(88 days)
The LUMA™ Light System is an Ultraviolet Light Emitting Medical Device. It is intended for use in localized phototherapeutic treatment of dermatologic conditions such as psoriasis, vitiligo, atopic dermatitis (eczema), sebhoic dermatitis, and leukoderma on all skin types (I-VI).
The Luma Light System is a phototherapy system intended to treat dermatological conditions such as psoriasis. The system includes a light module, an Android Nexus 4 phone, a software-based phone application (app), and a device charger. The light module contains light emitting diodes (LEDs), which create an array of narrowband UVB light centered at a wavelength between 300 - 320 nm. The light module attaches to a dressing applied to the patient's affected skin to allow for passive dosing of the lesion. This is a home use device intended to be used and operated by the patient (see technical specifications for environmental limitations). A physician will determine the dose and frequency of treatment. The app is then used by the patient to deliver treatments, provide treatment reminders and store data about prior treatments.
The provided text describes the Luma Light System, a phototherapy device for dermatological conditions, and its substantial equivalence to a predicate device (Skylit Phototherapy System, K170489). However, it does not contain specific acceptance criteria, reported device performance metrics in numerical form, or details about a study designed to prove the device meets acceptance criteria using a test set with ground truth.
The document primarily focuses on establishing substantial equivalence based on similar indications for use, principles of operation, fundamental technological characteristics, and user interface compared to the predicate device. It lists general performance testing conducted to verify functional and performance requirements but does not provide results.
Therefore, many of the requested details cannot be extracted from this document as they are not present.
Here's a breakdown of what can and cannot be answered based on the provided text:
1. A table of acceptance criteria and the reported device performance
- Cannot be provided. The document states that the device underwent "software, electrical, and mechanical testing in accordance with the following industry standards" to "verify that device design meets its functional and performance requirements." However, it does not specify what those functional and performance acceptance criteria were (e.g., minimum power output, wavelength accuracy, duration consistency) nor does it report the actual performance results obtained from these tests in a quantifiable manner.
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Cannot be provided. The document mentions "representative samples of the device underwent software, electrical, and mechanical testing," but it does not specify the sample size of these devices, the type of data provenance, or if there was a separate "test set" for performance evaluation against acceptance criteria as might be done for an AI/algorithm-driven device.
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)
- Cannot be provided. This question is highly relevant to studies involving AI or diagnostic devices where human expert consensus is used to establish ground truth for evaluating performance. The Luma Light System is a phototherapy treatment device, not a diagnostic one or an AI algorithm for interpreting data. The document describes performance testing of the device hardware/software, not a clinical study involving human readers or a ground truth established by experts in the context of diagnostic accuracy.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Cannot be provided. Similar to point 3, this is relevant to studies evaluating diagnostic accuracy, often with human interpretation. This document does not describe such a study.
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
- Cannot be provided. This type of study (MRMC, AI assistance) is not applicable to the Luma Light System as described. It is a phototherapy device, not an AI-assisted diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Cannot be provided. While the device has an app and software, the performance testing mentioned is for the device's functional integrity as a phototherapy system (electrical, mechanical, software adherence to standards), not for a standalone diagnostic algorithm's performance.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Cannot be provided. As the document describes engineering verification testing (software, electrical, mechanical) rather than a clinical accuracy study, the concept of "ground truth" as typically applied in diagnostic or AI evaluations is not present. The "ground truth" for the engineering tests would be the specified requirements and standards themselves.
8. The sample size for the training set
- Cannot be provided. This information pertains to machine learning models. The Luma Light System is a hardware device with an app, not explicitly described as using a machine learning model that requires a distinct "training set." The software mentioned is for delivering treatments, providing reminders, and storing data, not for learning or making diagnostic predictions.
9. How the ground truth for the training set was established
- Cannot be provided. As there's no mention of a training set for an AI model, this question is not applicable.
§ 878.4630 Ultraviolet lamp for dermatologic disorders.
(a)
Identification. An ultraviolet lamp for dermatologic disorders is a device (including a fixture) intended to provide ultraviolet radiation of the body to photoactivate a drug in the treatment of a dermatologic disorder if the labeling of the drug intended for use with the device bears adequate directions for the device's use with that drug.(b)
Classification. Class II.