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This device indicated for use in dermatologic and general surgical procedures for electrocoagulation and hemostasis.

The DENSITY, DENZA, DENSITY Noir generates radiofrequency (RF) energy by means of high RF at 6.78MHz. The RF energy is delivered through the skin into the target tissue via a handpiece equipped with an electrode tip. As the RF energy passes through the tissue, it generates an electrothermal reaction which is capable of coagulating the tissue. In detail, the main body uses the "reverse thermal gradient" principle to deliver RF energy, and thus, heat is generated and selective coagulation occurs while cooling the epidermis, resulting in denaturation and contraction of collagen fibers.

The devices are an RF (radiofrequency), software-controlled electrosurgical device used for electrocoagulation of soft tissue and hemostasis.

It consists of the following components:

• Electrosurgical Unit - Main body
• Handpiece
• electrode tips
• Neutral electrode pad and neutral electrode pad cable, cleared under K201685
• Foot switch
• Power cord

This document is a 510(k) clearance letter for an electrosurgical device, not a study report for an AI device. As such, most of the requested information regarding AI device acceptance criteria, study details, and performance metrics (like effect sizes for AI assistance, standalone performance, training sets, etc.) is not present in the provided text.

The device described, "DENSITY; DENZA; DENSITY Noir," is an electrosurgical cutting and coagulation device. The clearance is based on substantial equivalence to a predicate device (K230663), implying that its performance is expected to be similar to legally marketed devices based on established standards and non-clinical testing.

Here's a breakdown of the information that can be extracted from the provided text, along with an explanation of why other requested information is not available:

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

The document does not explicitly state "acceptance criteria" for performance that would be found in a typical AI device study (e.g., sensitivity, specificity, AUC thresholds). Instead, the acceptance is based on demonstrating substantial equivalence to a predicate device through adherence to recognized standards and non-clinical performance testing.

Acceptance Criteria (Implied by Substantial Equivalence and Standards Adherence):

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

This information is not provided as this letter describes non-clinical testing for an electrosurgical device, not a clinical study or AI performance evaluation. The "test set" here refers to the materials and conditions used for bench and ex-vivo testing. The document states:

• "Ex Vivo testing conducted on three types of tissue". No specific sample size (e.g., number of tissue samples) or provenance is mentioned beyond "under GLP Thermal testing."

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 applicable/not provided. Ground truth for an AI device is typically established by expert interpretation of medical images or data. For an electrosurgical device, performance is evaluated against engineering specifications, recognized safety standards, and physiological responses during ex-vivo testing, not by expert interpretation generating a "ground truth" in the same sense as an AI diagnostic.

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

This information is not applicable/not provided. Adjudication methods are used in studies involving human interpretation or labeling, especially for AI algorithm ground truth establishment. This is not relevant for the type of non-clinical testing described.

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

This information is not applicable/not provided. An MRMC study is relevant for evaluating the impact of AI assistance on human performance, typically in diagnostic imaging. The device in question is a standalone electrosurgical instrument and does not involve AI assistance for human readers.

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

This information is not applicable/not provided. This device is a manual electrosurgical instrument, not an AI algorithm. Therefore, "standalone algorithm performance" is not relevant.

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

For the non-clinical testing:

• Bench testing: Ground truth is defined by the device's technical specifications and engineering design (e.g., power output within tolerance, correct operating frequency).
• Ex Vivo testing: Ground truth would be the expected physiological effect (e.g., desired thermal coagulation) confirmed through histological examination or other scientific methods in the tissue samples. This is implied by "Ex Vivo testing conducted... under GLP Thermal testing."

8. The sample size for the training set

This information is not applicable/not provided. This device is an electrosurgical instrument, not an AI system that requires a "training set."

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

This information is not applicable/not provided for the same reason as point 8.

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