
The U.K. Society of Radiographers (SoR) is drawing attention to a statement written by a team of sonographers and patients on "etiquette" for obstetric examination.
The statement addresses what can be a tricky navigation of expectations about obstetric ultrasound scans, according to a team led by Donna White of East and North Hertfordshire National Health Service Trust.
"Popular media tends to portray obstetric ultrasound scans as joyful events where everyone is smiling, the lights are always on and the telling of the baby's sex plays a big part in the drama of the event," White's team wrote.
"Real scans are not like this. They are quiet and serious affairs which require great concentration by the professionals involved. And while sonographers also love to share the joy of a pregnancy with their clients, sadly not every pregnancy is a joy, not every scan is a happy occasion," the group noted.
The COVID-19 pandemic changed the dynamics of the obstetric ultrasound, in part because the partners and children of the pregnant woman were not able to attend the exam.
"For some, the thought of attending a scan alone was unthinkable," the authors wrote. "For other women, the enforced solitude in the scan room offered a chance to listen, concentrate and interact with their healthcare professionals in a real synergy of care."
It may be that post COVID-19, obstetric ultrasound etiquette will change, the team concluded.
"COVID-19 has given us the chance to reset our relationship with our service users, which is to everyone's benefit," White and her colleagues pointed out. "We hope we have come through the pandemic to a level of greater understanding."

















![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&fit=crop&h=112&q=70&w=112)
