Abstract submissions are now open for the 37th ISUOG World Congress, taking place in Lisbon, Portugal from 13–16 September 2027.
Dr Rozina Iqbal shares her story of a life-changing diagnosis for her baby, which resulted in a heartbreaking loss not long after his birth.
Ultrasound Essentials 2027 brings together internationally renowned speakers to share valuable scientific insights on key aspects of ultrasound in obstetrics and gynecology, ranging from fundamental concepts to specialised applications.
This year's Travel Grant scheme allowed 6 abstract submitters from low-resource countries to attend the ISUOG World Congress. Read their profiles and testimonials below:
Find out more about the 36th World Congress on Ultrasound in Obstetrics and Gynecology in London- including the scientific program, scientific awards and content available on demand.
New UOG Journal videoclip showing the ‘gable roof’ sign: a new 2D/3D ultrasound imaging sign for the early diagnosis of Cesarean scar ectopic pregnancy.
New UOG Journal videoclip showing 3D ultrasound reconstruction of decidualized posterior compartment deep endometriosis, with hypervascularization highlighted on color Doppler, which can mimic malignancy.
New UOG Journal videoclip showing a decidualized ovarian endometrioma, which can mimic malignancy in non-pregnant women receiving low-dose progesterone or progestin therapy.
The October issue of Ultrasound in Obstetrics & Gynecology includes a prospective longitudinal study investigating anthropometric and cardiovascular parameter trajectories across 12 months postpartum in women at high risk for pre-eclampsia (PE), a secondary analysis of a multicenter randomized trial evaluating risk factors for PE in high-risk women receiving low-dose aspirin prophylaxis, an observational study assessing the accuracy of gestational-age estimation using an artificial intelligence system applied to non-targeted ultrasound sweeps, and a retrospective observational study investigating the potential for radiomics features to distinguish between high-grade and low-grade serous ovarian carcinoma and whether their incorporation into machine-learning models can provide additional discriminatory value over models based on conventional ultrasound.