Successful direct sales of its medical systems helped Swedish healthcare informatics firm Sectra to 11% net sales growth in its fiscal second quarter.
For the period, the Linköping-based firm had net sales of 373.4 million Swedish kronor ($45.8 million U.S.), up from 329.1 million kronor ($40.3 million) in the same quarter last year. Profit after financial items increased to 48.2 million kronor ($5.9 million), up from 23 million SEK ($2.8 million) a year ago.
Order bookings of 723.5 million kronor ($88.7 million) in the second quarter were the highest ever for Sectra, due to direct medical system sales. Among other deals, Sectra received an order from the Northern Ireland Department of Health valued at about 360 million kronor ($44.1 million) over 10 years. The deal was the largest single order ever for Sectra.
A strengthening of the U.S. dollar and euro contributed to a significant rise in profit, according to the vendor.
Related Reading
Sectra to integrate MRI workflow app, November 18, 2008
Road to RSNA, Healthcare Informatics, Sectra, November 10, 2008
Road to RSNA, Women's Imaging, Sectra, October 28, 2008
Sectra teams up with Norwegian EPR firm, October 27, 2008
Road to RSNA, PACS, Sectra, October 23, 2008
Copyright © 2008 AuntMinnie.com
![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)
