Proton therapy technology developer Ion Beam Applications (IBA) is projecting a double-digit increase in revenue when the company releases its 2015 financial report next month.
IBA estimates that 2015 revenues will reach approximately 270 million euros ($300.7 million U.S.), up more than 20% from the 220.6 million euros ($245.7 million U.S.) recorded in 2014. Recurring earnings before interest and taxes (REBIT) in 2015 will be more than 20% higher than the 22.9 million euros ($25.5 million U.S.) posted in 2014, according to the firm.
The company also anticipates reporting a record for orders in 2015 and a backlog of approximately 330 million euros ($367.6 million U.S.) in proton therapy and other accelerators at the end of 2015, compared with a backlog of 256.2 million euros ($285.4 million U.S.) at the end of 2014.
This year also looks promising, according to IBA, with expected revenue growth of more than 20% in 2016. The forecast is based on the anticipated continued development of the proton therapy market, as well as the company's economies of scale from an enhanced production rate and its investment in research and development, IBA said.
![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)
