EchoNavigator R5.0

K253614

Philips Medical Systems Nederland B.V. · cleared 2026-03-17 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“EchoNavigator is a Software Medical Device that assists the interventionalist and surgeon with image guidance during treatment of cardiovascular disease for which the procedure uses both live X-ray and live Echo guidance.”
AlgorithmArtificial Intelligence built with Deep Learning technology for real-time automatic device detection, tracking and 3D pose-estimation.
source quote (p.7)
“DeviceGuide offers real-time automatic device detection, tracking and 3D pose-estimation in live Echo and live X-ray enabled by Artificial Intelligence which is built with Deep Learning technology.”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedYes
source quote (p.10)
“UL ANSI 2900-1, Standard For Safety, Standard For Software Cybersecurity Network-Connectable Products, Part 1: General Requirements (First Edition, 2017). FDA/CDRH recognition number 13-96 UL ANSI 2900-2-1, Standard for Safety Software Cybersecurity for Network-Connectable Products Part 2-1: Particular Requirements for Network Connectable Components of Healthcare and Wellness Systems, (First Edition, 2017). FDA/CDRH recognition number 13-104 IEC 81001-5-1 Edition 1.0 2021-12 Health software and health IT systems safety, effectiveness and security - Part 5-1: Security - Activities in the product life cycle. FDA/CDRH recognition number 13-122.”

Validation studies (2)

Retrospective clinical

n=113 patients

endpoints: positional accuracy; trajectory/orientation accuracy; algorithm latency

standards: IEC 62304 Medical device software – Software life cycle processes (Edition 1.1, 2015-06 Consolidated Version). FDA/CDRH recognition number 13-79., IEC 62366-1 Medical devices - Part 1: Application of usability engineering to medical devices (Edition 1.1, 2020-06 Consolidated Version). FDA/CDRH recognition number 5-129., IEC 82304-1 Health software – Part 1: General requirements for product safety (Edition 1.0 2016-10), FDA/CDRH recognition number 13-97., ISO 14971 Medical devices Application of risk management to medical devices (Third Edition 2019-12). FDA/CDRH recognition number 5-125., ISO 15223-1 Medical devices - Symbols to be used with information to be supplied by the manufacturer - Part 1: General requirements (Fourth edition 2021-07). FDA/CDRH recognition number 5-134., ISO 20417:2021 Medical devices Information to be supplied by the manufacturer (First edition 2021-04 Corrected version 2021-12). FDA/CDRH recognition number 5-135., UL ANSI 2900-1, Standard For Safety, Standard For Software Cybersecurity Network-Connectable Products, Part 1: General Requirements (First Edition, 2017). FDA/CDRH recognition number 13-96, UL ANSI 2900-2-1, Standard for Safety Software Cybersecurity for Network-Connectable Products Part 2-1: Particular Requirements for Network Connectable Components of Healthcare and Wellness Systems, (First Edition, 2017). FDA/CDRH recognition number 13-104, IEC 81001-5-1 Edition 1.0 2021-12 Health software and health IT systems safety, effectiveness and security - Part 5-1: Security - Activities in the product life cycle. FDA/CDRH recognition number 13-122.

Reader study (MRMC)

sample size not stated

endpoints: sufficiency of algorithm output

standards: IEC 62304 Medical device software – Software life cycle processes (Edition 1.1, 2015-06 Consolidated Version). FDA/CDRH recognition number 13-79., IEC 62366-1 Medical devices - Part 1: Application of usability engineering to medical devices (Edition 1.1, 2020-06 Consolidated Version). FDA/CDRH recognition number 5-129., IEC 82304-1 Health software – Part 1: General requirements for product safety (Edition 1.0 2016-10), FDA/CDRH recognition number 13-97., ISO 14971 Medical devices Application of risk management to medical devices (Third Edition 2019-12). FDA/CDRH recognition number 5-125., ISO 15223-1 Medical devices - Symbols to be used with information to be supplied by the manufacturer - Part 1: General requirements (Fourth edition 2021-07). FDA/CDRH recognition number 5-134., ISO 20417:2021 Medical devices Information to be supplied by the manufacturer (First edition 2021-04 Corrected version 2021-12). FDA/CDRH recognition number 5-135., UL ANSI 2900-1, Standard For Safety, Standard For Software Cybersecurity Network-Connectable Products, Part 1: General Requirements (First Edition, 2017). FDA/CDRH recognition number 13-96, UL ANSI 2900-2-1, Standard for Safety Software Cybersecurity for Network-Connectable Products Part 2-1: Particular Requirements for Network Connectable Components of Healthcare and Wellness Systems, (First Edition, 2017). FDA/CDRH recognition number 13-104, IEC 81001-5-1 Edition 1.0 2021-12 Health software and health IT systems safety, effectiveness and security - Part 5-1: Security - Activities in the product life cycle. FDA/CDRH recognition number 13-122.

Reported performance (3 observations)

accuracyas written: “positional accuracy”5
source quote (p.11)
“Overall performance met predefined specification limits, including ≤5 mm positional accuracy”
accuracyas written: “trajectory/orientation accuracy”10
source quote (p.11)
“and ≤10° trajectory/orientation accuracy.”
time_to_resultas written: “algorithm latency (detection and localization)”100
source quote (p.11)
“Algorithm latency met predefined specification, including detection and localization of the therapy device within 100ms of reception of the echo image.”

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/K253614