A computer virus penetrated the security firewalls of the healthcare IT networks of three hospitals in London last week, forcing their shutdown for a 24-hour period.
The hospitals affected were St. Bartholomew's Hospital, the Royal London Hospital, and the London Chest Hospital, all of which are part of the Barts and The London NHS Trust hospital system.
A press release issued by the Trust stated that emergency procedures were activated to ensure that key clinical systems continued. Ambulances were diverted to neighboring hospitals and admittance to the emergency department was restricted to ambulatory patients only. Lab testing and diagnostic imaging services remained available, according to Julian Nettel, chief executive officer of the Trust.
The system was restored to normal operation on Wednesday, November 19. The virus was believed to be the Mytob worm, which spreads via e-mail and plants a backdoor Trojan on infected computers that can be used to remotely take control of the machine, according to Graham Cluley, senior technology consultant at Sophos, a global security firm with headquarters in Oxford, U.K., and Boston.
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Intrusion-detection testing finds network vulnerabilities, August 11, 2008
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![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)
