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510(k) Data Aggregation

    K Number
    K120995
    Manufacturer
    Date Cleared
    2012-12-03

    (245 days)

    Product Code
    Regulation Number
    892.2050
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    eRAD PACS/ eRAD RIS/PACS is a PACS software product used to receive DICOM images, scheduling information and textual report, organize and store them in an internal format, and to make that information available across a network via web and customized user interfaces.

    The eRAD PACS/ eRAD RIS/PACS viewer software is intended for use as a primary diagnostic and analysis tool for diagnostic images. eRAD PACS/ eRAD RIS/PACS is for hospitals, imaging centers, radiologists, reading practices and any user who requires and is granted access to patient image, demographic and report information.

    The eRAD PACS/ eRAD RIS/PACS viewer displays images from CT, computed radiography, MRI, mammography, nuclear medicine, PET, secondary capture, ultrasound, x-ray angiography, x-ray fluoroscopy and visible light modalities.

    Lossy compressed mammography images and digitized film screen mammography images must not be reviewed for primary image interpretations. Mammography images may only be interpreted using an FDA approved monitor that offers at least 5 mega-pixel resolution and meets other technical specifications reviewed and accepted by FDA.

    Device Description

    eRAD PACS/ eRAD RIS/PACS Software Product is a PACS system, comprised of acquisition components, a central systems manager component, diagnostic viewing components, and an archiving component. The data flow is such that patient and procedure information is optionally delivered to the central system manager, followed by the acquisition of the image objects directly from the image sources or by one of the acquisition components. After receiving the procedure information or after receiving image objects, the central system manager searches for and retrieves relevant prior procedure data from the archiving a component. When the central system manager registers the acquired image objects and the retrieved prior procedure data, a user can access the information by selecting the item from the operator worklist. The image data is transmitted to and rendered on the user's workstation using the diagnostic viewing components. After using the workstation to view the images, the user optionally dictates a report into the system, after which, a user can play back the diction and transcribe it to text. Once eRAD PACS's central system manager registers a report, the report is available for access by the referring physician, or it can be exported into an information system. At some configured point in time, the image data and the report information is delivered to the archiving component for backup and long-term storage.

    AI/ML Overview

    The provided 510(k) submission for K120995 (eRAD PACS/eRAD RIS/PACS Software) does not contain acceptance criteria or a detailed study proving the device meets specific performance criteria in the way a clinical performance study for an AI/CADe device would.

    This submission is for a Picture Archiving and Communications System (PACS), which is a foundational medical imaging infrastructure. The "testing" referred to is about demonstrating that the modified software (making it available in a software-only option) is substantially equivalent to its predicate devices and functions as intended, not about its diagnostic performance against specific clinical endpoints.

    Therefore, many of the requested elements for a clinical performance study are not applicable to this documentation.

    Here's a breakdown based on the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance

    Not applicable in the context of a clinical performance study. The 510(k) focuses on substantial equivalence for a PACS system, not on specific diagnostic performance metrics like sensitivity or specificity. The "performance" assessment is about system functionality and equivalence to the predicate device.

    2. Sample Size Used for the Test Set and Data Provenance

    Not applicable. No clinical "test set" in the context of diagnostic performance (e.g., a set of patient images with confirmed diagnoses) is described. The non-clinical testing mentioned refers to system verification and validation against design requirements.

    3. Number of Experts Used to Establish Ground Truth and Qualifications

    Not applicable. Ground truth, as it pertains to diagnostic accuracy, is not established or discussed in this submission.

    4. Adjudication Method for the Test Set

    Not applicable. No clinical test set or ground truth adjudication process is described.

    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

    No. A MRMC study was not done, as this submission is not about the diagnostic performance of an AI/CADe tool requiring human-in-the-loop assessment.

    6. Standalone (Algorithm Only) Performance Study

    No. A standalone performance study for an algorithm's diagnostic capabilities was not performed. The device is a PACS system, intended for displaying and managing images for human interpretation, not an automated diagnostic algorithm.

    7. Type of Ground Truth Used

    Not applicable. No ground truth for diagnostic purposes is mentioned. The testing focused on functional verification and validation of the PACS system.

    8. Sample Size for the Training Set

    Not applicable. The device is a PACS system, not an AI or machine learning algorithm that requires a training set in the diagnostic performance sense.

    9. How the Ground Truth for the Training Set Was Established

    Not applicable. As there is no training set for an AI/ML algorithm, this question is not relevant to the provided documentation.


    Summary of what the submission does say about "testing":

    • Discussion of Non-Clinical Testing Performed: "Thorough non-clinical system verification and validation testing was conducted in accordance with applicable international standards and internal design requirement to verify that the eRAD PACS/ eRAD RIS/PACS Software Product meet user needs and indications for use. Testing demonstrated that the eRAD PACS/ eRAD RIS/PACS Software Product were substantial equivalent to their predicate devices." (Page 2)
    • Conclusions: "The information provided in this premarket notification submission has shown that the eRAD PACS/ eRAD RIS/PACS Software Product is substantially equivalent to the predicate devices and are safe and effective for its intended use." (Page 3)

    In essence, this 510(k) focuses on demonstrating that the eRAD PACS is functionally equivalent to its predicate, safe, and effective for its intended use as a PACS system, not on providing evidence of diagnostic accuracy comparable to an AI/CADe device.

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