New Zealand breast imaging software developer Matakina International has announced that the Dutch breast screening organizations and the University Medical Centre Utrecht will use its Volpara software to assess breast density in a forthcoming clinical trial.
The objective of the MRI as Additional Screening Modality to Detect Breast Cancer in Women With Extremely Dense Breasts (DENSE) trial is to determine the cost-effectiveness of biennial screening with mammography and MRI compared with mammography alone in women ages 50 to 75 years old and who show mammographic density greater than 75% (BI-RADS breast density category 4).
The clinical trial's principal investigator is Carla van Gils, PhD, of the department of clinical epidemiology at the Julius Center for Health Sciences and Primary Care University Medical Centre Utrecht. Radiology departments at hospitals located in Amsterdam, Groningen, Maastricht, Nijmegen, and Rotterdam also have enrolled to participate.
For the trial, breast density will be assessed using the Volpara imaging software in a subset of the screening units. Some 5,000 women with BI-RADS breast density category 4 will be invited for breast MRI and their results will be compared with those who have only a mammogram.
![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)
