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The CO2 Laser System is used for human tissue vaporization, coagulation in dermatoloty and plastic surgery, general surgery, gynecology, podiatry, dental and otorhinolaryngology.

The device emits CO2 laser at the wavelength of 10.6um, which is the spectral line in the far infrared range. The device is used for human tissue vaporization, coagulation in dermatology and plastic surgery, general surgery, gynecology, podiatry, dental and otorhinolaryngology.

This FDA 510(k) summary describes a CO2 Laser System by Beijing Superlaser Technology Co., Ltd. and seeks to demonstrate its substantial equivalence to a predicate device (K192528).

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

The document doesn't explicitly state "acceptance criteria" as a separate section with specific thresholds. Instead, the substantial equivalence is based on a comparison to a predicate device, showing that the proposed device performs "the same" or "similarly" across various specifications and complies with relevant safety standards.

Here's a table based on the "Performance Comparison" and "Safety Comparison" sections, with "Reported Device Performance" being the specifications of the Proposed Device and "Acceptance Criteria" being implicitly met if it's "SAME" or "SIMILAR" to the Predicate Device, or complies with established standards.

The study (non-clinical testing) states that "The test results demonstrated that the proposed device complies with the following standards" for safety and that "Non clinical tests were conducted to verify that the proposed device met all design specifications as was Substantially Equivalent (SE) to the predicate device." This implicitly means the device meets the acceptance criteria of conforming to the predicate device's performance characteristics and a set of recognized electrical, EMC, and laser safety standards.

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

• Sample size for the test set: Not applicable. The document describes non-clinical bench testing and software validation, not a study with a "test set" of patient data or images.
• Data provenance: Not applicable, as there isn't patient data/images involved in this type of submission. The tests are bench tests performed in a laboratory setting by the manufacturer. The company is based in Beijing, China.

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

Not applicable. This submission is for a CO2 Laser System that performs surgical functions, not an AI/imaging device requiring expert consensus for ground truth on diagnostic interpretations. The "ground truth" for this device would be its physical performance specifications and adherence to safety standards, verified through engineering tests.

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

Not applicable, as there is no "test set" in the context of clinical or image-based studies requiring adjudication.

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, an MRMC comparative effectiveness study was not done. The device is a physical CO2 laser system, not an AI diagnostic tool that assists human readers.

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

Not applicable. This is not an AI algorithm. The device performance is assessed through its physical operation and compliance with engineering standards.

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

The "ground truth" for this device's performance and safety is established through:

• Engineering specifications and measurements: Comparing output power, wavelength, spot size, etc., against the predicate device's documented specifications.
• Compliance with recognized international standards: IEC 60601-1, IEC 60601-2-22, IEC 60825-1, IEC 60601-1-2 for electrical, EMC, and laser safety.
• Bench Performance Tests: These would involve direct measurements of the device's output and function.
• Software Validation & Verification Test: Ensuring the control system software operates correctly according to its design specifications.

8. The sample size for the training set:

Not applicable. There is no training set as this is not an AI/machine learning device.

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

Not applicable. There is no training set.

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