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RO handpiece and AGNES RF handpiece of RFMagik Lite are intended for use in dermatologic and general surgical procedures for electrocoagulation and hemostasis.

RFMagik Lite is a medical device combined with RF current, to function as an electrosurgical device for use in dermatology and general surgical procedures. It is possible to select and change modes, parameters, outputs, etc. using the panel on the main body. It consists of the main device, LCD screen, two handpieces, single use electrodes, electrode pad, NE pad cable, food switch. There are two handpieces. RO handpiece and AGNES RF handpiece that delivers RF energy through the disposable electrode in the handpiece.

The provided FDA 510(k) clearance letter for RFMagik Lite does not contain information about specific acceptance criteria or a study that directly proves the device meets such criteria in terms of clinical performance or effectiveness. The document primarily focuses on demonstrating substantial equivalence to predicate devices through non-clinical testing (electrical, EMC, biocompatibility, sterility, shelf life, and performance bench testing) and an ex vivo study.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

No specific acceptance criteria in terms of clinical performance metrics (e.g., success rates, complication rates, or comparative outcomes) are mentioned in the document for the RFMagik Lite. The "performance testing" referenced is primarily bench testing to ensure the device operates safely within design specifications. The acceptance criteria for the non-clinical tests are implicit in the adherence to recognized standards.

2. Sample Size Used for the Test Set and Data Provenance

The document does not specify a "test set" in the context of clinical or human subject data. The testing mentioned is non-clinical (bench, ex vivo). For the ex vivo study, the number of tissue types used was three (liver, skin, and muscle), but the specific number of samples or specimens within each tissue type is not provided.

The provenance of this ex vivo data would be laboratory-based, focusing on tissue samples rather than human subjects. The country of origin for the ex vivo study is not explicitly stated, but the submission is from a South Korean company.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

Since there is no mention of a clinical "test set" or human subject data, there is no information about experts establishing ground truth for such a set. The ex vivo study would likely involve experts in histology or pathology for evaluating thermal effects, but their number and qualifications are not detailed.

4. Adjudication Method for the Test Set

Not applicable, as there is no described clinical "test set" requiring adjudication.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

Not applicable. The RFMagik Lite is an electrosurgical device for cutting and coagulation, not an AI-assisted diagnostic or imaging device that would typically undergo an MRMC study comparing human reader performance with or without AI assistance.

6. If a Standalone (i.e., Algorithm Only Without Human-in-the-Loop Performance) Was Done

Not applicable. The RFMagik Lite is a physical electrosurgical device, not a standalone algorithm.

7. The Type of Ground Truth Used

For the non-clinical testing, the "ground truth" is defined by the adherence to and successful completion of recognized consensus standards (e.g., AAMI ES60601-1, IEC60601-2-2 for electrical safety, ISO 10993 for biocompatibility). For the ex vivo study, the "ground truth" would likely be the observed thermal effects on the tested tissues, assessed against predetermined safety or efficacy thresholds (though these thresholds are not explicitly stated in the document).

8. The Sample Size for the Training Set

Not applicable. This device is not an AI/ML algorithm that requires a training set.

9. How the Ground Truth for the Training Set Was Established

Not applicable, as there is no training set for an AI/ML algorithm.

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AGNES is indicated for use in dermatological and general surgical procedures for electrocoagulation and hemostasis.

AGNES is a RF electrosurgical device. It consists of LCD screen, radiofrequency generator and SMPS. The accessories are a footswitch, a hand-piece, single use RF electrodes and FDA cleared Disposable neutral electrode pad (K102372).

The provided text describes a 510(k) summary for the AGNES RF electrosurgical device. It primarily focuses on demonstrating substantial equivalence to a predicate device, particularly for newly added electrode models. However, it does not explicitly detail acceptance criteria or a comprehensive study proving the device meets specific performance thresholds in a clinical or AI-assisted context.

The document is a K223805 510(k) submission for an electrosurgical cutting and coagulation device. The key information is about the device's technical specifications and the comparison of the subject device (AGNES with additional electrode models) to its predicate device (AGNES with a previously cleared electrode model).

Based on the provided text, a robust study proving the device meets acceptance criteria, especially in the context of an AI/human-in-the-loop diagnostic accuracy study, is NOT present. The document describes a bench testing and an animal testing study to demonstrate the safety and effectiveness of the device as an electrosurgical tool, but not a study designed to evaluate diagnostic performance or human reader improvement with AI assistance.

Therefore, many of the requested sections regarding acceptance criteria and performance in a diagnostic or AI-assisted context cannot be directly answered from the provided text.

Here's an analysis of what CAN be extracted or inferred from the document regarding its performance in the context of a 510(k) submission, and what cannot:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't provide a typical "acceptance criteria" table for diagnostic performance metrics (e.g., sensitivity, specificity, AUC). Instead, the "acceptance criteria" can be inferred from the comparison table demonstrating substantial equivalence to the predicate device and the results of the bench and animal testing.

2. Sample Size Used for the Test Set and Data Provenance:

• Test Set (for performance validation of the electrosurgical function):
  • Bench Testing: Not explicitly stated as a "sample size" of devices, but implies testing of the subject device and its new accessories against electrical safety and performance standards (IEC 60601-2-2:2017).
  • Animal Testing: Tissues from 3 mini pigs were used for thermal tissue spread experiment (skin, liver, kidney, femoral muscle). Skin from 1 mini pig was used for histopathological analysis. This is not a "test set" in the context of an AI/diagnostic study, but for evaluating the physical tissue effects of the electrosurgical device.
• Data Provenance: The studies were conducted by AGNES Medical Co., Ltd, based in Korea. The provenance of the specific test data for the animal study is "mini pig tissues." It would be considered prospective for the device's validation.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Those Experts:

• This question is not applicable to the provided document. The document describes a medical device (electrosurgical unit), not a diagnostic AI system requiring expert consensus for ground truth establishment. The "ground truth" in this context relates to the physical and biological effects of the electrosurgical energy, evaluated through standard engineering tests and pre-clinical animal studies. Histopathological analysis for the animal study would typically involve a veterinary pathologist, but their number and specific qualifications are not detailed.

4. Adjudication Method for the Test Set:

• Not applicable in the context of diagnostic AI. For the animal study, the evaluation methods were "Thermal imaging area analysis, the maximum temperature, the time to reach basal temperature, and histopathological analysis." Adjudication among human readers is not relevant here.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done and the effect size of how much human readers improve with AI vs without AI assistance:

• No, an MRMC study was NOT done. This type of study is relevant for diagnostic AI devices where human readers interpret medical images. The AGNES device is an electrosurgical cutting and coagulation device, not an image interpretation or diagnostic AI tool.

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

• Not applicable. The AGNES device is not an algorithm or AI system. It's a hardware medical device used by a human operator. Its performance is inherent in its electrosurgical capabilities, not in an independent software algorithm.

7. The Type of Ground Truth Used:

• Bench Testing: Engineering measurements against established performance standards (e.g., output power, frequency, safety parameters).
• Animal Testing: Direct measurement of physical effects on biological tissues (thermal imaging, temperature readings, histopathological analysis). This is a form of direct biophysical ground truth.

8. The Sample Size for the Training Set:

• Not applicable. The AGNES device is not an AI/ML device, so there is no "training set" in the context of machine learning. Its design and efficacy are based on established electrosurgical principles and engineering/biological validation, not on learned patterns from a dataset.

9. How the Ground Truth for the Training Set was Established:

• Not applicable, as there is no training set.

In summary: The provided 510(k) summary focuses on demonstrating the substantial equivalence of an electrosurgical device, particularly regarding the addition of new electrode models, to its predicate. The "studies" mentioned (bench and animal testing) are for validating the physical and biological safety and performance of the electrosurgical function, not for evaluating diagnostic accuracy or AI-assisted human performance, which are the typical contexts for the detailed questions about acceptance criteria and ground truth in your prompt.

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AGNES is indicated for use in dermatological and general surgical procedures for electrocoagulation and hemostasis.

AGNES is a RF electrosurgical device. It consists of LCD screen, radiofrequency generator and SMPS. The accessories are a footswitch, a hand-piece, FDA cleared Single use needle type RF electrodes (K171707) and FDA cleared Disposable neutral electrode pad (K102372).

The provided text is a 510(k) summary for the AGNES RF electrosurgical device. It outlines changes made to an existing device (K160469) and asserts substantial equivalence to meet FDA requirements. However, this document does not contain the acceptance criteria or a study proving device performance against such criteria for a diagnostic or AI-driven device.

This 510(k) summary focuses on demonstrating that modifications made to an existing RF electrosurgical device (AGNES) do not negatively impact its safety and effectiveness compared to the predicate device. It primarily covers design changes, software changes, and performance testing related to international standards for electrosurgical equipment.

Therefore, I cannot provide the requested information from the given text as it is not present. The document focuses on regulatory compliance for modifications to an electrosurgical device, not on diagnostic performance or AI model validation studies.

Here's why the requested information cannot be extracted:

• Acceptance Criteria & Reported Performance: There are no specific acceptance criteria for a diagnostic device or AI system in this document. The "performance" discussed relates to the electrosurgical unit's output power levels, operating time, and compliance with general safety standards for electrosurgical devices (e.g., IEC 60601-2-2).
• Sample Size & Data Provenance (Test Set): No test set for an AI model or diagnostic performance is mentioned. The "tests" performed are for hardware changes and software validation of the electrosurgical unit.
• Number of Experts & Qualifications (Ground Truth): Not applicable, as there's no diagnostic ground truth being established or evaluated.
• Adjudication Method: Not applicable.
• Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: Not applicable.
• Standalone Performance: The "standalone" performance mentioned refers to the electrosurgical unit functioning by itself, not an AI algorithm.
• Type of Ground Truth: Not applicable; there is no diagnostic ground truth.
• Sample Size (Training Set): Not applicable; no AI model training is mentioned.
• Ground Truth for Training Set: Not applicable.

In summary, the provided FDA 510(k) notification is for a physical medical device (an electrosurgical unit) and its modifications, not for a diagnostic device or AI system that would have the types of performance studies and acceptance criteria you're asking about.

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