CardioVision

K251293

Icardio.Ai · cleared 2025-11-21 · product code QUO · Cardiovascular

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“The iCardio.ai CardioVision™ Al is a standalone image analysis software developed by iCardio.ai Corporation, designed to assist in the review of echocardiography images.”
Algorithmconvolutional neural networks (CNNs), machine learning-based
source quote (p.6)
“The iCardio.ai CardioVision™ AI takes as input a DICOM-compliant, partial or full echocardiogram study, which must include at least one parasternal long-axis (PLAX) view of the heart and at least one full cardiac cycle. The device uses a set of convolutional neural networks (CNNs) to analyze the image data and estimate the likelihood of moderate or severe aortic stenosis.”
Adaptive (vs locked)No
source quote (p.6)
“The CNNs and their thresholds are fixed prior to validation and do not continuously learn during standalone testing.”
PCCPNo
Cybersecurity addressedNo

Validation studies (1)

Retrospective clinical

n=608 patients · 12 site(s)

endpoints: sensitivity; specificity; AUROC

Reported performance (7 observations)

sensitivity0.896CI 95% Wilson score CI: [0.8427, 0.9321]
source quote (p.12)
“Without indeterminate outputs, the sensitivity was estimated to be 89.6% (95% Wilson score CI: 84.3%-93.2%)”
specificity0.872CI 95% Wilson score CI: [0.8384, 0.8995]
source quote (p.12)
“and the specificity was estimated to be 87.2% (95% Wilson score CI: 83.8%-90.0%).”
aurocas written: “auc”0.945
source quote (p.12)
“AUROC 0.945”
ppvas written: “PPV”0.734CI 95% Wilson score CI: [0.673, 0.787]
source quote (p.12)
“PPV 0.734 (95% Wilson score CI: [0.673, 0.787])”
npvas written: “NPV”0.955CI 95% Wilson score CI: [0.931, 0.971]
source quote (p.12)
“NPV 0.955 (95% Wilson score CI: [0.931, 0.971])”
sensitivityas written: “Sensitivity (including indeterminate outputs)”0.876CI 95% Wilson score CI: [0.8213, 0.9162]
source quote (p.12)
“When including indeterminate outputs (i.e. rejections) in the sensitivity and specificity calculations, the sensitivity was estimated to be 0.876 (95% Wilson score CI: [0.8213, 0.9162])”
specificityas written: “Specificity (including indeterminate outputs)”0.866CI 95% Wilson score CI: [0.8324, 0.8943]
source quote (p.12)
“and the specificity was estimated to be 0.866 (95% Wilson score CI: [0.8324, 0.8943]).”

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 Cardiovascular 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/K251293