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510(k) Data Aggregation

    K Number
    K192176
    Device Name
    IntelePACS
    Date Cleared
    2020-04-02

    (234 days)

    Product Code
    Regulation Number
    892.2050
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K172490

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    IntelePACS is a software application that receives digital images and data from various sources (such as, CT scanners, MR scanners, ultrasound systems, R/F units, computer and direct radiographic devices, secondary capture devices, scanners, imaging gateways, or other imaging sources). Images and data can be communicated, processed, manipulated, enhanced, stored, and displayed within the system and/or across computer networks at distributed locations. Postprocessing of the images can be performed using Multi Planar Reconstruction (MPR). Only preprocessed DICOM for presentation images can be interpreted for primary image diagnosis in mammographic images with lossy compression and digitized film screen images must not be reviewed for primary image interpretations. Mammographic images may only be interpreted using an FDA cleared display that meets technical specifications reviewed and accepted by FDA.

    When used with a mobile device, IntelePACS is suitable for diagnostic image review only on tested devices as specified in Intelerad product documentation. IntelePACS is not intended for primary diagnostic image review on mobile devices. Mobile usage for Mammography is for reference and referral only.

    Device Description

    IntelePACS, (version 5), is based upon the predicate device IntelePACS, version 4.9.1 (K150707). Both the subject device and the predicate are from Intelerad Medical Systems Inc. IntelePACS is comprised of software modules that provide image capture, storage, distribution, enhancement, manipulation, and networking of medical images at distributed locations. In cases where DICOM images are not directly available to IntelePACS, the system can acquire medical images using a DICOM image gateway, which generates DICOM-type files. For example, film digitizers obtain images from original film and convert them to meet DICOM standards. Stored files are transmitted using a network and can be viewed or manipulated using InteleViewer viewing software.

    The main components are:

    • InteleViewer is an image viewing system, providing access to the tools required for reviewing images and searching to find studies and reports. InteleViewer features DICOM support, including DICOM Query/Retrieve, Store, and Print. The software module includes a thumbnail display, real-time cine playback, linked stacking, MPR, annotations and measurements, etc. The web-enabled InteleViewer software uses JPEG 2000 compression and an advanced streaming protocol to provide lossless or lossy image viewing and manipulation. The user can examine multiple studies simultaneously and define customized image layouts. With a mouse click, the User can stack, rotate, zoom, take measurements, and view reports.
    • InteleConnect Enhanced Viewer (used on Mobile Devices) is a web-based portal for medical images review that can be used on the desktop and on mobile devices without requiring software installation. This is a new module which is not in the Primary Predicate but is available in the Reference Predicate device.
    • InteleBrowser which is a web-based administrative interface for IntelePACS, and allows the facility System Administrator to customize and configure the facility radiological workflow and corporate branding. The System Administrator can administer hundreds or thousands of IntelePACS users by taking advantage of the user management and access granting tools.
    AI/ML Overview

    The provided text describes the 510(k) summary for IntelePACS, focusing on its substantial equivalence to predicate devices and performance data for mobile device use. However, it does not contain a table of acceptance criteria or a detailed study proving the device meets specific performance criteria beyond general statements of compliance with standards and limitations for mobile displays.

    Here's what can be extracted and what is missing based on your request:

    1. A table of acceptance criteria and the reported device performance:

    This information is not explicitly provided in the document in the format requested. The document mentions that "Validation testing indicated that as required by the risk analysis, designated individuals performed all verification and validation activities and that the results demonstrated that the predetermined acceptance criteria were met." However, the specific acceptance criteria themselves and the detailed performance metrics are not listed in a table.

    The closest to "reported device performance" is the section on mobile device testing, which presents observations and measurements regarding:

    • Spatial Resolution: "Devices tested provide high resolution displays with high pixels per inch counts, with pixel pitch well below 250 um. ... All devices tested, satisfy this criterion."
    • Pixel Defects: "Devices were visually inspected for any pixel defects and none were detected."
    • Artifacts: "At the end of the test, a visual observation was performed and confirmed that no such occurrence of either artifact, for all devices tested."
    • Temporal Response: "All devices tested present a reasonable response time in the 40-60% luminance transitions, namely around 30ms or better."
    • Luminance: "Maximum luminance is well above 350 cd/m² for all devices tested."
    • Conformance to DICOM GSDF: "All devices tested only conform to DICOM GSDF within 20% over subsets of the JND range. While some mobile devices performed better than others, any one of the mobile devices did not fully satisfy the criteria." (This is a non-conformance with a subsequent mitigation.)
    • Color Tracking: "All values for △D65(u',v') are within acceptable range for all devices tested."

    2. Sample size used for the test set and the data provenance:

    • Sample size: Four specific mobile devices were tested: iPad Pro 2017, iPhone 8, iPhone XS, and iPad Air (2019). It's unclear if "devices tested" refers to a single unit of each model or multiple units.
    • Data provenance: Not explicitly stated, but the testing seems to be internal ("A test lab evaluated...") to the manufacturer or a contracted lab. The document does not specify the country of origin for the data or whether it was retrospective or prospective.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

    • Number of experts: Not mentioned.
    • Qualifications of experts: Not mentioned. The testing seems to be based on physical measurements and visual inspection against standards (AAPM TG18, AAPM report 270, AAPM report No.260), rather than expert consensus on diagnostic images.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

    • Adjudication method: Not applicable/not mentioned. The testing described is physical display characteristic assessment, not diagnostic image review requiring adjudication among readers.

    5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

    • An MRMC comparative effectiveness study was not conducted or described. This submission is for a PACS system, not an AI-assisted diagnostic tool.

    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

    • This is not applicable as IntelePACS is a PACS system for image management and viewing, not a diagnostic algorithm. The performance evaluation focuses on display quality.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

    • The "ground truth" for the mobile device display testing appears to be objective physical measurements and visual assessments against established industry standards and guidelines (e.g., pixel pitch, luminance, temporal response, adherence to DICOM GSDF, pixel defects, artifacts). It is not based on clinical "ground truth" like pathology or expert consensus on a disease state, as the device itself is not making a diagnosis.

    8. The sample size for the training set:

    • Not applicable. As a PACS system, IntelePACS does not involve a "training set" in the context of machine learning. Its functionality is based on established software engineering principles and adherence to standards like DICOM.

    9. How the ground truth for the training set was established:

    • Not applicable for the same reason as above.

    Summary of what's provided for acceptance criteria and study:

    The document states that IntelePACS "passed all predetermined testing criteria" and "met all the requirements listed in the Standards." For mobile devices, it lists specific objective measurements and observations (e.g., luminance, resolution, pixel defects) and whether the devices met those criteria, with one notable exception (DICOM GSDF conformance) for which mitigations were implemented. The study described is a technical assessment of display characteristics for specific mobile devices against generally accepted industry standards for medical displays, rather than a clinical trial measuring diagnostic accuracy.

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