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    • Products

    Coronary artery disease, the number one cause of death worldwide,
    can be diagnosed in advance by calcification score using CT images.

    Artificial intelligence accurately detects coronary artery calcification
    at an expert level (99.2%).

    Artificial intelligence accurately detects coronary artery calcification
    at an expert level (99.2%).

    MFDS • FDA • CE • PMDA • TFDA Clearance

    Accurate and detailed segmentation

    With CAC’s automatic segmentation of the heart and surrounding structures, CAC can accurately analyze the calcified plaques in coronary arteries.

    Accurate calcification detection
    in coronary arteries

    ROBINSCA* clinical examination of 997 non-contrast ECG CT images Performance evaluation was performed through CAC detection and quantification.

    *ROBINSCA : Risk Or Benefit IN Screening for CArdiovascular disease

    • Medical AI diagnostic accuracy: 99.2%
    • Detection and classification concordance: 87%
    • Agatston score concordance: 95%

    Diagnoses are also available
    from chest CTs

    Coronary artery calcification can be quantified not only on heart CT images but also on chest CT images, helping early detection, and reducing patient exposure.

    • Kernel conversion AI technology is applied.

    Predicting risk
    with the lastest calssification method

    Using CAC-DRS* is better for predicting risk than just using Agatston scores on non-contrast and non-cardiac CT scans.

    *CAC-DRS: Coronary Artery Calcium Data and Reporting System.
    An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT)

    • Represents the total calcium score and the number of involved arteries.
    • General recommendations are provided for further management

    Integration in all standard reading environments

    Integration in all solutions comply with DICOM, TCP/IP
    (PACS & 3rd party solutions)

    • DICOM
    • HL7
    • Shared folder and Open API
    • Outputs: Annotated images, DICOM SR, pdf
    • Deployment:
      Locally on dedicated hardware, Locally virtualized (docker), Cloud-based

    Entirely automated process

    Pre-analysis is possible with fully automatic work procedures, and reports containing accurate and detailed results can be used in clinical practice.


    • Improving the CAC Score by Addition of Regional Measures of Calcium Distribution: Multi-Ethnic Study of Atherosclerosis

      JACC Cardiovascular Imaging, 2016

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    • 2016 SCCT/STR guidelines for coronary artery calcium scoring of noncontrast noncardiac chest CT scans: A report of the Society of Cardiovascular Computed Tomography and Society of Thoracic Radiology

      Journal of Cardiovascular Computed Tomography, 2016

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    • Distribution of coronary artery calcium by race, gender, and age: results from the Multi-Ethnic Study of Atherosclerosis (MESA)

      Circulation, 2006

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    • Age and gender distributions of coronary artery calcium detected by electron beam tomography in 35,246 adults

      The American Journal of Cardiology, 2001

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