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Radiofrequency Generator System is used in conjunction with Cura RF Electrode for coagulation of tissue during percutaneous, laparoscopic, and intraoperative surgical procedures.

The Cura RF Electrode is to be used with Radiofrequency Generator System intended for coagulation of tissue during percutaneous, laparoscopic, and intraoperative surgical procedures.

Radiofrequency Generator System consists of a genstaltic pump for electrode cooling, a foot switch and a respiratory locator. This Radiofrequency Generator System is used in conjunction with the Cura RF electrode for coagulation of tissue during percutaneous, laparoscopic, and intraoperative surgical procedures.

The Radiofrequency Generator System is capable of delivering up to 250 W of RF power is limited through software control, and the power, impedance, current are monitored by software. The temperature of the electrode's tip is monitored for charring.

The generator generates high frequency alternating current and transferred to the RF electrode and generator is interrupted, the generator will stop the power output and trigger reminder. When the temperature of RF electrode detected by the generator exceeds 99℃, or the temperature of the neutral electrode reaches the setting temperature, the device will automatically out off the power output and give a corresponding reminder. The power output can also be manually stopped.

This document is a 510(k) Premarket Notification from the FDA, a regulatory submission for a medical device. It does not describe an AI/ML-based device, but rather a Radiofrequency Generator System and Cura RF Electrode used for tissue coagulation. Therefore, many of the typical acceptance criteria and study details related to AI/ML performance (e.g., sample size for test set, number of experts, MRMC studies, ground truth establishment for training set, etc.) are not applicable or present in this type of submission.

Specifically, the document focuses on demonstrating substantial equivalence to existing predicate devices based on:

• Indications for Use: The devices have similar intended uses.
• Technological Characteristics: Comparison of physical specifications, operating principles, and safety features.
• Performance Data (Non-Clinical): Testing against recognized standards and ex-vivo tissue tests, rather than clinical efficacy studies on human subjects that would involve extensive human reader studies or large clinical trial data sets.

Therefore, the requested information cannot be fully provided as it pertains to AI/ML device evaluations, which is not the subject of this FDA submission.

However, I can extract the relevant information regarding the non-clinical performance data and the "acceptance criteria" presented in this type of regulatory context, which are primarily compliance with relevant medical device standards.

Here's a breakdown based on the provided document and the non-applicability of certain AI/ML-specific questions:

Acceptance Criteria and Device Performance for a Radiofrequency Generator System

The acceptance criteria for this device are not defined in terms of AI/ML performance metrics (like accuracy, sensitivity, specificity, AUC) but rather through compliance with established medical device safety and performance standards, and demonstration of heating effects in ex-vivo tissue that align with the intended function.

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

The "acceptance criteria" for this specific device (a radiofrequency generator and electrode) are primarily demonstrated through compliance with various national and international standards for electrical safety, electromagnetic compatibility, usability, biological compatibility, and sterilization. The "reported device performance" refers to the successful completion of these tests.

Also explicitly stated in the comparison table of Radiofrequency Generator System: "Complied with IEC 60601-1-2". |
| Usability | IEC 60601-1-6 Edition 3.1 2013-10 (Medical electrical equipment - Part 1-6: General requirements for basic safety and essential performance - Collateral standard: Usability) | "The test results demonstrated that the proposed device complies with the following standards:" |
| Biological Evaluation | ISO 10993-5 Third edition 2009-06-01 (Tests for in vitro cytotoxicity) | "The test results demonstrated that the proposed device complies with the following standards:" |
| | ISO 10993-10 Third Edition 2010-08-01 (Tests for irritation and skin sensitization) | "The test results demonstrated that the proposed device complies with the following standards:" |
| | ISO 10993-11 Third edition 2017-09 (Tests for systemic toxicity and Pyrogen test) | "The test results demonstrated that the proposed device complies with the following standards:" |
| Sterilization & Residuals | ISO 10993-7:2008 (Ethylene oxide sterilization residuals) | "The test results demonstrated that the proposed device complies with the following standards:" |
| | ISO 11135 Second edition 2014-07-15 [Including: Amendment 1 (2018)] (Sterilization of health-care products - Ethylene oxide - Requirements for the development, validation and routine control of a sterilization process for medical devices) | "The test results demonstrated that the proposed device complies with the following standards:" |
| | ISO 11137-2 Third edition 2013-06 [Including AMD1:2022] (Sterilization of health care products - Radiation - Part 2: Establishing the sterilization dose) | "The test results demonstrated that the proposed device complies with the following standards:" |
| Packaging & Shelf-life | ASTM F1980-16 (Standard Guide for Accelerated Aging of Sterile Barrier Systems for Medical Devices) | "The test results demonstrated that the proposed device complies with the following standards:" |
| Software Performance | IEC 62304:2015 and FDA guidance "Content of Premarket Submissions for Device Software Functions" (Software verification and validation testing for embedded software monitoring power, time, impedance, and temperature). | "Software verification and validation testing were conducted... to support enhanced level." (Implies successful completion and meeting requirements, as the device received 510(k) clearance). |
| Thermal Effects (Ex-vivo) | FDA Guidance 'Premarket Notification (510(k)) Submissions for Electrosurgical Devices for General Surgery' (Test on thermal effects to evaluate width and depth of thermally damaged zone in relation to active part length, gauge, working mode, and power setting on liver, kidney, and muscle tissue). | "The test on thermal effects was performed... The test results demonstrated that the proposed device complies with the following standards:" (implies the thermal effects were within expected/acceptable parameters to show equivalence for tissue coagulation, aligning with the FDA guidance). |

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

• Test Set Sample Size: For the non-clinical tests, sample sizes are not explicitly stated in the summary, but they would be typical for engineering verification and validation testing of medical devices according to the specified standards (e.g., a certain number of units for electrical tests, specific tissue samples for ex-vivo tests). These are typically small, controlled engineering samples, not large patient datasets.
• Data Provenance: The tests are likely performed by the manufacturer (Zhejiang CuraWay Medical Technology Co., Ltd. in China) or contract testing organizations on their behalf. The data is prospective in the sense that the tests were specifically conducted to support this submission.

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

This question is not applicable as this is not an AI/ML diagnostic device requiring expert consensus for "ground truth" on diagnoses. The "ground truth" for this device's performance is objective measurements (e.g., electrical parameters, temperature readings, physical dimensions of coagulation zones) and compliance with specified engineering and medical device standards.

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

This question is not applicable as it pertains to expert consensus/adjudication in diagnostic studies, which is not relevant for this type of device submission.

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 question is not applicable. An MRMC study is relevant for AI/ML diagnostic aids that assist human readers. This device is a therapeutic/surgical tool (radiofrequency generator), not a diagnostic AI.

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

This question is not applicable for the same reasons as above. The device's performance is its direct physical output (e.g., RF energy, coagulation effect), not an algorithm-only output like an AI diagnostic prediction. Its "standalone" performance is assessed through its compliance with technical standards and ex-vivo tests.

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

The "ground truth" for this device's performance is based on:

• Pre-defined technical specifications and ranges for electrical output, temperature monitoring, and safety features.
• The ability to achieve intended thermal effects (coagulation zone) in ex-vivo tissue models, compared against expectations from existing predicate devices and literature.
• Compliance with recognized national and international consensus standards (e.g., IEC, ISO, ASTM).

8. The sample size for the training set

This question is not applicable. This is not an AI/ML device that requires a "training set" in the machine learning sense. The device is a hardware system with embedded software, developed using traditional engineering principles and verified/validated against specifications and standards.

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

This question is not applicable for the reasons stated above.

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