The countdown for the 25^th ECR in Vienna has started! Find out what ECR 2019 has in store for its participants!

• A new and magnificent format for the opening ceremony: Grand Opening – Five Senses.
• Cube 2.0, the ECR's area for interventional radiology, will offer more than twice the space compared with last year.
• Women in Focus, a new event dedicated to women in radiology and healthcare.
• The return of the Coffee & Talk sessions and the My Thesis in 3 Minutes presentations, after their successful debut last year.
• The Voice of EPOS™ will again offer a platform for poster authors to present their work in a moderated poster session. This year there will be more stages and more sessions than ever before!

Check out the ECR 2019 Interactive Programme Planner to find out more about this year's highlights and to create your personal congress schedule!

Meet with the ESR iGuide team to discover how clinical decision support using the ESR's guidelines can help make imaging referrals more appropriate! Visit the ESR iGuide booth, located within the EuroSafe Imaging Lounge (1st floor ACV), or schedule a demonstration at ECR 2019 here.

EuroSafe Imaging will celebrate 5 years of success in medical radiation protection at the forthcoming ECR 2019. Join our celebration and visit the EuroSafe Imaging Lounge (1st floor ACV), which will feature a café, photo booth, and a stand providing information on patient safety topics. You can also attend one of the dedicated scientific sessions or Coffee & Talk sessions; or check out the electronic poster exhibition, which has contributions from experts around the world.

Find out what EuroSafe Imaging has in store for you at ECR 2019 here.

This dramatic increase of 34% compared to last year’s figure of 75,502 members has been a goal of the society throughout 2018, and it is proud to have accomplished it right at the very the end of 2018.  

Read all about this stunning success. 

Application for or renewal of ESR Membership for 2019 is open until August 31, 2019.

Benefits include reduced congress registration fees for ECR 2019, coverage of Article Processing Charges for accepted articles in Insights into Imaging and European Radiology Experimental, free electronic access to European Radiology, Europe’s no. 1 general radiological journal, and more. Check out all the benefits here.

European Radiology Experimental provides a forum for basic scientific discoveries, novel approaches and techniques in experimental settings. Read all its articles here and submit yours here!

Don’t forget that for ESR Members, Article Processing Charges for accepted articles in Insights into Imaging and European Radiology Experimental are covered.

EuroSafe Imaging is pleased to announce a new free webinar organised together with the IAEA Radiation Protection of Patients (RPOP) Unit, scheduled for January 24, 2019, at 15:00 (CET). Prof. Guy Frija, Chair of EuroSafe Imaging, will explain why justification and guidelines are key to radiation protection in medical imaging. Don't miss this opportunity!

Register here.

Two more examination dates have been added to the EDiR calendar! The examinations will be taking place on June 19 in Istanbul, Turkey; and July 2 and 3 in Barcelona, Spain! Online application will open on the EBR website on January 28.

ESR Corresponding Members who apply before March 10 will benefit from a special early bird fee. Further details are available here. 

Special offers apply for Hospitals and Heads of Departments wishing to register their last year residents. For further information, please contact us via email.

Artificial intelligence (AI) has quickly become the number one topic of conversation amongst radiologists due to its potential to revolutionise the way we work in the twenty-first century. This study gives a quick overview of the impact AI has had so far in the world of radiology and tries to predict the future of its development and use. (Eur Radiol)

In the recent years, radiology has changed greatly due to the influence of digitalization. The already important part of clinical decision-making process has gained even more credit and opened new opportunities for synergy between physicians and computer networks —via computer-aided diagnosis (CAD), computer-aided prediction of response (CARP), and computer-aided biological profiling (CABP). Therefore, the authors of this article argue that radiomics is a critical step in the future of medical imaging. (Insights Imaging)

The applications of artificial intelligence and machine learning in radiology are currently on a rise. To make the best use of these systems, well-organized and accessible data is required. That is why the goal of this review was to give a brief overview on how structured reporting can help to facilitate research in artificial intelligence and the context of big data. (Eur Radiol Exp)

This study was constructed to compare the efficacy of magnetic resonance imaging (MRI) with extracellular contrast agents (ECA‐MRI) and MRI with hepatobiliary agents (HBA‐MRI) for the diagnosis of hepatocellular carcinoma (HCC) using the Liver Imaging Reporting and Data System (LI‐RADS). The authors concluded that ECA‐MRI showed better sensitivity and accuracy than HBA‐MRI for the diagnosis of HCC with LI‐RADS. Furthermore, better diagnostic performance was achieved when applying a modified washout on PVP/TP HBA‐MRI and an illusional washout on ECA‐MRI than with conventional criteria. (Hepatology)

Previous studies have reported inconclusive findings on whether screening can detect small cell lung cancer (SCLC) at an earlier stage and whether there might be a survival benefit. The authors of this study set to examine the characteristics of SCLC that can be detected by using low-dose CT (LDCT) and to prove that early detection using LDCT imaging had no impact on SCLC outcomes. (Chest)

This study aimed to use deep convolutional neural network (DCNN) models to improve the diagnostic accuracy of thyroid cancer by analysing sonographic imaging data from clinical ultrasounds. In this retrospective, multicohort, diagnostic study, the authors developed and trained the DCNN model on the training set. Read more here. (Lancet Oncol)