Radiation oncology firm Nucletron of Veenendaal, Netherlands, enjoyed strong financial results over the first half of 2009.
Net sales amounted to $73.1 million (51.2 million euros), a 3% increase compared to the first half of 2008. Nucletron attributed the results in part to its collaboration with Advanced Radiation Therapy of Billerica, MA, and Isodose Control of Ede, Netherlands.
Related Reading
Nucletron outfits US Oncology, July 24, 2009
Nucletron adds executives, July 21, 2009
Nucletron nets FDA OK for new apps, July 13, 2009
Elekta, Nucletron ink Mosaiq deal, May 19, 2009
Nucletron adds to sales in 2008, April 24, 2009
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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)





