Sonio Suspect

K243614

Sonio · cleared 2025-02-21 · product code POK · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“Sonio Suspect is a Software as a Service (SaaS) solution that aims at helping interpreting physicians (designated as healthcare professionals i.e. HCP in the following) to identify abnormal fetal ultrasound findings during and/or after fetal ultrasound examinations.”
AlgorithmComputer vision Machine Learning-Based Algorithm
source quote (p.9)
“The technical principle of both Sonio Suspect and the predicate Koios DS is the characterization of ultrasound images items using computer vision and machine learning-based algorithms.”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedYes
source quote (p.10)
“Cybersecurity testing”

Validation studies (2)

Bench

n=8,745 images · 75 site(s)

endpoints: sensitivity; specificity

Reader study (MRMC)

n=750 images · 47 site(s)

endpoints: reader accuracy (AUC)

Reported performance (3 observations)

sensitivity0.932CI [91.6%-94.6%]
source quote (p.10)
“The results of the standalone performance testing demonstrated that Sonio Suspect automatically detects abnormal fetal ultrasound findings with a sensitivity of 93.2% (Confidence Interval of [91.6%-94.6%]) and a specificity of 90.8% (Confidence Interval of [89.5%-92.0%]).”
specificity0.908CI [89.5%-92.0%]
source quote (p.10)
“The results of the standalone performance testing demonstrated that Sonio Suspect automatically detects abnormal fetal ultrasound findings with a sensitivity of 93.2% (Confidence Interval of [91.6%-94.6%]) and a specificity of 90.8% (Confidence Interval of [89.5%-92.0%]).”
aurocas written: “auc”0.909CI (0.886, 0.931)
source quote (p.14)
“Overall 0.219 (0.185, 0.253) 0.689 (0.65, 0.73) 0.909 (0.886, 0.931)”

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

0
recalls in product code, 24mo
0
MAUDE reports in code, 12mo
—
vs code's own 3-yr baseline
0
drift signals on this device

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/K243614