Sonio Detect

K240406

Sonio · cleared 2024-04-26 · product code IYN · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“Sonio Detect is a Software as a Service SaaS solution that aims at helping sonographers, OB/GYN MFMs and Fetal surgeons (all three designated as healthcare professionals i.e. HCP in the following) to perform their routine fetal ultrasound examinations in real-time.”
AlgorithmArtificial Intelligence, Lecture of biometrics, Colorimetry for 3D and Doppler
source quote (p.12)
“Artificial Intelligence Lecture of biometrics Colorimetry for 3D and Doppler”
Adaptive (vs locked)No
source quote (p.5)
“The end user can interact with the software to override the Sonio Detect's outputs (reassign the image to another view or unassign it or assign it if it was not assigned, changes the status of a quality criteria from verified to unverified or from unverified to verified) and manually set the characteristics of the views. The user has the ability to review and edit/override the matching at any time during or at the end of the exam.”
PCCPNo
Cybersecurity addressedYes
source quote (p.13)
“Cybersecurity testing”

Validation studies (1)

Bench

n=36,769 images

endpoints: Automatic detection of 3D fetal ultrasound images; Automatic detection of Doppler fetal ultrasound images; Automatic detection of fetal ultrasound views through reading of annotations on images; Automatic detection of 7 T1 fetal ultrasound images; Automatic detection of 18 T2/T3 fetal ultrasound images; Automatic detection of 8 fetal brain anatomical structures on the views "Transthalamic”, “Transventricular”, "Transcerebellar" at T2/T3; Automatic detection of 6 fetal thorax and heart anatomical structures on the views "Four chambers", "LVOT”, “RVOT”, "Three vessels or Three vessels and trachea", "Abdominal Circumference", "Axial view of the kidneys" at T1; Automatic detection of 21 fetal thorax and heart anatomical structures on the views "Four chambers", "LVOT”, “RVOT”, "Three vessels or Three vessels and trachea", "Abdominal Circumference”, “Axial view of the kidneys” at T2/T3; Automatic detection of 4 fetal placenta anatomical structures on the views "Placenta insertion", "Placenta location" at T2/T3; Automatic detection of the Anterior placenta location for the views “Placenta insertion”, “Placenta location" at T2/T3; Automatic detection of the Posterior placenta location for the views “Placenta insertion”, “Placenta location" at T2/T3; Automatic detection of the "Female sex" for fetal sex for the view "External Genitalia"; Automatic detection of the "Male sex" for fetal sex for the view "External Genitalia"

Reported performance (5 observations)

sensitivity0.934CI (0.925-0.943)
source quote (p.14)
“Automatic detection of 8 fetal brain anatomical structures on the views "Transthalamic”, “Transventricular”, "Transcerebellar" at T2/T3 0.934 (0.925-0.943)”
specificity0.949CI (0.942-0.955)
source quote (p.14)
“0.949 (0.942-0.955)”
sensitivityas written: “Automatic detection of 3D fetal ultrasound images Sensitivity”0.892CI (0.836-0.931)
source quote (p.14)
“Automatic detection of 3D fetal ultrasound images 0.892 (0.836-0.931)”
sensitivityas written: “Automatic detection of 6 fetal thorax and heart anatomical structures... at T1 Sensitivity”0.861CI (0.841-0.878)
source quote (p.14)
“Automatic detection of 6 fetal thorax and heart anatomical structures on the views "Four chambers", "LVOT”, “RVOT”, "Three vessels or Three vessels and trachea", "Abdominal Circumference", "Axial view of the kidneys" at T1 0.861 (0.841-0.878)”
specificityas written: “Automatic detection of 6 fetal thorax and heart anatomical structures... at T1 Specificity”0.938CI (0.926-0.948)
source quote (p.14)
“0.938 (0.926-0.948)”

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

85
recalls in product code, 24mo
554
MAUDE reports in code, 12mo
+85%
vs code's own 3-yr baseline
5
drift signals on this device
  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K252433 (decision 2026-03-16) from Sonio for a matching device line ("Sonio Detect (v3)") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K252433

  • recall_reason_pattern

    Software/algorithm-related recall in product code IYN (Philips Ultrasound, LLC, initiated 2025-10-31): "Ultrasound system compatibility issues with Apple devices running iOS 18 may cause a failure to perform live imagining." Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:97843

  • recall_reason_pattern

    Software/algorithm-related recall in product code IYN (GE Medical Systems, LLC, initiated 2025-09-18): "The Ultrasound-Guided Attenuation Parameter (UGAP) measurement data may display inaccurate values representing liver steatosis. This could potentially lead to inappropriate clinica" Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:97726

  • recall_reason_pattern

    Software/algorithm-related recall in product code IYN (GE Medical Systems China Co., Ltd. Dev. Zone National Hi-Tech; No., initiated 2025-05-16): "GE HealthCare has become aware that the Estimated Fetal Weight (EFW) measurement data feature on the Versana Premier R3 and LOGIQ F R3 series ultrasound systems can display previou" Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:96992

  • recall_reason_pattern

    Software/algorithm-related recall in product code IYN (Siemens Medical Solutions USA, Inc., initiated 2024-08-15): "If ultrasound systems with software, are changed from factory default to : 1) Milliliters per second (ml/sec, mL/sec) or 2) Milliliters per minute (ml/min, mL/min); then systems wi" Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:95254

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device); a recall is shown as device-attributed only when the recall record itself lists this clearance number. Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Radiology panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K240406