Dear Imaging Informatics Insider,
Phone interruptions during reporting sessions are a constant challenge for radiologists. Electronic order systems should help reduce the number of calls, but the full benefits of these applications are not being realized, according to a survey presented at the recent U.K. Radiology Conference in Manchester. For the full details, click here.
In general, European radiologists have been reluctant Twitter users, but that needs to change, Dr. María Jesús Díaz Candamio and Dr. Erik Ranschaert write in a new column. The potential of Twitter as a source of global knowledge is huge, and broadening the horizons of radiological tweeters and connecting them with colleagues in other specialties and the general public, not only from the English-speaking world, are desirable, they believe. Click here to read more.
More attention must be given to improving image display and hanging protocols, noted Dr. Giles Maskell in an article about minimizing errors. Also, the use of structured or template reports may help by prompting radiologists to review areas or structures that they might otherwise overlook, he pointed out. To find out more, click here.
Three key priorities for France's national union of private radiologists include preservation of a national imaging network that promotes local care and services close to patients, encouragement and support for information sharing between the public and private imaging sector, and quality teleradiology based on the Teleradiology Charter. The group unveiled its plan of action on 29 June. Click here for the full story.
Finally, don't miss the second part of our special focus on home reporting. How can you plan and implement a service successfully? Learn more here.
This letter features only a few of the many articles posted over recent weeks in the Imaging Informatics Community -- you'll find many more stories by looking over the links below.
















![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&fit=crop&h=112&q=70&w=112)


