Swedish radiation oncology firm Elekta of Stockholm will introduce its new Elekta Infinity digital linear accelerator at next week's annual meeting of the American Society for Therapeutic Radiology and Oncology (ASTRO) in Boston.
Elekta Infinity is designed to increase speed and precision in delivering volumetric modulated arc therapy (VMAT) with reduced treatment times.
Elekta also will show its upgraded Mosaiq 2.0 software, with oncology charting to track patients from the moment they enter a cancer center through long-term follow-up.
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Elekta receives FDA nod, June 17, 2008
Elekta launches virtual clinic, June 13, 2008
Elekta wins Louisiana radiotherapy contract, June 5, 2008
Elekta receives Australian order, May 2, 2008
Elekta readies first order for New Zealand, April 25, 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)
