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Aim: To compare digital breast tomosynthesis (DBT) and ultrasound in women recalled for assessment after a positive screening mammogram and assess the potential for each of these tools to reduce unnecessary biopsies. Methods: This data linkage study included 538 women recalled for assessment from January 2017 to December 2019. The association between the recalled mammographic abnormalities and breast density was analysed using the chi-square independence test. Relative risks and the number of recalled cases requiring DBT and ultrasound assessment to prevent one unnecessary biopsy were compared using the McNemar test. Results: Breast density significantly influenced recall decisions (p < 0.001). Ultrasound showed greater potential to decrease unnecessary biopsies than DBT: in entirely fatty (21% vs. 5%; p = 0.04); scattered fibroglandular (23% vs. 10%; p = 0.003); heterogeneously dense (34% vs. 7%; p < 0.001) and extremely dense (39% vs. 9%; p < 0.001) breasts. The number of benign cases needing assessment to prevent one unnecessary biopsy was significantly lower with ultrasound than DBT in heterogeneously dense (1.8 vs. 7; p < 0.001) and extremely dense (1.9 vs. 5.1; p = 0.03) breasts. Conclusion: Women with dense breasts are more likely to be recalled for assessment and have a false-positive biopsy. Women with dense breasts benefit more from ultrasound assessment than from DBT.

Abstract Background Opinions seem somewhat divided when considering the effect of artificial intelligence (AI) on medical imaging. The aim of this study was to characterise viewpoints presented online relating to the impact of AI on the field of radiology and to assess who is engaging in this discourse. Methods Two search methods were used to identify online information relating to AI and radiology. Firstly, 34 terms were searched using Google and the first two pages of results for each term were evaluated. Secondly, a Rich Search Site (RSS) feed evaluated incidental information over 3 weeks. Webpages were evaluated and categorized as having a positive, negative, balanced, or neutral viewpoint based on study criteria. Results Of the 680 webpages identified using the Google search engine, 248 were deemed relevant and accessible. 43.2% had a positive viewpoint, 38.3% a balanced viewpoint, 15.3% a neutral viewpoint, and 3.2% a negative viewpoint. Peer-reviewed journals represented the most common webpage source (48%), followed by media (29%), commercial sources (12%), and educational sources (8%). Commercial webpages had the highest proportion of positive viewpoints (66%). Radiologists were identified as the most common author group (38.9%). The RSS feed identified 177 posts of which were relevant and accessible. 86% of posts were of media origin expressing positive viewpoints (64%). Conclusion The overall opinion of the impact of AI on radiology presented online is a positive one. Consistency across a range of sources and author groups exists. Radiologists were significant contributors to this online discussion and the results may impact future recruitment.

Abstract Background There exists a significant divide between what is learnt in medical school and subsequently what is required to practice medicine effectively. Despite multiple strategies to remedy this discordance, the problem persists. Here, we describe the identification of a comprehensive set of learning outcomes for a preparation for practice course in radiology. Methods Assessment of interns’ readiness to interact with the radiology department was conducted using a national survey of both interns and radiologists. In parallel, group concept mapping (GCM) which involves a combination of qualitative and quantitative techniques was used to identify the shared understanding of participants from a diverse range of medical specialties regarding what topics should be included in an intern preparatory course for interacting with the radiology department. Results The survey demonstrated that most interns and radiologists felt that undergraduate medical training did not prepare interns to interact with the radiology department. GCM identified six learning outcomes that should be targeted when designing a preparatory module: requesting investigations; clinical decision support; radiology department IT and communication; adverse reactions and risks; interpretation of radiology results and urgent imaging. The thematic clusters from the group concept mapping corroborated the deficiencies identified in the national survey. Conclusion We have identified six key learning outcomes that should be included in a preparation for practice module in radiology. Future courses targeting these thematic clusters may facilitate a smoother transition from theory to practice for newly graduated doctors.

This study aimed to systematically review the literature to synthesise and summarise the evidence surrounding the efficacy of artificial intelligence (AI) in classifying paediatric pneumonia on chest radiographs (CXRs). Following the initial search of studies that matched the pre-set criteria, their data were extracted using a data extraction tool, and the included studies were assessed via critical appraisal tools and risk of bias. Results were accumulated, and outcome measures analysed included sensitivity, specificity, accuracy, and area under the curve (AUC). Five studies met the inclusion criteria. The highest sensitivity was by an ensemble AI algorithm (96.3%). DenseNet201 obtained the highest level of specificity and accuracy (94%, 95%). The most outstanding AUC value was achieved by the VGG16 algorithm (96.2%). Some of the AI models achieved close to 100% diagnostic accuracy. To assess the efficacy of AI in a clinical setting, these AI models should be compared to that of radiologists. The included and evaluated AI algorithms showed promising results. These algorithms can potentially ease and speed up diagnosis once the studies are replicated and their performances are assessed in clinical settings, potentially saving millions of lives.

Background: To compare the diagnostic efficacy of digital breast tomosynthesis (DBT) and ultrasound across breast densities in women recalled for assessment. Methods: A total of 482 women recalled for assessment from January 2017 to December 2019 were selected for the study. Women met the inclusion criteria if they had undergone DBT, ultrasound and had confirmed biopsy results. We calculated sensitivity, specificity, PPV, and AUC for DBT and ultrasound. Results: In dense breasts, DBT showed significantly higher sensitivity than ultrasound (98.2% vs. 80%; p < 0.001), but lower specificity (15.4% vs. 55%; p < 0.001), PPV (61.3% vs. 71%; p = 0.04) and AUC (0.568 vs. 0.671; p = 0.001). In non-dense breasts, DBT showed significantly higher sensitivity than ultrasound (99.2% vs. 84%; p < 0.001), but no differences in specificity (22% vs. 33%; p = 0.14), PPV (69.2% vs. 68.8%; p = 0.93) or AUC (0.606 vs. 0.583; p = 0.57). Around 73% (74% dense and 71% non-dense) and 77% (81% dense and 72% non-dense) of lesions assigned a RANZCR 3 by DBT and ultrasound, respectively, were benign. Conclusion: DBT has higher sensitivity, but lower specificity and PPV than ultrasound in women with dense breasts recalled for assessment. Most lesions rated RANZCR 3 on DBT and ultrasound are benign and may benefit from short interval follow-up rather than biopsy.

Educating students to become evidence-based practitioners remains a significant challenge in health professional education. Clinical placements form a significant element of curriculum, and the impact of students' work integrated learning experiences on their ability and desire to practice in an evidence-based manner remains largely unexplored. This study used focus groups to explore students' experiences of evidence-based practice (EBP) during clinical placements, the impact of these experiences on their education, and their future EBP tendencies within the profession. Reflexive thematic analysis was utilized to analyze data and three main overarching themes were identified. These themes are education, culture and responsibility and hopes, fears and barriers and they were explored in detail. Improving the teaching of EBP skills within health professional education, which includes the strengthening of the integration of these skills across work-integrated learning curricula, has the potential to enhance the translation of knowledge into practice as these graduates become qualified clinicians within the profession.