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510(k) Data Aggregation

    K Number
    K192936
    Device Name
    Soltus 500
    Manufacturer
    Date Cleared
    2019-11-15

    (28 days)

    Product Code
    Regulation Number
    892.1720
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    Soltus 500

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

    Intended for use by a qualified/trained doctor or technician on both adult and pediatric subjects for taking diagnostic radiographic exposures of the skull, spinal column, extremities, and other body parts. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position. Not for mammography

    Device Description

    The Soltus 500 Mobile Digital X-Ray System, Model 10501, ("Mobile X-Ray System") is the same as the predicate mobile PhoeniX with 2 additional features, (i) Distributed Antenna System (DAS), and (ii) Enhanced Work Flow (EWF). The Mobile X-Ray System has motorized movement and full battery operation. It contains a touch screen that operates as a control console. The Mobile X-Ray System supports various Canon flat panel detectors (Digital Radiography CXDI) supplied with the unit.

    AI/ML Overview

    The provided text is a 510(k) Summary for the Soltus 500 mobile X-ray system. This document focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study to prove meeting specific acceptance criteria for performance metrics typically associated with AI/CADe devices.

    Therefore, many of the requested elements for acceptance criteria and study details (like sample size for test/training sets, expert qualifications, adjudication methods, effect size of human readers with AI, ground truth details) are not applicable or findable in this type of submission.

    Here's a breakdown based on the information available in the provided text:

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

    The document doesn't present specific performance metrics or acceptance criteria in the typical sense of an AI/CADe device. Instead, the "acceptance criteria" are implied by demonstrating substantial equivalence to a predicate device and compliance with relevant safety and performance standards.

    Acceptance Criteria (Implied)Reported Device Performance
    Safety and Effectiveness (equivalent to predicate)"The results of bench testing indicates that the new device is as safe and effective as the predicate device."
    "Proper system operation is fully verified upon installation."
    "We verified that the modified combination of components worked properly and produced diagnostic quality images as good as our predicate generator/panel combination."
    "The Soltus 500 Battery Mobile X-Ray Units have been tested to be in compliance with the following International Standards: IEC 60601-1, IEC 60601-1-2, IEC 60601-1-3, IEC 60601-2-54, IEC 60601-2-28, IEC 60601-1-6, IEC 62304."
    Technological Characteristics (substantially the same)See the "Substantial Equivalence Chart" (Page 4-5) which details that most characteristics (Indications for Use, Configuration, X-ray Generator(s), Collimator, Digital X-ray Panel Supplied, Software, Panel Interface, Meets US Performance Standard, Power Source) are "SAME" as the predicate K192011. The differences (Computer, Wireless Antennas) are described as improvements (EWF, DAS) that do not impact safety or effectiveness.
    Firmware and Cybersecurity Validation"Firmware was validated according to the FDA Guidance: Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices Document issued on: May 11, 2005."
    "Because the system uses Wi-Fi and Ethernet, we observed the recommendations contained in the FDA Guidance Document: Content of Premarket Submissions for Management of Cybersecurity in Medical Devices Guidance for Industry and Food and Drug Administration Staff Document Issued on: October 2, 2014."
    Diagnostic Quality Images"produced diagnostic quality images as good as our predicate generator/panel combination."
    Compliance with relevant standardsIEC 60601-1:2005+A1:2012 (Edition 3.1)
    IEC 60601-1-2:2014 (Edition 4.0)
    IEC 60601-1-3:2008+A1:2013 (Edition 2.1)
    IEC 60601-2-54:2009+A1:2015 (Edition 1.1)
    IEC 60601-2-28:2010 (Edition 2.0)
    IEC 60601-1-6:2010 + A1:2013 (Edition 3.1)
    IEC 62304:2006 + A1:2016 (Edition 1.1)

    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    • Not applicable/Not provided. This device is a mobile X-ray system, not an AI/CADe device that performs diagnostic analysis on images. The evaluation primarily involved bench testing of the hardware and software components, and comparison to the predicate device. Clinical testing was explicitly stated as "not required."

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

    • Not applicable/Not provided. No clinical ground truth was established as clinical testing was not required.

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

    • Not applicable/Not provided. No adjudication method was used as no clinical test set requiring ground truth was established.

    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

    • No. This was not an AI/CADe device, and therefore no MRMC study was performed.

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

    • Not applicable. This device is an X-ray imaging system, not a diagnostic algorithm.

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

    • Not applicable/Not provided. No clinical ground truth was used for evaluation. The "ground truth" for the device's functionality was based on engineering specifications, performance standards, and comparison to the predicate device's established performance, verified through bench testing.

    8. The sample size for the training set

    • Not applicable/Not provided. This is a hardware system, not an AI/ML algorithm that requires a training set.

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

    • Not applicable/Not provided. This is a hardware system; there is no training set or ground truth in this context.
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