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510(k) Data Aggregation

    K Number
    K152332
    Date Cleared
    2016-02-25

    (191 days)

    Product Code
    Regulation Number
    878.4810
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    Perfectio LED infrared device

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

    Perfectio LED infrared device is an over the counter device indicated to emit energy in the red and IR region of the spectrum for use in dermatology for the treatment of periorbital wrinkles.

    Device Description

    Perfectio LED infrared device is a battery operated device that uses low power light spectrum at red and infrared LED, at wavelength of 633 ±5nm, 830 ±5nm emitting optical power in a uniform distribution with no hot spots. The device is composed of a handpiece for delivery of light energy, base unit for charging and storage when not in use, and A.C. charging adapter. It is a hand held light emitting diode (LED) device for the treatment of periorbital wrinkles designed for home-use.

    AI/ML Overview

    This document, an FDA 510(k) Premarket Notification Summary for the "Perfectio LED Infrared Device," does not include specific acceptance criteria for device performance based on a clinical study, nor does it detail a study that proves the device meets such criteria in the way a clinical study typically would. Instead, the submission relies on demonstrating substantially equivalent (SE) to a predicate device through non-clinical testing and shared indications for use.

    Here's an analysis based on the provided text, addressing your points where possible:

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

    The document does not present acceptance criteria for clinical performance (e.g., a specific percentage reduction in wrinkles, or a statistical improvement over a control). Instead, it establishes substantial equivalence based on:

    • Identical Indications for Use: Both the predicate and proposed device are "indicated to emit energy in the red and IR region of the spectrum for use in dermatology for the treatment of periorbital wrinkles."
    • Similar Technological Characteristics: Wavelengths, light source (LED), waveform, handheld nature, and materials are the same or very similar.
    • Compliance with Safety Standards: The device met several IEC and AAMI/ANSI standards related to electrical safety, electromagnetic disturbances, home healthcare environment, and photobiological safety.
    • Biocompatibility: Patient contact materials (ABS and stainless steel 304) were tested and found to meet ISO biocompatibility standards (cytotoxicity, irritation, delayed-type hypersensitivity).
    • Usability/Label Comprehension:
      • Acceptance Criteria (Implied): A high percentage of participants (stated as 100% for setup/operation, 95% for questionnaire) can correctly perform critical tasks and understand labels.
      • Reported Performance:
        • 100% of 35 participants correctly self-selected, demonstrated setup, light sensitivity test, operation, and cleaning.
        • 95% of 35 participants correctly answered each question on the questionnaire.

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

    • Non-Clinical Tests (Bench Tests/Standards Compliance): No "test set" in the sense of patient data is mentioned for these. These are typically laboratory-based tests on the device itself.
    • Usability/Label Comprehension Study:
      • Sample Size: 35 participants.
      • Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). This would generally be considered prospective data collection for a usability study.
    • Clinical Data: The document explicitly states: "Clinical data was not included in this submission." This means there was no patient-based performance study to demonstrate efficacy for wrinkle treatment. The reliance is on non-clinical data and equivalence to the predicate.

    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 in this Context: Since no clinical data was submitted, there was no clinical "ground truth" to establish for device performance on patients.
    • For the usability study, "ground truth" would be the objectively correct way to perform tasks or answers to questions, established by the study design and device manufacturer, not independent experts in the same way clinical data is adjudicated.

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

    • Not Applicable: No clinical test set requiring expert adjudication was performed.
    • For the Usability Study, "adjudication" (e.g., if a participant performed a step correctly) would be determined by the study observers following a predefined protocol, not by independent expert concensus.

    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

    • Not Applicable: This device is not an AI-assisted diagnostic tool, and no clinical comparative effectiveness study (MRMC or otherwise) involving human readers was mentioned. The device is a direct-treatment device.

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

    • Not Applicable: This refers to the performance of a software algorithm. The "Perfectio LED Infrared Device" is a hardware device for direct light therapy, not an algorithm.

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

    • Not Applicable for Clinical Efficacy: As clinical data was explicitly excluded, there was no ground truth for "treatment of periorbital wrinkles" established for this submission. The "ground truth" for the non-clinical tests revolved around meeting engineering and safety specifications (e.g., actual vs. required power output, successful completion of usability tasks).

    8. The sample size for the training set

    • Not Applicable: This device is a hardware device for light therapy, not a machine learning model that requires a training set.

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

    • Not Applicable: As above, no training set for a machine learning model was used.
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