Company Spotlight: Sonio Suspect - Moving Fetal Ultrasound AI from the Cloud to the Machine

In this Company Spotlight, we explore the FDA 510(k) summary for Sonio Suspect, an AI tool designed to detect abnormal fetal ultrasound findings. We unpack how Sonio transitioned their algorithm from a cloud-based web application to an integrated, on-device solution, examining the performance data, the exact anatomical anomalies it screens for, and what this regulatory shift means for medtech developers and clinicians.

Key points

Sonio Suspect is an AI software cleared to assist interpreting physicians in identifying abnormal fetal ultrasound findings from 11 weeks to 41 weeks of gestational age.This specific 510(k) clearance allows Sonio to shift from a Python-based cloud application to a C++ algorithm integrated directly into third-party ultrasound systems.The integrated device demonstrated an average sensitivity of 92.5% and specificity of 90.4% across tested findings, establishing substantial equivalence to the predicate device.The testing validated performance across specific chest, abdominal, and cephalic anomalies, though the public summary does not disclose the total number of scans in the test dataset.The FDA document emphasizes that patient management decisions should not be made solely on the results of the Sonio Suspect analysis.

Source: FDA 510(k) summary K261519: Sonio Suspect (Sonio) - U.S. Food and Drug Administration, 2026

This episode is an AI-generated conversation summarising a public document; the hosts' voices are synthetic. It is for information only and is not medical advice. Always refer to the original source.

Full transcript: https://ai-in-medicine-podcast.vercel.app/episodes/company-spotlight-sonio-suspect-moving-fetal-ultrasound-ai-from-the-cl-3260c2