Ventripoint Medical System Plus (VMS+) 4.0

K241222

Ventripoint Diagnostics Ltd. · cleared 2025-02-26 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typehardware with ml
source quote (p.5)
“The Ventripoint VMS+ 4.0 System is a medical imaging device designed to assist clinicians in evaluating cardiac function through 3D reconstruction of heart chambers. It uses a Knowledge-Based Reconstruction (KBR) algorithm to recreate the heart's shape by capturing 2D ultrasound images at specific angles and referencing a database of MRI heart shape catalogs. The reconstructed 3D heart models are used to calculate volumes of any of the four chambers at end-diastolic and/or end-systolic phases. The software can also be installed on a separate workstation to import 3D datasets, MRI studies, and VMS+ studies.”
AlgorithmKnowledge-Based Reconstruction (KBR) algorithm with an edge detection algorithm and automated point placement first guesses (AI software)
source quote (p.5)
“It uses a Knowledge-Based Reconstruction (KBR) algorithm to recreate the heart's shape by capturing 2D ultrasound images at specific angles and referencing a database of MRI heart shape catalogs. The system employs user-driven anatomical control point placement to generate 3D models. Users manually adjust control points based on an anatomical template aligned with the patient's ultrasound images. An edge detection algorithm refines these points to match detected anatomical boundaries, ensuring model precision. Alternatively, automated point placement first guesses can be generated via a button press. User must manually adjust first guess point placements as required.”
Adaptive (vs locked)No
source quote (p.8)
“The automated control point first guess feature only provides an alternate method for obtaining first guesses for the location of the control points and users are still expected to update control point location in the same manner as the predicate before being used for further analysis. These proposed modifications are verified to ensure overall performance remains the same as the predicate with acceptable results.”
PCCPNo
Cybersecurity addressedYes
source quote (p.7)
“Cybersecurity testing was performed as recommended by FDA's Guidance for Industry and FDA Staff, "Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions". This included both internal cybersecurity validation and external penetration testing to ensure that any existing vulnerabilities were discovered and addressed, and that the device is cyber safe.”

Validation studies (2)

Bench

sample size not stated

Standalone

n=160 images

endpoints: user performance for anatomical point processing; proportion of images for each software where all anatomical points within the image would be finalized, by the user, within its respective expert consensus region

Reported performance (0 observations)

FDA source did not state a quantitative performance metric — non-reporting is itself the signal.

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/K241222