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510(k) Data Aggregation

    K Number
    K250151
    Device Name
    Us2.ca
    Manufacturer
    Eko.ai Pte. Ltd. d/b/a Us2.ai
    Date Cleared
    2025-06-20

    (150 days)

    Product Code
    SDJ
    Regulation Number
    870.2200
    Why did this record match?
    Applicant Name (Manufacturer) :

    Eko.ai Pte. Ltd. d/b/a Us2.ai

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP Authorized
    Intended Use
    Us2.ca processes acquired transthoracic cardiac ultrasound images to support qualified cardiologists, sonographers, or other licensed professional healthcare practitioners in their diagnosis of cardiac amyloidosis. Us2.ca is intended for use only in adult patients with increased left ventricular wall thickness, defined as an interventricular septal thickness (IVSd) or left ventricular posterior wall thickness (LVPWd) ≥ 12mm. Us2.ca is not intended to provide a diagnosis and does not replace current standards of care. The results from Us2.ca are not intended to exclude the need for further follow-up on cardiac amyloidosis.
    Device Description
    The Us2.ai platform is a clinical decision support tool that analyzes echocardiogram images in order to generate a series of AI-derived measurements. Fully automated, functional reporting with disease indications is also provided, in line with ASE & ESC guidelines. Echo images are sent to the Us2.ai platform where they are processed, analyzed and measured. Results that meet the confidence threshold for both image quality and measurement accuracy are passed through to a report for review by the clinical users. Report text is also generated and presented with the measurements, providing functional reporting and disease indications. The ultimate clinical decision and interpretation reside solely with the clinician. Us2.ca is an enhancement to Us2.ai existing Us2.v2 software, adding the capability to detect cardiac amyloidosis. It is an image post-processing analysis software device used for viewing and quantifying cardiovascular ultrasound images in DICOM format. The device is intended to aid diagnostic review and analysis of echocardiographic data, patient record management and reporting. The primary intended function of Us2.ca is to automatically identify patients who require additional follow-up for cardiac amyloidosis. In doing so, the primary benefit is to improve clinical echocardiographic workflow, enabling clinicians to generate and edit reports faster, with precision and with full control. The final clinical decision of the results still remains with the clinicians.
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    K Number
    K210791
    Device Name
    Us2.v1
    Manufacturer
    eko.ai Pte. Ltd. d/b/a Us2.ai
    Date Cleared
    2021-07-27

    (133 days)

    Product Code
    QIH, LLZ
    Regulation Number
    892.2050
    Why did this record match?
    Applicant Name (Manufacturer) :

    eko.ai Pte. Ltd. d/b/a Us2.ai

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP Authorized
    Intended Use
    Us2.v1 is a fully automated software platform that processes, analyses and makes measurements on acquired transthoracy cardiac ultrasound images, automatically producing a full report with measurements of several and functional parameters. The data produced by this software is intended to be used to support qualified cardiologists or licensed primary care providers for clinical decision-making. Us2.v1 is in adult patients. Us2.v1 has not been validated for the assessment of congenital heart disease, pericardial disease, and/or intra-cardiac lesions (e.g. tumours, thrombi).
    Device Description
    Us2.v1 is an image post-processing analysis software device used for viewing and quantifying cardiovascular ultrasound images in DICOM format. The device is intended to aid diagnostic review and analysis of echocardiographic data, patient record management and reporting. The software provides an interface for a skilled sonographer to perform the necessary markup on the echocardiographic image prior to review by the prescribing physician. The markup includes: the cardiac segments captured, measurements of distance, time, area and blood flow, quantitative analysis of cardiac function, and a summary report. The software allows the sonographer to enter their markup manually. It also provides automated markup and analysis, which the sonographer may choose to accept outright, to accept partially and modify, or to reject and ignore. Machine learning based view classification and border detection form the basis for this automated analysis. Additionally, the software has features for organizing, displaying and comparing to reference guidelines the quantitative data from cardiovascular images acquired from ultrasound scanners.
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