Comparison of image acquisition and radiologist interpretation times in a diagnostic mammography center

Leveling the Workload for Radiologists in Diagnostic Mammography: Application of Lean Principles and Heijunka

To facilitate the delivery of accurate and timely care to patients in complex environments, process improvement methodologies such as Lean can be very effective. Lean is a quality improvement methodology that seeks to add value for patients and employees by continuously improving processes and eliminating waste. At our institution, Lean principles were applied to improve efficiency and minimize waste in the diagnostic breast imaging reading room. This paper describes how we applied Lean principles, including plan-do-study-act testing, level-loading (heijunka), and visual management, to level the workload of the diagnostic radiologists in our practice. Implementation of these principles to improve the diagnostic workflow in breast imaging is described along with examples from our practice, including challenges and future opportunities.

Comparable prediction of breast cancer risk from a glimpse or a first impression of a mammogram

Expert radiologists can discern normal from abnormal mammograms with above-chance accuracy after brief (e.g. 500 ms) exposure. They can even predict cancer risk viewing currently normal images (priors) from women who will later develop cancer. This involves a rapid, global, non-selective process called “gist extraction”. It is not yet known whether prolonged exposure can strengthen the gist signal, or if it is available solely in the early exposure. This is of particular interest for the priors that do not contain any localizable signal of abnormality. The current study compared performance with brief (500 ms) or unlimited exposure for four types of mammograms (normal, abnormal, contralateral, priors). Groups of expert radiologists and untrained observers were tested. As expected, radiologists outperformed naïve participants. Replicating prior work, they exceeded chance performance though the gist signal was weak. However, we found no consistent performance differences in radiologists or naïves between timing conditions. Exposure time neither increased nor decreased ability to identify the gist of abnormality or predict cancer risk. If gist signals are to have a place in cancer risk assessments, more efforts should be made to strengthen the signal.

Improved Screening Mammogram Workflow by Maximizing PACS Streamlining Capabilities in an Academic Breast Center

The aim of this study was to perform an operational improvement project targeted at the breast imaging reading workflow of mammography examinations at an academic medical center with its associated breast centers and satellite sites. Through careful analysis of the current workflow, two major issues were identified: stockpiling of paperwork and multiple worklists. Both issues were considered to cause significant delays to the start of interpreting screening mammograms. Four workflow changes were suggested (scanning of paperwork, worklist consolidation, use of chat functionality, and tracking of case distribution among trainees) and implemented in July 2015. Timestamp data was collected 2 months before (May-Jun) and after (Aug-Sep) the implemented changes. Generalized linear models were used to analyze the data. The results showed significant improvements for the interpretation of screening mammograms. The average time elapsed for time to open a case reduced from 70 to 28 min (60 % decrease, p < 0.001), report turn-around time with preliminary signature decreased from 151 to 107 min (29 % decrease, p < 0.001), and report turn-around time final signature from 153 to 139 min (9 % decrease, p = 0.002). These improvements were achieved while keeping the efficiency of the workflow for diagnostic mammograms at large unaltered even with increased volume of mammography examinations (31 % increase of 4344 examinations for May-Jun to 5678 examinations for Aug-Sep). In conclusion, targeted efforts to improve the breast imaging reading workflow for screening mammograms in a teaching environment provided significant performance improvements without affecting the workflow of diagnostic mammograms.

Detecting Breast Cancer with a Dual-Modality Device

Although mammography has been the gold standard for the early detection of breast cancer, if a woman has dense breast tissue, a false negative diagnosis may occur. Breast ultrasound, whether hand-held or automated, is a useful adjunct to mammography but adds extra time and cost. The primary aim was to demonstrate that our second-generation Aceso system, which combines full-field digital mammography (FFDM) and automated breast ultrasound (ABUS) in a single platform, is able to produce improved quality images that provide clinically meaningful results. Aceso was first tested using two industry standards: a Contrast Detail Mammography (CDMAM) phantom to assess the FFDM images, and the CIRS 054GS phantom to evaluate the ABUS images. In addition, 25 women participated in a clinical trial: 14 were healthy volunteers, while 11 were patients referred by the breast clinic at Groote Schuur Hospital. The CDMAM phantom results showed the FFDM results were better than the European Reference (EUREF) standard of "acceptable" and were approaching "achievable". The ABUS results showed a lateral and axial spatial resolution of 0.5 mm and an adequate depth penetration of 80 mm. Our second-generation Aceso system, with its improved quality of clinical FFDM and ABUS images, has demonstrated its potential for the early detection of breast cancer in a busy clinic.

Overview of the radiographers' practice in 65 healthcare centers using digital mammography systems in Portugal

PURPOSE

To assess current practices in digital mammography (DM) in Portuguese healthcare providers using digital systems. To investigate compliance with European standards regarding mean glandular dose and quality control practice and to identify optimisation needs.

METHODS

Two questionnaires, targeted at breast radiographers and chief radiographers, were designed and applied in 65 imaging departments offering DM. Questions fielded were focused on the staff profile and technical/clinical practice.

RESULTS

Prior to starting their activity in DM, 70% (82 out of 118) of the respondents received training in DM. The practice in 29 out of 59 providers was established by the manufacturers' recommendations for image acquisition. Variations were observed between radiographers who belong to the same provider namely the selection of exposure parameters such as the target-filter combination and automatic mode. The use of the manual exposure mode was reported for imaging breast implants (44%) and surgical specimens (22%). The main causes of repeat examinations were skin folding (21%) and absence of pectoral muscle (PM) (20%).

CONCLUSIONS

The study revealed opportunities to optimise radiographers' practice in DM regarding the selection of exposure parameters. A robust and consistent training programme in DM and established local protocols can help to reduce the variations observed and improve clinical practice.

MAIN MESSAGES

• Radiographers adopted different practices selecting AEC modes and T/F combinations. • Radiographer practice is more consistent using DR than using CR systems. • The main causes for rejecting images were the visibility of skin folding and PM absence. • Radiographers were partly unaware of the dose indicator. • Radiographers' training needs: QC, interventional procedures and breast dose optimisation.

Utility of adaptive control processing for the interpretation of digital mammograms

Background Adaptive control processing for mammography (ACM) is a novel program that automatically sets up appropriate image-processing parameters for individual mammograms (MMGs) by analyzing the focal and whole breast histogram. Purpose To investigate whether ACM improves the image contrast of digital MMGs and whether it improves radiologists' diagnostic performance in reading of MMGs. Material and Methods One hundred normal cases for image quality assessment and another 100 cases (50 normal and 50 cancers) for observer performance assessment were enrolled. All mammograms were examined with and without ACM. Five radiologists assessed the intra- and extra-mammary contrast of 100 normal MMGs, and the mean scores of the intra- and extra-mammary contrast were compared between MMGs with and without ACM in both the dense and non-dense group. They classified 100 MMGs into BI-RADS categories 1-5, and were asked to rate the images on a scale of 0 to 100 for the likelihood of the presence of category 3-5 lesions in each breast. Detectability of breast cancer, reading time, and frequency of window adjustment were compared between MMGs with and without ACM. Results ACM improved the intra-mammary contrast in both the dense and non-dense group but degraded extra-mammary contrast in the dense group. There was no significant difference in detectability of breast cancer between MMGs with and without ACM. Frequency of window adjustment without ACM was significantly higher than that with ACM. Reading time without ACM was significantly longer than that with ACM. Conclusion ACM improves the image contrast of MMGs and shortens reading time.