application of AAPM Report 270 in display quality assurance: A report of Task Group 270.

Published in January 2019, AAPM Report 270 provides an update to the recommendations of the AAPM's "TG18" report. Report 270 provides new definitions of display types, updated testing patterns, and revised performance standards for the modern, flat-panel displays used as part of medical image acquisition and review. The focus of the AAPM report is on consistent image quality and appearance, and how to establish a quality assurance program to achieve those two goals. This work highlights some of the key takeaways of AAPM Report 270 and makes comparisons with existing recommendations from other references. It also provides guidance for establishing a display quality assurance program for different-sized institutions. Finally, it describes future challenges for display quality assurance and what work remains.

Summary of the AAPM task group 248 report: Interoperability assessment for the commissioning of medical imaging acquisition systems.

PURPOSE: We 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. METHODS: To guide the clinical physicist involved in commissioning of imaging systems, we describe a framework and tools for incorporating interoperability assessment into imaging equipment commissioning. RESULTS: While 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. CONCLUSION: The 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.

Pictorial Review of Digital Radiography Artifacts.

Visual familiarity with the variety of digital radiographic artifacts is needed to identify, resolve, or prevent image artifacts from creating issues with patient imaging. Because the mechanism for image creation is different between flat-panel detectors and computed radiography, the causes and appearances of some artifacts can be unique to these different modalities. Examples are provided of artifacts that were found on clinical images or during quality control testing with flat-panel detectors. The examples are meant to serve as learning tools for future identification and troubleshooting of artifacts and as a reminder for steps that can be taken for prevention. The examples of artifacts provided are classified according to their causal connection in the imaging chain, including an equipment defect as a result of an accident or mishandling, debris or gain calibration flaws, a problematic acquisition technique, signal transmission failures, and image processing issues. Specific artifacts include those that are due to flat-panel detector drops, backscatter, debris in the x-ray field during calibration, detector saturation or underexposure, or collimation detection errors, as well as a variety of artifacts that are processing induced. ©RSNA, 2018.

Implementing a radiology-information technology project: mobile image viewing use case and a general guideline for radiologist-information technology team collaboration.

OBJECTIVE: This article illustrates the importance of radiologist engagement in the successful implementation of radiology-information technology (IT) projects through the example of establishing a mobile image viewing solution for health care professionals. CONCLUSION: With an understanding of the types of decisions that benefit from radiologist input, this article outlines an overall project framework to provide a context for how radiologists might engage in the project cycle.

Medical imaging displays and their use in image interpretation.

The adequate and repeatable performance of the image display system is a key element of information technology platforms in a modern radiology department. However, despite the wide availability of high-end computing platforms and advanced color and gray-scale monitors, the quality and properties of the final displayed medical image may often be inadequate for diagnostic purposes if the displays are not configured and maintained properly. In this article-an expanded version of the Radiological Society of North America educational module "Image Display"-the authors discuss fundamentals of image display hardware, quality control and quality assurance processes for optimal image interpretation settings, and parameters of the viewing environment that influence reader performance. Radiologists, medical physicists, and other allied professionals should strive to understand the role of display technology and proper usage for a quality radiology practice. The display settings and display quality control and quality assurance processes described in this article can help ensure high standards of perceived image quality and image interpretation accuracy.

Human contrast-detail performance with declining contrast.

PURPOSE: How do display settings and ambient lighting affect contrast detection thresholds for human observers? Can recalibrating a display for high ambient lighting improve object detection? METHODS: Contrast∕detail (CD) threshold detection performance was measured for observers using four color displays with varying overall contrast (e.g., differing maximum luminance and ambient lighting conditions). Detailed mapping of contrast detection performance (for fixed object size) was tracked as a function of: display maximum luminance, ambient lighting changes (with and without recalibrating for the higher ambience), and the performance of radiologists vs. nonradiologists. RESULTS: The initial phase was analyzed with a hierarchical linear model of observer performance using: background gray level, maximum display luminance, and radiologist vs. nonradiologist. The only statistically significant finding was a maximum luminance of 100 cd∕m(2) display performing worse than a baseline peak of 400 cd∕m(2). The second phase examined ambient lighting effects on detection thresholds. Background gray level and maximum display luminance were examined coupled with ambient lighting for: baseline at 30, 435 uncorrected, and 435 lx with display recalibration for the ambient conditions. Results showed ambient correction improved sensitivity for small background digital driving level, but not at higher luminance backgrounds. CONCLUSIONS: For CD study, nonradiologist observers can be used without loss of applicability. Contrast detection thresholds improved significantly between displays with peak luminance from 100 cd∕m(2) to 200 cd∕m(2), but improvement beyond that was not statistically significant for contrast detection thresholds in a reading room environment. Applying a calibration correction at high ambience (435 lx) improved detection tasks primarily in the darker background regions.

Artifacts in digital radiography.

OBJECTIVE: The purpose of this article is to discuss flat-panel digital radiography (DR) artifacts to help physicists, radiologists, and radiologic technologists visually familiarize themselves with an expanded range of artifact appearance. CONCLUSION: Flat-panel DR is a growing area of general radiography. As a radiology community, we are still becoming familiar with these systems and learning about clinically relevant artifacts and how to avoid them. These artifacts highlight important limitations or potential complications in using flat-panel DR systems.

Dose reduction in helical CT: dynamically adjustable z-axis X-ray beam collimation.

OBJECTIVE: The purpose of this study was to measure the dose reduction achieved with dynamically adjustable z-axis collimation. MATERIALS AND METHODS: A commercial CT system was used to acquire CT scans with and without dynamic z-axis collimation. Dose reduction was measured as a function of pitch, scan length, and position for total incident radiation in air at isocenter, accumulated dose to the center of the scan volume, and accumulated dose to a point at varying distances from a scan volume of fixed length. Image noise was measured at the beginning and center of the scan. RESULTS: The reduction in total incident radiation in air at isocenter varied between 27% and 3% (pitch, 0.5) and 46% and 8% (pitch, 1.5) for scan lengths of 20 and 500 mm, respectively. Reductions in accumulated dose to the center of the scan were 15% and 29% for pitches of 0.5 and 1.5 for 20-mm scans. For scan lengths greater than 300 mm, dose savings were less than 3% for all pitches. Dose reductions 80 mm or farther from a 100-mm scan range were 15% and 40% for pitches of 0.5 and 1.5. With dynamic z-axis collimation, noise at the extremes of a helical scan was unchanged relative to noise at the center. Estimated reductions in effective dose were 16% (0.4 mSv) for the head, 10% (0.8 and 1.4 mSv) for the chest and liver, 6% (0.8 mSv) for the abdomen and pelvis, and 4% (0.4 mSv) and 55% (1.0 mSv) for coronary CT angiography at pitches of 0.2 and 3.4. CONCLUSION: Use of dynamic z-axis collimation reduces dose in helical CT by minimizing overscanning. Percentage dose reductions are larger for shorter scan lengths and greater pitch values.