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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):

• IEC 60601-1:2005, IEC 60601-1:2005/AMD1:2012, IEC 60601-1:2005/AMD2:2020 (Basic safety and essential performance)
• IEC 60601-1-2:2014 (Electromagnetic disturbances)
• IEC 60601-2-2 (HF surgical equipment particular requirements)
• IEC 60601-1-6:2013 (Usability) |
  | Software | Software verified and validated to a moderate level of concern, adhering to software lifecycle processes. | Evaluated according to IEC 62304:2006. |
  | Usability/Human Factors | Application of usability engineering to medical devices. | Evaluated in accordance with IEC 62366:2008 based on Human Factor Engineering. |
  | Biocompatibility | Materials in contact with patients are biocompatible. | Documented in reference to ISO 10993-1:2009, ISO 10993-5:2009, and 10993-10:2010. |
  | Bench Testing Performance | Device operates safely and within predefined design specifications, demonstrating intended function for electrocoagulation and hemostasis. | Bench testing conducted to assure safe operation and adherence to design specifications. |
  | Ex Vivo Thermal Testing | Performance in tissue coagulation and hemostasis, particularly regarding thermal effects. | Ex Vivo testing conducted on three types of tissue under GLP Thermal testing in accordance with FDA guidance "Premarket Notification (510(k)) Submissions for Electrosurgical Devices for General Surgery". |
  | Risk Management | Risks identified, analyzed, and controlled. | Risk analysis conducted based on ISO 14971:2019. |
  | Substantial Equivalence | Device is as safe and effective as a legally marketed predicate device, with no new questions of safety or effectiveness raised by differences. | Compared to predicate device K230663. All key parameters (output energy type, user interface, operating frequency, max power, electrode tip types, temperature range, impedance, coolant solution, communication) were found to be substantially equivalent. Minor differences in electrode tip styles and number of tips were deemed not to affect performance or safety. |

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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The POTENZA is intended for use in dermatologic and general surgical procedures for electrocoagulation and hemostasis.

The POTENZA is an RF (radiofrequency), software-controlled electrosurgical device used for electrocoagulation of soft tissue and hemostasis. The POTENZA consists of the following components: Electrosurgical Unit - Main body, Two different handpieces ( motor and AC), Six different electrode tips for the motor handpiece and three needle tips for the AC handpiece; provided as single use, sterile products, Neutral electrode pad and neutral electrode pad cable, cleared under K092761, Handpiece stand, Foot switch, Power cord. The POTENZA generates radiofrequency (RF) energy by means of high RF at 1MHz or 2MHz. 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. The POTENZA has two operating modes: monopolar mode and bipolar mode.

This looks like a 510(k) summary for a medical device. Based on the provided text, the device in question is the "POTENZA," an RF electrosurgical device. However, the document does NOT contain information about acceptance criteria or a study proving the device meets those criteria in the way you've outlined for AI/CADe devices (i.e., sensitivity, specificity, reader studies, etc.).

This document describes the regulatory process for establishing substantial equivalence to a predicate device, which primarily relies on demonstrating that the new device has similar technological characteristics and performs comparably to devices already on the market. The performance data presented here are primarily engineering bench tests, electrical safety, biocompatibility, and software validation. These are standard tests for electrosurgical devices to ensure safety and functionality, not to evaluate diagnostic performance or AI algorithm effectiveness.

Therefore, many of the specific questions you've asked, particularly those related to AI/CADe system validation (sample sizes for test sets, data provenance, ground truth establishment, expert adjudication, MRMC studies, standalone performance), are not applicable to the information provided in this 510(k) summary for an electrosurgical device.

Here's a breakdown of what can be extracted, and why other parts are not present:

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

The document does not explicitly state "acceptance criteria" in the format of a clinical performance metric (like sensitivity or specificity) with a target value. Instead, the acceptance criteria are implicitly met by passing various engineering and biocompatibility tests.

Regarding the specific questions about AI/CADe validation:

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

   • Not applicable. This device is an electrosurgical unit, not an AI/CADe system that analyzes data like images. The "test set" here refers to physical components and the device itself undergoing engineering and biological safety tests.

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. Ground truth, in the context of AI/CADe, involves expert interpretation of data. For this electrosurgical device, "ground truth" relates to objective physical and biological properties measured by standardized tests (e.g., cytotoxicity assays, electrical measurements).

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

   • Not applicable. Adjudication is for resolving discrepancies in expert interpretations of data. This is not performed for physical device testing.

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 is not an AI-assisted diagnostic device.

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

   • Not applicable. This is not an AI algorithm. Its performance is evaluated as a standalone electrosurgical unit through bench and safety tests.

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

   • The "ground truth" for the tests performed are highly standardized scientific and engineering measurements. For example, for biocompatibility, the ground truth is whether specific biological responses (e.g., cell death, irritation) occur above a predefined threshold according to the specified ISO standards. For electrical safety, the ground truth is whether the device parameters (e.g., leakage current, output power) fall within the limits set by IEC standards.

8. The sample size for the training set.

   • Not applicable. There is no AI training set for this electrosurgical device.

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

   • Not applicable. There is no AI training set or associated ground truth.

In summary, the provided document is a 510(k) summary for an electrosurgical device, detailing its regulatory pathway to market based on substantial equivalence. It focuses on safety and fundamental performance characteristics through engineering and biocompatibility testing, not on the diagnostic accuracy or AI performance metrics you've requested.

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