Radiation oncology firm Elekta of Stockholm has finalized plans to acquire radiation treatment planning firm CMS of St. Louis.
Elekta has signed a purchase agreement to acquire CMS for $75 million in cash. The transaction could close as soon as March.
CMS develops and markets advanced radiation therapy planning equipment, and supports more than 1,500 sites in clinical operation worldwide. There are eight clinical installations of its treatment planning for proton therapy devices, which feature the company's Mosaiq information management system.
In fiscal year 2007 (end-September 31), CMS reported orders worth $61 million.
Related Reading
Elekta lands Nebraska MEG installation, February 11, 2008
Elekta repurchases own shares, January 24, 2008
Elekta VMAT in use in Europe, January 18, 2008
Elekta moves to acquire planning firm CMS, January 8, 2008
CMS nets FDA OK for Monaco, October 16, 2007
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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&fit=crop&h=112&q=70&w=112)




