Radiation oncology firm Elekta of Stockholm will provide cancer and neurosurgical treatment technology and supporting IT systems to a new hospital being built in Sydney, Australia, as a joint venture between Dalcross Private Hospital and Macquarie University.
Elekta will deliver its Leksell Gamma Knife Perfexion for noninvasive radiosurgery, Elekta Synergy digital linear accelerator systems for intensity-modulated and image-guided radiation therapy, Mosaiq information management system, Mosaiq RTP and ERGO++ for radiation treatment planning, and its 3-mm micro-MLC for radiation therapy.
Dalcross Private Hospital currently operates a facility that specializes in ophthalmology; neurosurgery; vascular surgery; and ear, nose, and throat surgery. Beginning next year, Dalcross also will operate the Macquarie University Private Hospital as a joint venture with the school's Australian School of Advanced Medicine.
The Private Hospital will be the first center in Australia to offer Gamma Knife surgery.
Related Reading
Elekta readies first order for New Zealand, April 25, 2008
Elekta completes CMS purchase, March 5, 2008
Elekta receives French MEG contract, February 22, 2008
Elekta to buy CMS, February 19, 2008
Elekta lands Nebraska MEG installation, February 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)
