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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, single use needle type RF electrodes and FDA cleared Disposable neutral electrode pad (K102372).

This document, K203013, is a 510(k) summary for a medical device called AGNES, an RF electrosurgical device. It's a submission to the FDA to demonstrate substantial equivalence to a previously cleared device (K192728).

The document details changes made to the device and the testing performed to ensure safety and effectiveness. However, it does not contain any information regarding acceptance criteria or a study proving the device meets those criteria in the context of human clinical performance or AI algorithm performance. This is because K203013 is for an electrosurgical device, not an AI or imaging device that would typically have performance metrics like sensitivity, specificity, or reader improvement.

The tests performed are primarily bench tests, animal studies, and biocompatibility tests related to the physical changes made to the device (e.g., power input, connector color, and a new type of RF electrode). Therefore, I cannot fulfill your request for information on acceptance criteria and a study proving performance in the way you've outlined for an AI/imaging device.

To directly address your specific points, based on the provided document:

1. A table of acceptance criteria and the reported device performance: This document does not provide a table of acceptance criteria for clinical performance (e.g., sensitivity, specificity, accuracy) because it's not evaluating an AI or diagnostic imaging device in that manner. The "performance" discussed relates to electrical safety, electromagnetic compatibility, and thermal effects, for which the acceptance is successful compliance with recognized standards.

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

   • Bench Testing (Electrical Safety, EMC): These tests are typically performed on a sample of the manufactured device and new accessories. Sample size is not specified but would follow standard engineering testing practices for medical devices, often a small number of units.
   • Biocompatibility Testing: Tested on materials of manufacture and the final device. Sample size not specified.
   • Animal Testing: Conducted on tissues from 3 mini pigs for thermal tissue damage/spread, and skin from 1 mini pig for histopathological analysis.
   • Data Provenance: Not explicitly stated for specific test data, but the submitter is Agnes Medical CO., LTD in South Korea.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. The "ground truth" for this device's performance is established by compliance with engineering and biological safety standards (e.g., IEC standards, ISO standards for biocompatibility), not through expert consensus on diagnostic interpretations. For the animal study, histopathological analysis would be performed by a qualified pathologist, but the number and qualifications are not specified.

4. Adjudication method for the test set: Not applicable. There's no human interpretation or diagnostic decision-making being assessed by multiple readers that would require adjudication.

5. If a multi-reader, multi-case (MRMC) comparative effectiveness study was done: No. This is not an AI or diagnostic imaging device; therefore, an MRMC study is not relevant.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. This is not an AI algorithm.

7. The type of ground truth used:

   • Bench Testing: Engineering specifications and compliance with international standards (e.g., IEC 60601-1, IEC 60601-2-2, IEC 60601-1-2).
   • Biocompatibility: Compliance with ISO 10993 series standards.
   • Animal Testing: Histopathological analysis of tissue and thermal imaging measurements.

8. The sample size for the training set: Not applicable. This document does not describe an AI/ML device that requires a training set.

9. How the ground truth for the training set was established: Not applicable.

In summary, the provided document pertains to the regulatory clearance of an electrosurgical device based on engineering and biological safety standards, not an AI or diagnostic imaging device involving clinical performance metrics and reader studies.

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RF Surgical Generator FW-120A is an electrosurgical generator containing monopolar and bipolar technology. It is intended for use with accessories during surgical procedures where the surgeon requires electrosurgical cutting and coagulating.

RF Surgical Generator FW-120A, is a compact source of high power RF energy, enhanced capability of radiosurgery generator, which can be employed for a variety of radiosurgery procedures, such as cut and coagulate living human tissue.

The device which is consisted of a generator, an IEC Neutral Plate, and a Two Pedal Footswitch, provides 5 modes and corresponding output power ranges that is user/operator selectable based on the surgical procedure undertaken. The action is achieved by front panel selection of waveforms and power level. All selection is affected through push buttons and indicators which give the operator feedback of status. Power level for each mode is indicated by front panel digital displays

The device is provided with safety features of automatically system initialize self-check after power on and continuously monitored during the device running. The device will provide error information and/ or alerts when detect following faults, such as a) Accessary fail connection, b) Overheating of Main Unit, c) Neutral plates Contact resistance exceed the limit, d) System initialize error. The error monitoring is interlocked with the controls to prevent operation when fault condition happened in the unit.

The generator is configured for Monopolar and Biopolar output and the final output power could be controlled by pedal foot switch and/or hand switches. Recommended Monopolar Handpieces 510(k) No.: K092634. Recommended IEC Neutral Plate 510(k) No.: K102372.

This document is a 510(k) premarket notification for an RF Surgical Generator (Model: FW-120A) and focuses on demonstrating substantial equivalence to a predicate device, rather than providing details on a study to meet specific acceptance criteria for a new device.

Therefore, many of the requested categories about acceptance criteria, detailed study design, ground truth, and expert involvement are not applicable or not provided in this type of submission. This document primarily reports on verification testing against established standards and a comparison to a predicate device.

Here's a breakdown based on the information available in the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The submission does not outline specific numerical "acceptance criteria" in the way one might see for a diagnostic device (e.g., sensitivity/specificity targets). Instead, it relies on demonstrating compliance with recognized safety and performance standards and showing equivalence to a predicate device.

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

• Sample Size: Not specified in terms of number of human subjects or distinct test cases. The testing involved "lab bench testing" and "porcine muscle, liver, and kidney" tissue. The number of samples/tests for each tissue type is not detailed.
• Data Provenance: The testing was "lab bench testing" using "porcine" tissue. The country of origin for the data is not explicitly stated beyond the applicant being based in China. The data is from prospective testing conducted specifically for this submission.

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

• Not Applicable / Not Provided: This type of submission (510(k)) for an electrosurgical generator typically relies on objective physical measurements and engineering evaluations against standards, rather than expert-established ground truth like in diagnostic imaging. There is no mention of experts establishing a ground truth for a test set in this context.

4. Adjudication Method for the Test Set

• Not Applicable / Not Provided: As there's no mention of expert ground truth establishment, there is no adjudication method described.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No: An MRMC comparative effectiveness study is not mentioned as this device is an electrosurgical generator, not an interpretative diagnostic imaging device that involves human readers.

6. Standalone (Algorithm Only) Performance

• Yes, implicitly: The "performance data" section (Section 6) describes "System Performance and waveform outputs test," "Thermal effects testing," and "software verifications" which represent the standalone performance of the device itself and its integrated software. These tests involve direct measurement of the device's output and effects, independently of human interpretation of a diagnostic output.

7. Type of Ground Truth Used

• Objective Measurements and Physical Science Principles: The "ground truth" for this device's performance is established through objective measurements of electrical output parameters (waveform, power), physical effects on tissue (thermal damage size), and compliance with internationally recognized safety and performance standards (e.g., IEC 60601 series). For software, it's verification against design specifications and guidance documents.

8. Sample Size for the Training Set

• Not Applicable / Not Provided: This device, an RF Surgical Generator, does not utilize machine learning or AI models that require a "training set" in the conventional sense. Its functionality is based on established engineering principles and not on learning from a large dataset.

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

• Not Applicable / Not Provided: As there is no training set for a machine learning model, this question is not applicable.

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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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The Electrosurgical Generator – Model FW-350A is a non-sterile, reusable multi-purpose electrosurgical generator that is designed to perform monopolar and bipolar functions in the surgical operation area.

Electrosurgical Generator-Model FW-350A has Monopolar and Bipolar modes that can satisfy the general requirements of electrosurgical field. The CQMS function can monitor the area of patient body applied with ESU pad during the operation every 40ps. Once the pad loses or that area shrinks, the computer will cut off all outputs within 40us to prevent patient from getting burnt. The PPS system ensure the safety of a constant output that send out compulsory stimulation at the initial instant of every CUT or COAG to make the operation process go smoothly. Moreover, the memory function can decrease the medical staff workload and human errors. At last, the Power ON self diagnostics function can diagnosis whether all working modes and functions are working normally and feedback information by code displaying and alarm voice prompt that the operational safety is improved greatly.

The provided text describes a 510(k) premarket notification for an Electrosurgical Generator, Model FW-350A. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than providing extensive details on novel acceptance criteria and comprehensive study results as would be typical for a de novo submission or a new technology.

Therefore, the information available in the document primarily addresses the safety and performance of the device relative to existing standards and a predicate device. It does not contain an "acceptance criteria" table in the classical sense, nor detailed study results that prove the device meets these criteria in a standalone, statistically robust manner. Instead, the "acceptance criteria" are implied by compliance with recognized standards and a demonstration of comparable performance to the predicate device through bench testing.

Here's a breakdown of the information that can be extracted, interpreted based on the context of a 510(k) submission:

1. Table of Implied Acceptance Criteria and Reported Device Performance

Since this is a 510(k) submission, the "acceptance criteria" are primarily based on demonstrating equivalence to the predicate device and compliance with relevant safety standards. The reported device performance is presented in comparison to the predicate.

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The Electrosurgical Generator (OBS-350A) is a non-sterile, reusable multi-purpose electrosurgical generator that is designed to perform monopolar and bipolar functions in the surgical operation area.

The generator is enclosed in a metal and molded plastic enclosure and will have an angled front panel in the display and controls area. The front panel displays and controls will be sealed to facilitate cleaning and minimize the possibility of problems caused by accidental spills. The receptacles for the active electrosurgical accessories will be in a recessed area and will conform to IEC60601-1:2005/(R) 2012 And A1:2012.

Device components: Chassis and Cover, Front panel controls, Power supply board, Microprocessor board, Footswitch board, Interface circuits, Front panel receptacles.

Special features: Three CUT modes (Pure CUT, Blend 1, Blend 2), Three COAG modes (COAG1 (Spray), COAG2 (Forced), COAG3 (Soft)), Two Bipolar modes (Bipolar1 (Macro), Bipolar2 (Micro)), Memory (10 memory Presets), CQMS (contact quality monitoring system), Power ON self diagnostics, PPS (peak power system).

Here's a breakdown of the acceptance criteria and study information for the OBS Electrosurgical Generator (model: OBS-350A), based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria in this document are primarily based on achieving "substantial equivalence" to a predicate device (Valleylab Force FX). This means the OBS-350A is considered acceptable if its performance is comparable to the predicate across various parameters, particularly regarding safety and effectiveness.

2. Sample Size for the Test Set and Data Provenance

• Sample Size for Test Set: The document does not specify a numerical sample size for the "test set" in terms of number of devices or number of tissue samples for the bench testing. It refers to "evaluations" and "tests."
• Data Provenance: The testing was "bench" testing, comparing the performance of the OBS-350A against its own design specifications and against the predicate device (Valleylab Force FX). The document implicitly indicates the testing was done by the manufacturer (Baisheng Medical Co., Ltd.) as part of their submission for market clearance. No country of origin for test data is explicitly stated beyond the manufacturer's location in China. The testing is considered prospective in the sense that it was conducted directly to support this 510(k) submission.

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

• The document does not mention the use of experts to establish a "ground truth" for the test set. The evaluation is focused on direct comparison of physical and electrical characteristics and compliance with recognized standards. This is typical for electrosurgical generators, where performance is objectively measured rather than subjectively interpreted (like image analysis).

4. Adjudication Method for the Test Set

• No adjudication method is described, as the testing involves objective measurements rather than subjective assessments requiring reader adjudication.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No, an MRMC comparative effectiveness study was not done. The document explicitly states: "Clinical and animal studies were not deemed necessary to support substantial equivalence." This type of study would involve human readers (e.g., surgeons) evaluating the device's performance, which was not performed or required here.

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

• This question is not applicable in the context of an electrosurgical generator. A standalone "algorithm" performance is relevant for AI/software devices that make diagnostic or treatment recommendations. The OBS-350A is a physical medical device that applies energy. Its performance is measured directly, not via an algorithm operating independently to produce an outcome. The document does mention software validation for the device's embedded software, which would be a form of "standalone" software assessment, but not in the AI/human-in-the-loop sense.

7. The Type of Ground Truth Used

• The "ground truth" in this context is established by:
  • Design Specifications: The device's performance is compared against its own defined design specifications.
  • Predicate Device Performance: Direct comparison of electrical waveforms and tissue thermal effects against a legally marketed predicate device (Valleylab Force FX).
  • Recognized Standards: Compliance with international standards such as IEC 60601-1, IEC 60601-2-2, and IEC 60601-1-2.

8. The Sample Size for the Training Set

• This question is not applicable. The OBS-350A is an electrosurgical generator, not an AI/machine learning device that requires a "training set" of data.

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

• This question is not applicable, as there is no "training set" for this type of medical device.

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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 hand-piece, Single use RF electrodes (needle type). Disposable neutral electrode pad and a footswitch.

Here's an analysis of the provided text regarding the acceptance criteria and supporting studies for the AGNES device.

It's important to note that the provided document is a 510(k) Summary, which establishes substantial equivalence to a predicate device. It demonstrates that the new device is as safe and effective as a legally marketed device and does not necessarily involve establishing new acceptance criteria or conducting a comprehensive "study that proves the device meets the acceptance criteria" in the same way a PMA (Premarket Approval) submission would. Instead, the focus is on showing equivalence through comparing specifications, adherence to recognized standards, and preclinical/animal testing to address differences.

Therefore, some of the requested information (like human reader MRMC studies or specific acceptance criteria for a novel AI algorithm's performance) is not applicable or present in this type of FDA submission.

Acceptance Criteria and Device Performance for AGNES (K160469)

The "acceptance criteria" for this 510(k) submission are primarily rooted in demonstrating that the AGNES device is substantially equivalent to its predicate devices (HR-5000 and INTRAcel Premium Fractional RF Micro Needle System) and that any differences do not raise new questions of safety or effectiveness. This is achieved by conforming to recognized electrical safety and performance standards, and, for specific functional aspects, through preclinical and animal studies.

The document does not present a table of quantitative acceptance criteria for its overall performance and compare it to reported device performance in a clinical efficacy context. Instead, it demonstrates compliance with safety and engineering standards and addresses the biological effects of its differences through testing.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Engineering/Safety Tests (Electrical, Biocompatibility, Sterility): The document refers to compliance with recognized standards (IEC, ISO, ASTM). These standards typically define the sample sizes and procedures for testing components and the overall device. For example, biocompatibility tests (ISO 10993) would involve specific numbers of cell cultures, animals, or material samples. The exact sample sizes for each specific engineering test are not detailed in this 510(k) summary but are inherent to the standard methods. Data provenance is implied to be laboratory testing by the manufacturer or accredited labs.
• Animal Study: The study used "mini pigs" for penetration depth and coagulation assessment, and a "rabbit's ear model" for acne treatment. Specific numbers of animals are not provided in the summary. The provenance is preclinical testing, likely conducted by or for the manufacturer.

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

• Engineering/Safety Tests: "Experts" in this context are the qualified personnel in test laboratories who perform and interpret the results of the standard tests (e.g., electrical engineers for IEC 60601, toxicologists/biologists for ISO 10993, microbiologists for sterility tests). Their specific number and qualifications are not detailed in the summary but are presumed to meet the requirements of the standards.
• Animal Study (Macroscopic Assessment): A "dermatologist" performed macroscopic assessment on damage and safety. The number of dermatologists and their specific years of experience are not specified.
• Animal Study (Histological Assessment): The histological assessments would typically be performed by a veterinary pathologist or a pathologist with experience in animal tissue, but their number and specific qualifications are not detailed.

4. Adjudication Method for the Test Set

• Engineering/Safety Tests: Adjudication is generally not applicable in the same way as clinical imaging studies. Compliance is determined by whether the device's performance meets the quantitative thresholds defined by each standard (e.g., leakage current within limits, tensile strength exceeding a value).
• Animal Study:
  • Macroscopic Assessment: A "dermatologist" assessed damage and safety. It's unclear if this was a single dermatologist, or if a consensus/adjudication process was used if multiple assessors were involved.
  • Microscopic Assessment: The histological assessment involves objective staining and observation. While interpretation requires expertise, a formal adjudication process between multiple experts for "ground truth" establishment in this specific context is not mentioned.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No, an MRMC comparative effectiveness study was not explicitly mentioned or performed as part of this 510(k) submission. This type of study is more common for diagnostic devices (e.g., AI for radiology reading) to compare human performance with and without AI assistance. The AGNES device is a therapeutic electrosurgical device; its primary function is to perform a physical action (electrocoagulation and hemostasis) and treat conditions like acne, not to provide diagnostic readings. The "effectiveness" is shown through its functional performance and biological effect, not by improving human reader interpretation.

6. Standalone (Algorithm Only Without Human-in-the-Loop) Performance

• Not applicable. The AGNES device is a physical electrosurgical device operated by a human. It is not an AI algorithm designed to operate autonomously or provide outputs without human interaction.

7. Type of Ground Truth Used

• Engineering/Safety Tests: The "ground truth" is defined by the objective pass/fail criteria established by the international and national standards (IEC, ISO, ASTM).
• Animal Study: The "ground truth" for the animal study was based on:
  • Clinical Assessment (Photo Assessment): Macroscopic observations by a dermatologist and photographic evidence.
  • Histological Pathology Analyses: Microscopic examination of tissue samples stained with hematoxylin & eosin, assessing sebaceous gland destruction, inflammatory cells, etc. This is considered objective biological evidence.
  • 3D Measuring Instrument (PRIMOS Pico): For assessing reduction of acne lesions, providing quantitative data.

8. Sample Size for the Training Set

• Not applicable / Not disclosed. This is a medical device approval that primarily relies on engineering specifications, safety standards, and preclinical (animal) performance, not machine learning or AI models that require a "training set" in the conventional sense. The device itself is designed and tested, not "trained" on data.

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

• Not applicable. As there is no "training set" in the AI/machine learning sense, no ground truth was established for it.

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