Imaging firm Pie Medical Imaging will release the new version of its CAAS MRV cardiac MR quantitative analysis software at this week's Society for Cardiovascular Magnetic Resonance (SCMR) meeting in Orlando.
New image acquisition capabilities have been added to increase the flexibility of importing images, according to the Maastricht, Netherlands-based firm. The software has also received enhancements for calculating volumes and ejection fractions using only long-axis images.
In addition, Pie said it has incorporated improvements to automatic breathing motion and added more flexibility for up-slope calculation.
Related Reading
Pie unveils CAAS MR, December 23, 2008
Pie adds to CAAS software, October 18, 2007
Pie to launch CAAS MRV 3.2 at ISMRM show, May 21, 2007
Pie to release new CAAS software, March 20, 2007
Pie Medical adds 3D visualization, October 16, 2006
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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)
