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To be used with the MEHL Chromos 694 Ruby Laser for the removal of unwanted body and facial hair.

The ChromoScan is a scanner which is used with the Chromos 694 Ruby Laser for the removal of unwanted body and facial hair. The hand held ChromoScan attachment enables treatment of multiple, rather than single hairs, thereby increasing efficiency and adding to the safety of the parent laser. The unit lays down a mathematically precise treatment grid whereby overlap is reduced and thermal recovery time is optimized. It is expected to lessen potential operator error by diminishing the time and tedium associated with one-hair-at-a-time hair removal procedures. Moreover, safeguards within the Chromos 694's intrinsic software insure that the scanner's fluences do not exceed those of the basic laser, i.e., no more than 20J/cm . ChromoScan is substantially equivalent to the other laser delivery attachment, the fiber optic handpiece. Both produce the same spot size, 7mm, and energies, as shown by computergenerated thermographic profiles.

This document is a 510(k) summary for the ChromoScan Scanner, an attachment for a ruby laser used in hair removal. The document focuses on demonstrating substantial equivalence to a predicate device, rather than providing detailed acceptance criteria or a comprehensive study report on device performance against specific metrics. Therefore, many of the requested details are not present in the provided text.

Here is an analysis based on the available information:

1. Table of acceptance criteria and the reported device performance

2. Sample sized used for the test set and the data provenance

The document mentions "Preliminary use of the ChromoScan on subjects in Europe."

• Sample size: Not specified.
• Data provenance: Europe, prospective (implied, as it refers to "preliminary use").

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

Not specified. The document does not describe a formal ground truth establishment process by experts for performance metrics, but rather a general safety observation during preliminary use.

4. Adjudication method for the test set

Not applicable/Not specified. The preliminary use observation for safety does not describe an adjudication method for data.

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 a laser scanner attachment for hair removal, not an AI-assisted diagnostic tool.

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

This concept is not directly applicable to a physical medical device like a laser scanner. However, the document emphasizes the scanner's ability to "lessen potential operator error" and lay down a "mathematically precise treatment grid," suggesting that the device's design aims to standardize and improve consistency of treatment application, which could be considered an autonomous function of the device's mechanics/software. There is no specific standalone performance study described for this aspect.

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

For the safety aspect, "no concerns about safety" from preliminary use serves as an informal "ground truth" derived from observation. For technical specifications (spot size, energy), computer-generated thermographic profiles are used for comparison, implying a technical ground truth. There is no mention of pathology or broader outcomes data for the scanner itself.

8. The sample size for the training set

Not applicable. This is a physical device and an attachment, not an AI model that requires a training set.

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

Not applicable.

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The Chromos 694 (MEHL) Ruby Laser, Mark I, is indicated for the removal of unwanted body and facial hair.

The Mark I Chromos 694 Ruby Laser is a laser instrument used in medical practice for the removal of unwanted body and facial hair.

The provided text describes a 510(k) premarket notification for the "Chromos 694 Ruby Laser for Hair Removal," seeking substantial equivalence to a predicate device, the "MEHL Ruby Laser for Hair Removal." It does not contain information about specific quantitative acceptance criteria or a dedicated study designed to prove the device meets these criteria in the way typically expected for a new medical device approval with performance metrics like sensitivity, specificity, or accuracy.

Instead, the submission focuses on demonstrating substantial equivalence through:

1. Engineering data: Showing similarity in light delivery characteristics.
2. Calculations: Proving essentially equivalent fluences for the different spot sizes (5mm vs. 7mm).
3. Thermographic profiles: Comparing the optical fiber (new device) to the articulated arm (predicate device).
4. Improvements in safety and reliability: Listing features like the elimination of the Q-switched option, replacement of the articulated arm with optical fiber, larger spot size, and software-directed controls with shutdown provisions.

The clinical data mentioned refers to studies performed on the predicate device, not the new Chromos 694 Ruby Laser. The conclusion is that "With the similarity in technical characteristics between the MEHL Ruby Laser and the Chromos 694 Ruby Laser, equivalence in clinical performance can therefore be assured, with more safeguards, better control and increased reliability intrinsic to the newer model."

Therefore, most of the requested information regarding acceptance criteria and a study proving the device meets those criteria is not present in the provided document, as the submission strategy relies on demonstrating substantial equivalence to a previously approved device, rather than new, independent clinical efficacy/safety trials with pre-defined performance endpoints.

Here's a breakdown of what can be extracted and what is not available based on your request:

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

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

• Sample Size: Not specified. The clinical safety data mentioned refers to studies with the predicate device ("In clinical studies with the MEHL Ruby Laser..."), but the number of subjects or cases is not provided.
• Data Provenance: Not specified. It's implied to be clinical data from the predicate device, but no details on country, retrospective/prospective nature are given.

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)

• This information is not provided. The document relies on technical similarity and historical clinical safety data of the predicate, not a new clinical study with a ground truth established by experts specifically for the Chromos 694 Ruby Laser.

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

• Not applicable/Not specified. No new clinical trial with expert adjudication is described for the Chromos 694 Ruby Laser.

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 a laser for hair removal, not an AI-assisted diagnostic tool involving human "readers."

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

• Not applicable. This is a hardware medical device (laser), not an algorithm.

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

• For the predicate device's clinical safety, the "ground truth" implicitly referred to observed clinical outcomes (e.g., "no scarring or purpuric reactions were observed," "hyper- and hypopigmentation... resolved predictably"). For the new device, the "ground truth" for its equivalence claim relies on engineering and technical data demonstrating similarity to the predicate, ensuring comparable performance.

8. The sample size for the training set

• Not applicable. This is a hardware device submission, not an AI/machine learning algorithm that requires a "training set."

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

• Not applicable. (See #8)

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