AVA (Augmented Vascular Analysis)

K201369

See-Mode Technologies Pte. Ltd. · cleared 2020-09-16 · product code LLZ · Radiology

FDA 510(k) summary for AVA (Augmented Vascular Analysis) (K201369)

Constat organizes this clearance into predicate context, validation evidence, reported performance, postmarket signals, and reimbursement links. Each extracted claim stays tied to the public FDA source; missing fields remain explicitly unstated.

Validation studies
4
Cited predicates
1
Performance observations
2
Product code
LLZ
Official FDA 510(k) database record ↗FDA 510(k) source PDF ↗

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.3)
“See-Mode AVA (Augmented Vascular Analysis) is a stand-alone, image processing software for analysis, measurement, and reporting of DICOM-compliant vascular ultrasound images obtained from carotid and lower limb arteries.”
Algorithmartificial intelligence and machine learning
source quote (p.9)
“With the advancements in the field of artificial intelligence and machine learning, See-Mode AVA incorporates a logical update to use artificial intelligence for image analysis. Machine learning and artificial intelligence (AI) have been proven as an efficient and accurate method for analyzing medical images and is used among a wide range of legally marketed medical devices.”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (4)

Retrospective clinical

n=205 images

endpoints: IMT correlation coefficient

standards: IEC 62304:2006/AC:2015

Retrospective clinical

n=783 images

endpoints: Accuracy in reading different types of annotation

Retrospective clinical

n=1,117 images

endpoints: Correlation coefficient for PSV; Correlation coefficient for EDV

Retrospective clinical

n=150 images

endpoints: Overall accuracy in detecting the waveform type

Reported performance (2 observations)

accuracyas written: “Text recognition accuracy”stated without valueCI varying from 92% to 96%
source quote (p.10)
“The text recognition algorithm had a high accuracy in reading different types of annotation varying from 92% to 96%.”
accuracyas written: “Waveform type classifier overall accuracy”0.93
source quote (p.11)
“It was observed that the algorithm was in strong agreement with the expert annotations with a 93% overall accuracy in detecting the waveform type.”

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

25
recalls in product code, 24mo
397
MAUDE reports in code, 12mo
+963%
vs code's own 3-yr baseline
30
drift signals on this device
  • recall_reason_pattern

    Software/algorithm-related recall in product code LLZ (Merge Healthcare, Inc., initiated 2026-07-22): "Software issue may cause measurements to be displayed inaccurately." Recalling firm is another firm in the same product code.

    first seen 2026-09-02 · recall res_event_number:99520

  • recall_reason_pattern

    Software/algorithm-related recall in product code LLZ (FUJIFILM Healthcare Americas Corporation, initiated 2026-07-22): "Software issue may cause the ruler measurement to be inaccurate." Recalling firm is another firm in the same product code.

    first seen 2026-09-02 · recall res_event_number:99529

  • recall_reason_pattern

    Software/algorithm-related recall in product code LLZ (Merge Healthcare, Inc., initiated 2026-06-30): "Merge Healthcare has identified a potential issue that may cause thumbnails from a previously opened patient study to be displayed in the Thumbnail Bar while a different patient st" Recalling firm is another firm in the same product code.

    first seen 2026-09-02 · recall res_event_number:99391

  • recall_reason_pattern

    Software/algorithm-related recall in product code LLZ (Boston Scientific Corporation, initiated 2026-06-19): "Software anomaly occurs when a user adds one or more vials to the cart and subsequently returns to the Activity Calculator to modify one or more input. When a user modifies an inpu" Recalling firm is another firm in the same product code.

    first seen 2026-09-02 · recall res_event_number:99236

  • adverse_event_inflection

    MAUDE adverse-event reports for product code LLZ: 295 in the 12 months ending 2026-06, vs a 37.7/12mo average over the prior 3 windows (+683%). Code-level count — reports are not attributed to this specific device.

    first seen 2026-07-08 · openFDA /device/event.json count=date_received product_code=LLZ

  • recall_reason_pattern

    Software/algorithm-related recall in product code LLZ (GE Medical Systems SCS, initiated 2026-05-08): "GE HealthCare has become aware of a context synchronization issue in AW Server 3.2 ext. 6.5. When a user selects a patient or exam in the AW Server Web Client worklist and launches" Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:99042

  • …and 24 more.

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 2026-09-02.

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.

Related FDA clearances

More AI/ML devices under product code LLZ

These are recent clearances in the same FDA product-code category. Shared classification does not by itself make a device an appropriate predicate.

Acorn 3D Software (AC-SEG-4009); Acorn 3DP Model (AC-101-XX)

K251532

Mighty Oak Medical

cleared 2025-11-03

SurgiTwin

K250290

Twinsight

cleared 2025-08-29

Neuro Insight V1.0

K243681

Olea Medical S.A.S.

cleared 2025-07-23

GyriCalc (Version 1.0.0)

K250686

NeuroSpectrum Insights Corp.

cleared 2025-07-22

VersaViewer

K243651

GE Medical Systems SCS

cleared 2025-04-21

brAIn™ Shoulder Positioning

K243292

Avatar Medical

cleared 2025-03-20

aiCockpit AI Viewer

K241546

Fovia, Inc.

cleared 2025-02-26

QuickRad

K242838

Aikenist Technologies Pvt Ltd

cleared 2025-02-21

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K201369