BrightHeart View Classifier

K251456

BrightHeart · cleared 2025-06-05 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“BrightHeart View Classifier is a cloud-based software-only device which uses artificial intelligence (AI) to detect standard views during fetal heart scanning in fetal ultrasound images and video clips.”
Algorithmneural network performing standard view classification
source quote (p.8)
“The BrightHeart View Classifier device is powered by a neural network performing standard view classification in fetal ultrasound images.”
Adaptive (vs locked)FDA source did not state this
PCCPYes
source quote (p.1)
“FDA's substantial equivalence determination also included the review and clearance of your Predetermined Change Control Plan (PCCP). Under section 515C(b)(1) of the Act, a new premarket notification is not required for a change to a device cleared under section 510(k) of the Act, if such change is consistent with an established PCCP granted pursuant to section 515C(b)(2) of the Act.”
Cybersecurity addressedYes
source quote (p.7)
“Cybersecurity documentation was provided as recommended by FDA's Guidance for Industry and FDA Staff, “Content of Premarket Submissions for Management of Cybersecurity in Medical Devices".”

Validation studies (1)

Retrospective clinical

n=579 patients · 8 site(s)

endpoints: mean standard view recognition sensitivity; mean standard view recognition specificity

standards: FDA's Guidance for Industry and FDA Staff, “Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices.”, IEC 62304:2016, Medical device software - Software life cycle processes.

Reported performance (2 observations)

sensitivity0.939CI 95% CI, 0.917 ; 0.960
source quote (p.8)
“The performance testing demonstrated that BrightHeart View Classifier identifies standard views with a mean standard view recognition sensitivity of 0.939 (95% CI, 0.917 ; 0.960)”
specificity0.984CI 95% CI, 0.973 ; 0.996
source quote (p.8)
“and a mean standard view recognition specificity of 0.984 (95% CI, 0.973 ; 0.996).”

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
3
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/K251456