With reported performance validation on over 17,000 ultrasound images, Sonio Detect employs artificial intelligence (AI) to help ensure quality criteria for fetal ultrasound imaging of the brain and heart.
The Food and Drug Administration (FDA) has granted 510(k) clearance for Sonio Detect (Sonio), a fetal ultrasound software as a service (SaaS) platform that utilizes artificial intelligence (AI) to enhance the assessment of fetal heart and brain structures.
Emphasizing Sonio Detect’s robust accuracy in identifying ultrasound views and quality criteria, Sonio said the technology demonstrated a 92 percent sensitivity in performance validation testing on over 17,000 ultrasound images.
Sonio claimed the technology with Sonio Detect increases the efficiency of fetal heart and brain assessment and may facilitate improved diagnosis of fetal anomalies.
“Bringing the first easy to use, manufacturer agnostic and efficient quality control solution to all OBGYNs, (maternal fetal medicine specialists) and sonographers, we believe better screening will lead to better detection of potential anomalies or reassurance to provide better maternal care. Our goal is to transform prenatal care by providing a reliable tool that ensures better health outcomes for both mothers and babies,” noted Cecile Brosset, the chief executive officer and co-founder of Sonio.
Stay at the forefront of radiology with the Diagnostic Imaging newsletter, delivering the latest news, clinical insights, and imaging advancements for today’s radiologists.
FDA Expands Approval of MRI-Guided Ultrasound Treatment for Patients with Parkinson’s Disease
July 9th 2025For patients with advanced Parkinson’s disease, the expanded FDA approval of the Exablate Neuro platform allows for the use of MRI-guided focused ultrasound in performing staged bilateral pallidothalamic tractotomy.
Mammography Study: AI Facilitates Greater Accuracy and Longer Fixation Time on Suspicious Areas
July 8th 2025While noting no differences in sensitivity, specificity or reading time with adjunctive AI for mammography screening, the authors of a new study noted a 4 percent higher AUC and increased fixation time on lesion regions.