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510(k) Data Aggregation

    K Number
    K213524
    Device Name
    CytonPro-5000
    Manufacturer
    Date Cleared
    2022-08-10

    (280 days)

    Product Code
    Regulation Number
    890.5500
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    CytonPro-5000

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

    The model CytonPro-5000 laser emits energy in the infrared spectrum to provide topical heating to elevate tissue temperature for temporary relief of muscle and joint pain, muscle spasm and stiffness associated with arthritis. It also increases blood circulation and relaxes muscle tissue.

    Device Description

    The CytonPro-5000 laser is a non-invasive, diode laser system consisting of an enclosure which contains the control unit and a treatment probe connected by an optic fiber.

    AI/ML Overview

    The provided text does not contain information about acceptance criteria and a study that proves the device meets those criteria in the context of diagnostic performance or human-in-the-loop studies. The document describes a 510(k) submission for an infrared lamp (CytonPro-5000), which is a physical therapy device used for topical heating and pain relief.

    The "studies" described are primarily non-clinical performance and safety testing to demonstrate substantial equivalence to a predicate device. This type of submission focuses on comparing the new device's technical specifications and safety profile to an already cleared device, rather than diagnostic accuracy or effectiveness trials involving human subjects to establish clinical improvement due to AI assistance.

    Here's a breakdown of why many of your requested items cannot be answered from the provided text:

    • Acceptance Criteria for Diagnostic Performance: Not applicable as this is not a diagnostic AI device. The "acceptance criteria" discussed are related to engineering specifications and safety standards.
    • Study Proving Device Meets Acceptance Criteria (Diagnostic Performance): Not applicable. The "proof" is based on non-clinical engineering tests.

    However, I can extract the information that is present concerning the device's characteristics and the testing performed:

    1. Table of Acceptance Criteria and Reported Device Performance

    The document doesn't present explicit "acceptance criteria" in the sense of a numerical threshold for clinical effectiveness or diagnostic accuracy. Instead, the "acceptance" is based on demonstrating substantial equivalence to a predicate device (Cell Gen CG-4000) through comparable performance characteristics and compliance with safety standards.

    Performance CharacteristicAcceptance Criteria (Predicate Device)Reported Device Performance (CytonPro-5000)
    Indications for UseTemporary relief of muscle and joint pain, muscle spasm and stiffness associated with arthritis; increases blood circulation and relaxes muscle tissue.Temporary relief of muscle and joint pain, muscle spasm and stiffness associated with arthritis; increases blood circulation and relaxes muscle tissue.
    Wavelength1064nm1064nm
    Spectral Width+/- 5 nm+/-5nm
    Beam Size40mm +/- 5mm50mm
    Max Output Power from Treatment Head20W20W
    Max Power Density1.6 W/ cm^2800mW/ cm^2 (less than predicate)
    CouplingIntegrated Fiber200um optical fiber
    Umbilical Length6 ft (2 meters)6 ft (2 meters)
    Minimum Bend Radius3 in. (75mm)3 in. (75mm)
    Expected Lifetime>5000 hrs> 25,000 hrs
    Max Input Power650VA180W (less than predicate)
    Input Voltage120 V, 60Hz 5A100-240VAC, 50/60 Hz
    Temperature Range (Device)20C~ 50C20C ~ 50C
    Temperature Range (Skin)30C~ 45C30C ~ 45C
    System Weight14kg (30.86lbs)4.8kg (lighter than predicate)
    Electrical Safety & CompatibilityCompliance with relevant standards (e.g., ANSI/AAMI ES60601-1, IEC 60601-1-2, etc.)Passed all electrical and safety testing according to national and international standards.
    Software Verification & ValidationAdherence to FDA guidance for software in medical devices.Conducted and documentation provided.
    Temperature Testing (Clinical Effect)Induced therapeutic topical heating and maintained controlled skin temperature within a specific range.Induced therapeutic topical heating on hand and foot of five subjects within 100 seconds (800mW/cm^2 setting) or four minutes (300mW/cm^2 setting), with controlled skin temperature.

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

    • Test Set Sample Size: For the temperature testing, "five subjects" were used.
    • Data Provenance: Not specified (e.g., country of origin, retrospective/prospective).

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

    • Not applicable/Not mentioned. The temperature testing involved direct measurement of physical effects (heating) on subjects, not expert interpretation for establishing ground truth for a diagnostic task.

    4. Adjudication method for the test set:

    • Not applicable/Not mentioned. This is not a study requiring adjudication of diagnostic findings.

    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 is not an AI diagnostic imaging device, and no MRMC study was performed or needed for this type of device.

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

    • Not applicable. This device is a physical therapy apparatus, not an AI algorithm performing a diagnostic task.

    7. The type of ground truth used:

    • For the temperature testing, the "ground truth" was direct physiological measurement (skin temperature elevation) in response to the device's energy emission, demonstrating its intended therapeutic heating effect. This is an outcomes data (physiological response) type of ground truth in the context of its function.

    8. The sample size for the training set:

    • Not applicable. This is not an AI/ML device that requires a training set in the conventional sense.

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

    • Not applicable. As above, this is not an AI/ML device requiring a training set.
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