Echocardiography technology developer VentriPoint has published results of a clinical study that demonstrate its VMS heart analysis technology can go beyond 2D ultrasound imaging in a range of cardiac conditions.
In a study by German researchers at the Center for Congenital Heart Defects in Bad Oeynhausen, three imaging modalities -- 2D echo, 3D echo, and cardiac MRI -- gave the same results when analyzed using the VMS technique and were equivalent to a gold-standard MRI protocol when visualizing right ventricle function.
Usually, comparing echocardiography and cardiac MRI has been discouraged due to unexplained discrepancies, VentriPoint said. The firm asserts that standardization using the VMS technique for all images would give comparable longitudinal results and allow for patient monitoring and treatment decisions.
The study also showed that, when using the VMS approach, analysis took just five minutes, compared with 10 to 30 minutes using conventional techniques. It validates that the VMS approach is as accurate and reliable for analyzing MRI images or 3D ultrasound images, the firm added.
The study has been accepted for publication in the Journal of the American Society of Echocardiography, the company 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)
