Cardiac CT Function Software Application

K241038

Circle Cardiovascular Imaging · cleared 2024-06-07 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“Circle's Cardiac CT Function Software Application (“CT Function Module” or “CT Function", for short) is a software device that enables the analysis of cardiac images acquired using computed tomography (CT) scanners.”
AlgorithmArtificial Intelligence / Machine Learning (AI/ML) algorithm to detect and segment heart structures and post-processing methods to convert the heart segments to editable surfaces.
source quote (p.5)
“The CT Function Module implements an Artificial Intelligence / Machine Learning (AI/ML) algorithm to detect and segment heart structures and post-processing methods to convert the heart segments to editable surfaces.”
Adaptive (vs locked)No
source quote (p.11)
“All data used for validation were not used during the development of the ML algorithms.”
PCCPNo
Cybersecurity addressedFDA source did not state this

Validation studies (1)

Retrospective clinical

sample size not stated · 9 site(s)

endpoints: performance of the ML-based segmentation of Left Ventricle (LV) cavity; performance of the ML-based segmentation of LV myocardium; performance of the ML-based segmentation of Right Ventricle (RV) cavity; mean volume prediction error (Mean Absolute Error in predicted volumetric measures, or MAE); 3D Hausdorff Distance (HD); Dice coefficient; EF bias

standards: ISO 13485:2016, IEC 62304:2015, ISO 14971:2019, DICOM standards

Reported performance (3 observations)

diceas written: “LV cavity segmentation Dice coefficient”stated without valueCI > 86%
source quote (p.11)
“a Dice coefficient above 86%”
diceas written: “RV cavity segmentation Dice coefficient”stated without valueCI > 85%
source quote (p.11)
“a Dice coefficient above 85%”
diceas written: “LV myocardium segmentation Dice coefficient”stated without valueCI > 82%
source quote (p.11)
“a Dice coefficient above 82%”

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/K241038