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

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