Royal Philips and the Spanish National Center for Cardiovascular Research have developed an MRI technique that provides a complete cardiac study in less than a minute.
The MRI protocol is able to acquire images that visualize the shape and function of the heart, all in approximately 20 seconds. Another 20 seconds is needed to evaluate the degree of fibrous after cardiac muscle death, according to Philips. Typically, this process takes about one hour.
The new technique, which is called enhanced SENSE by static outer-volume subtraction (ESSOS), is based on the fact that -- except for the heart -- a patient's chest anatomy remains stationary during a breath-hold exam.
With ESSOS, after an initial image of the static, outer volume of the heart is captured, this MRI data is temporarily removed. Since the MRI signal of the beating heart can more easily be subtracted from the subsequent scan data, acquiring a 3D image of the heart can be performed four times faster. After the dynamic of the beating heart is reconstructed, the static outer volume images are returned to generate a full 3D cardiac image.
The new ESSOS cardiac MRI protocol can acquire faster 3D images. Image courtesy of Philips.More than 100 patients with heart issues participated in a clinical trial in which both the conventional and the ESSOS method were used. Radiologists determined that both image types were in excellent agreement on heart function measurements and the characterization of tissue damage to a patient's heart muscle, according to trial results published in April 2021 in the Journal of the American College of Cardiology.
Additionally, the method can be used with existing phased-array MRI scanners without modification.
![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)
