Faculty Bibliography

Quantitative imaging (QI) is increasingly applied in modern radiology practice, assisting in the clinical assessment of many patients and providing a source of biomarkers for a spectrum of diseases. QI is commonly used to inform patient diagnosis or prognosis, determine the choice of therapy, or monitor therapy response. Because most radiologists will likely implement some QI tools to meet the patient care needs of their referring clinicians, it is important for all radiologists to become familiar with the strengths and limitations of QI. The Association of University Radiologists Radiology Research Alliance Quantitative Imaging Task Force has explored the clinical application of QI and summarizes its work in this review. We provide an overview of the clinical use of QI by discussing QI tools that are currently used in clinical practice, clinical applications of these tools, approaches to reporting of QI, and challenges to implementing QI. It is hoped that these insights will help radiologists recognize the tangible benefits of QI to their patients, their referring clinicians, and their own radiology practice.

PURPOSE: To evaluate sustainability of impact of rapid, focused process improvement (PI) events on process and performance within an academic radiology department. METHODS: Our department conducted PI during 2011 and 2012 in CT, MRI, ultrasound, breast imaging, and research billing. PI entailed participation by all stakeholders, facilitation by the department chair, collection of baseline data, meetings during several weeks, definition of performance metrics, creation of an improvement plan, and prompt implementation. We explore common themes among PI events regarding initial impact and durability of changes. We also assess performance in each area pre-PI, immediately post-PI, and at the time of the current study. RESULTS: All PI events achieved an immediate improvement in performance metrics, often entailing both examination volumes and on-time performance. IT-based solutions, process standardization, and redefinition of staff responsibilities were often central in these changes, and participants consistently expressed improved internal leadership and problem-solving ability. Major environmental changes commonly occurred after PI, including a natural disaster with equipment loss, a change in location or services offered, and new enterprise-wide electronic medical record system incorporating new billing and radiology informatics systems, requiring flexibility in the PI implementation plan. Only one PI team conducted regular post-PI follow-up meetings. Sustained improvement was frequently, but not universally, observed: in the long-term following initial PI, measures of examination volume showed continued progressive improvements, whereas measures of operational efficiency remained stable or occasionally declined. CONCLUSIONS: Focused PI is generally effective in achieving performance improvement, although a changing environment influences the sustainability of impact. Thus, continued process evaluation and ongoing workflow modifications are warranted.

Academic radiology is poised to play an important role in the development and implementation of quantitative imaging (QI) tools. This article, drafted by the Association of University Radiologists Radiology Research Alliance Quantitative Imaging Task Force, reviews current issues in QI biomarker research. We discuss motivations for advancing QI, define key terms, present a framework for QI biomarker research, and outline challenges in QI biomarker development. We conclude by describing where QI research and development is currently taking place and discussing the paramount role of academic radiology in this rapidly evolving field.

OBJECTIVE. The purpose of this study was to assess perspectives and information relating to CT radiation risk on Twitter, a popular microblogging social network. MATERIALS AND METHODS. Publicly available posts on Twitter ("tweets") containing both the words "CT" and "radiation" were identified from the 1st week of each month in 2013. Type of user posting and source of linked articles were recorded. Two reviewers assessed the content of tweets and links regarding CT's benefit-to-risk ratio (favorable, unfavorable, etc.). RESULTS. Six hundred twenty-one relevant tweets were tweeted by 557 unique users, of whom 90 (16%) were physicians (17 of these were radiologists), 30 (5%) were medical practices or hospitals, 34 (6%) were patients, 8 (1%) were physicists or technologists, and 395 (71%) were other types of users. Two hundred twenty-seven tweets included user commentary regarding CT's benefit-to-risk ratio, of which 134 (59%) were unfavorable or concerned, 65 (29%) were neutral, 22 (10%) were informative regarding CT dose reduction strategies, and only 6 (3%) were favorable. Four hundred seventy-two tweets (76%) included links to a total of 99 unique articles, of which 25 (25%) were unfavorable or concerned, 10 (10%) were favorable, 25 (25%) were neutral, and 39 (39%) were informative regarding CT dose reduction. Article types were non-peer-reviewed medical sources (n = 50), lay press (n = 15), peer-reviewed medical journals (n = 13), blogs (n = 12), advertisements (n = 5), and informational websites (n = 4). CONCLUSION. The large majority of content on Twitter was either unfavorable or concerned regarding CT radiation risk. Most articles were not peer-reviewed and were posted by nonphysicians; posts by physicians were largely by nonradiologists. More active engagement on Twitter by radiologists and physicists and increased dissemination of peer-reviewed articles may achieve a more balanced representation and alleviate concerns regarding CT radiation risk on social networks.