The World Interactive Network Focused on Critical UltraSound (WINFOCUS) has released a new consensus statement for the use of focused cardiac ultrasound.
The article, titled "International Evidence-Based Recommendations for Focused Cardiac Ultrasound," presents results from the first international conference on the technology and its applications. The article was published in the July issue of the Journal of the American Society of Echocardiography (Vol. 27:7, pp. 683.e1-683.e33).
WINFOCUS conducted four conferences -- in New Delhi, Milan, Boston, and Barcelona, Spain -- to establish recommendations that outline the nature, applications, technique, potential benefits, clinical integration, education, and certification principles for focused cardiac ultrasound, both for adults and pediatric patients. The organization hopes to standardize the application of focused cardiac ultrasound in different clinical settings around the world.
"These recommendations represent a turning point for the medical community, especially, but not exclusively, in the field of emergency and critical care," said lead author Dr. Gabriele Via, from IRCCS Fondazione Policlinico San Matteo in Pavia, Italy, in a statement released by the journal. "For the first time ... multiple authoritative scientific societies representing different specialties and continents (including the world's major echocardiographic societies) collaborated to set the standards for the practice of focused cardiac ultrasound."
![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)
