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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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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.

Ask a specific question about this device

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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