Magnetic field strength in MRI shot to prominence again in 2021. In AuntMinnieEurope.com's top 10 list published on 22 December, field strength features in three of the four most popular stories, based on reader page views.
Our top article is about the development and implementation of an 11.7-tesla scanner by Dr. Denis Le Bihan, PhD, and his colleagues in Paris. In a novel touch, the researchers produced images of a pumpkin that clearly captured your imagination in the run-up to Halloween.
Earlier in the year, the Maverinck wrote a strong and insightful viewpoint column about field strength that appears at No. 3 in our list. Also, the winner of the EuroMinnies 2021 best new radiology device was a 0.55-tesla scanner, underlining the rapid evolution of low-field systems during MRI's 50th anniversary year.
Arguably the biggest surprise in the lineup is our second most popular article, which is about Dr. Chinna Dua, a well-known Indian radiologist who died of COVID-19 in June. Her husband, Vinod Dua, a pioneer in broadcast Hindi journalism, died in early December 2021. Their daughter, Mallika Dua, is a famous actor and comedian.
Research that underlines the benefits of using advanced quantitative MRI to study the brains of patients recovering from long-COVID features at No. 6, while an article about the impact on the pandemic on U.K. radiology's crisis appears at No. 10.
Unsurprisingly, medicolegal topics remain important for you, as shown by the theme of our fifth most popular article: the outcome of a test case in Australia involving the death of a woman who had a "wellness scan."
The remaining top stories were about buttock fillers and injections, the cybersecurity attack on the Irish health service, and Dr. Christiane Kuhl's latest thoughts on breast MRI.
Below is the full top 10 list of articles on AuntMinnieEurope.com for 2021, as measured by member traffic. We hope you enjoyed reading these stories as much as we enjoyed bringing them to you. We very much look forward to providing you with further coverage in 2022.
Top 10 stories for 2021
- 11.7T MRI scanner produces 1st images in time for Halloween, 13 October
- Celebrity radiologist Chinna Dua, 61, has died of COVID-19, 15 June
- Smashing the magnetic field strength dogma in MRI, 16 February
- Dutch radiology comes out on top in 2021 EuroMinnies awards, 25 February
- Coroner gives verdict on patient death after 'wellness scan', 23 November
- MRI sheds new light on brain tissue changes in long-COVID cases, 1 June
- When buttock fillers and injections go wrong, 19 January
- Ransomware attack leaves Irish radiology reeling after IT shutdown, 17 May
- Kuhl provides master class on breast MRI at ECR 2021, 9 March
- U.K. radiology's looming crisis deepens in COVID-19 pandemic, 28 April
![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)
