Radiology and Social Media: Are Private Practice Radiology Groups More Social Than Academic Radiology Departments?

PurposeThis study assesses the prevalence of use of the most commonly used social media sites among private radiology groups (PRGs) and academic radiology departments (ARDs).MethodsThe 50 largest PRGs and the 50 ARDs with the highest level of funding from the National Institutes of Health were assessed for presence of a radiology-specific social media account on Facebook, Twitter, Instagram, Pinterest, YouTube, and LinkedIn. Measures of organizational activity and end-user activity were collected, including the number of posts and followers, as appropriate; between-group comparisons were performed.ResultsPRGs adopted Facebook 12 months earlier (P = .02) and Twitter 18 months earlier (P = .02) than did ARDs. A total of 76% of PRGs maintained ≥1 account on the social media sites included in the study, compared with 28% of ARDs (P < .0001). The prevalence of having an account on the social media sites for PRGs was: Facebook, 66%; LinkedIn, 56%; Twitter, 42%; YouTube, 20%; Pinterest, 4%; and Instagram, 2%. The prevalence of radiology-specific social media accounts for ARDs was: Facebook, 18%; LinkedIn, 0%; Twitter, 24%; YouTube, 6%; Pinterest, 0%; and Instagram, 0%. There was no significant difference between ARDs and PRGs in measures of end-user or organizational activity on Facebook or Twitter.ConclusionsUse of social media in health care is emerging as mainstream, with PRGs being early adopters of Facebook and Twitter in comparison with ARDs. Competitive environments and institutional policies may be strong factors that influence how social media is used by radiologists at the group and department levels.     

Self-citation: comparison between Radiología, European Radiology and Radiology for 1997–1998

Self-citation, considered as the number of times a paper cites other papers in the same journal, is an important criteria of journal quality. Our objective is to evaluate the self-citation in the official journal of the Spanish Society of Radiology (Radiología), and to compare it with the European Radiology and Radiology journals. Papers published in Radiología, European Radiology, and Radiology during 1997 and 1998 were analyzed. The Self Citation Index, considered as the ratio between self-references and total number of references per article, for the journals Radiología (SCIR), European Radiology (SCIER), and Radiology (SCIRY), were obtained and expressed as percentages. Also, the number of references to Radiología in European Radiology and Radiology papers were calculated. Stratification of the index per thematic area and article type was also performed. Mean SCIR, SCIER, and SCIRY values were compared with the ANOVA and the Student-Newman-Keuls tests. The self-citation index was statistically higher in Radiology (23.2%; p<0.0001) than in Radiología (1.8%) and European Radiology (0.8%). There were no statistically significant differences between SCIR and SCIER indexes ( p=0.25). In the stratification per thematic areas and article type, self-citation in Radiology was statistically higher ( p<0.0001), with the only exception of "Radioprotection" area ( p=0.2), to SCIR and SCIER. Although there were no statistically significant differences, by thematic areas SCIR was always larger than SCIER, with the only exception of the "Genitourinary imaging" area, and by article type SCIR also went greater to SCIER, except in review articles. Radiología, The Spanish official radiological journal, although not included in Index Medicus and its database Medline, had a larger number of self-citing than European Radiology in the period 1997-1998.     

Online Hide and Seek: Allopathic US Medical Schools’ Radiology Education Virtual Presence

Rationale and ObjectivesTo highlight radiology's merits and boost appeal to medical students in the digital era, it is increasingly important for radiology departments to be readily accessible to medical students. We report the results of a multivariate analysis of the virtual presence of radiology medical student education of 152 allopathic United States (US) medical schools, the first report of its kind to the authors’ knowledge. We detail eight elements to include when optimizing a radiology medical student education website.MethodsIn August 2020, the Department of Radiology websites at 152 allopathic US medical schools were assessed for the presence of a medical student radiology education website and accessibility of collated information about preclinical and clinical course offerings, radiology interest groups, and outreach initiatives in the form of student radiology mentorship, shadowing, and research opportunities.Results65.1% (99/152) of allopathic US medical schools’ radiology departments have a dedicated medical student radiology education website, one of which was excluded from further review due to password protected content. 58.2% (57/98) of departmental websites include information about preclinical radiology coursework and 90.8% (89/98) of departments provide information about clinical courses. Details about interest groups were found on 26.5% (26/98) of departmental websites. Information about mentorship and shadowing was identified on less than half of departmental websites. 51% (50/98) of Department of Radiology websites provide information about research opportunities for students.ConclusionsThis study demonstrates that the majority of allopathic US medical schools’ radiology departments lack full information of relevance to medical students. To engage today's and tomorrow's medical learners digitally, there is opportunity and need to improve the online availability of information about preclinical and clinical radiology courses, student interest groups, shadowing opportunities, student mentorship, and student research. We detail eight elements to include when optimizing a radiology medical student education website. In most instances, this can be accomplished by revising an existing radiology department website in a manner that engages, educates, and recruits medical students. As a specialty, radiology must expand our digital footprint to reach tomorrow's colleagues and leaders.     

Summary of Journal of Interventional Radiology

T. Livraghi, S. Lazzaroni*, L. Civelli, M. Marks, F. Meloni, C. VettoriDivisione di Radiologia, Ospedale Civile, Mercate. Milano and * Divisione di Medicina, Ospedale S.Biagio Bergamo. Italy     

Strategic Talent Management: Implementation and Impact of a Leadership Development Program in Radiology

The rapidity of change and increasing complexity of the academic medical center environment require a talented and engaged workforce with competencies in adaptability, capacity for working in empowered and diverse interprofessional teams, and self-efficacy. Radiology—a crosscutting field that interfaces with most other biomedical disciplines and that is often at the forefront of technological disruption—is a potentially ideal venue to focus professional and leadership development to create positive organizational value. In this report, we detail the design of and 9-year experience with a departmental leadership academy at a large academic center intended to foster team-based skills in early to midcareer faculty and staff. Over the past decade, 100 participants have completed the program with 80% retention, substantial professional growth, and increased capacity for mentoring others. This in-house, customized leadership development program is aligned with our strategic and cultural imperative to promote nimble, engaged, and empowered teams in a diverse and inclusive setting.     

The Policy of Co–First Authorship and Co–Senior Authorship in Radiology Journals

ObjectiveIncreasingly, medical journals are recognizing “equally credited authors” (ECA) in the primary and senior authorship of articles. The aim of this study was to assess the policies of co–first authorship, co–senior authorship, and designation of a corresponding author in the radiology literature.MethodsWe identified 29 radiology journals based on impact factor ranking. Journal offices were contacted by phone and e-mail to ascertain their practices on first and senior authorship ECA designations. We surveyed the March, June, and December 2018 issues of each journal (when available) to assess the utilization of the co-designations in articles.ResultsTwenty-five of 29 journals responded to our survey (response rate: 86.2%). Of 25 journals, 20 (80%) allowed co–first authorship. Among these, 4 of 25 journals (16%) allowed more than two co–first authors. Among the 25 responses, 14 journals (56%) allowed co–senior authorship. Among the 24 journals who responded to this specific question, 23 (96%) approved designation of a corresponding author, different from the first or senior author. The review of March, June, December 2018 editions found co–first authorship and co–senior authorship ECA rates of 8.6% (range 0.0%-22.7%) and 1.8% (range 0.0%-13.3%), respectively. A corresponding author other than first or senior author was noted in 13.3% (range 0.0%-34.7%).DiscussionThere has been widespread acceptance of the concept of ECA in the policies of the top cited imaging journals particularly for first authors (80%). However, the utilization of these designations is uncommon for first authorship (8.6%) and rare (1.8%) for senior authorship based on our 2018 sampling.     

Natural Language Processing of Radiology Reports in Patients With Hepatocellular Carcinoma to Predict Radiology Resource Utilization

ObjectiveRadiology is a finite health care resource in high demand at most health centers. However, anticipating fluctuations in demand is a challenge because of the inherent uncertainty in disease prognosis. The aim of this study was to explore the potential of natural language processing (NLP) to predict downstream radiology resource utilization in patients undergoing surveillance for hepatocellular carcinoma (HCC).Materials and MethodsAll HCC surveillance CT examinations performed at our institution from January 1, 2010, to October 31, 2017 were selected from our departmental radiology information system. We used open source NLP and machine learning software to parse radiology report text into bag-of-words and term frequency–inverse document frequency (TF-IDF) representations. Three machine learning models—logistic regression, support vector machine (SVM), and random forest—were used to predict future utilization of radiology department resources. A test data set was used to calculate accuracy, sensitivity, and specificity in addition to the area under the curve (AUC).ResultsAs a group, the bag-of-word models were slightly inferior to the TF-IDF feature extraction approach. The TF-IDF + SVM model outperformed all other models with an accuracy of 92%, a sensitivity of 83%, and a specificity of 96%, with an AUC of 0.971.ConclusionsNLP-based models can accurately predict downstream radiology resource utilization from narrative HCC surveillance reports and has potential for translation to health care management where it may improve decision making, reduce costs, and broaden access to care.     

放射学多选题(MCQ in Radiology)

由A.H.Chapman P.J.Robinson编著的MCQs in Radiology (放射学多选题)已于1988年第6期刊登完毕。自本期起又连载由P.R.Patel编著,孔庆德教授译的《放射学多选题》。这本《放射学多选题》有200道,预计1989年可刊登完毕。这两本多选题内容丰富,立意新颖,不仅能诱导读者思考问题,而且能激发读者的学习兴趣,自1986年第4期连载以来,深受广大读者欢迎。为应广大读者要求,本刊拟将这两本多选题编译成册,以便读者携带和阅读。此事可望1989年年底完成,欲购者请注意本刊《书讯》。