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.

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.

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.