Dear AuntMinnieEurope Member,
It's time to start getting tough and refusing requests for unnecessary scans. So says Dr. Paul McCoubrie, who thinks more hospitals should consider not offering CT of the abdomen for unprovoked venous thromboembolism and knee MRIs in patients over 50 years of age, for example.
Make decisions based on clinical need rather than clinical demand, he urges. Go to our MRI Community, or click here.
ECR 2018 drew to a close on Sunday, and the well-organized congress hosted by the Germans, Swiss, and Chinese is likely to be a very tough act to follow. The new president of the European Society of Radiology, Dr. Lorenzo Derchi from Genoa, Italy, is relishing the prospect, and he has given a substantial interview with Julia Patuzzi about his priorities and plans for ECR 2019. In addition to Italy, Pakistan and the continent of Africa will be the hosts. Read more here, and make sure you add the dates to your diary.
Toward the end of ECR 2018, another group of Italian researchers from Candiolo, near Turin, presented their work on a breast MRI protocol that they believe is more accurate than what's currently being used. Also, leading breast MRI pioneer Dr. Christiane Kuhl from Aachen, Germany, asserted that the principles of evidence-based medicine have been "misused" in the case of preoperative breast MRI.
For the first time at ECR, we produced four Facebook Live videos onsite in Vienna, in which our five-strong editorial team gave some impressions of the meeting. The fourth video was about women's imaging, and you can view it here. You can view the other videos and all of our coverage from ECR 2018 in our RADCast @ ECR special section.
Meanwhile, don't miss our challenging, interactive Case of the Week about an 80-year-old woman who presents for resection of a long-standing transosseous mass of the right frontal bone. The patient has no history of malignancy. Test yourself here. And check out our archive here for our full list of cases since our site first launched at ECR 2011.
Finally, make sure you log back on to our home page later tomorrow for the publication of our top 5 trends from ECR 2018.
![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
