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The PRO MAX system is a Radiofrequency device intended for use in dermatologic procedures with separate indications for each handpiece.

The TC Handpieces (Shaper Max, Mini Shaper Max, iFine Max) are intended for:
• Relief of minor muscle aches and pain, relief of muscle spasm
• Temporary improvement of local blood circulation

When used up to 65W, the Mini Shaper Max and Small Max handpieces are also intended for the non-invasive treatment of mild to moderate facial wrinkles and rhytides.

The FSR Max Handpiece is intended for dermatological procedures requiring ablation and resurfacing of the skin.

The Intensif MAX Handpiece is intended for use in dermatologic procedures for electrocoagulation and hemostasis.

The EndyMed Contour MAX Handpiece is intended for the treatment of the following medical conditions; using the Contour MAX applicator for delivery of non-thermal RF combined with massage:
• Relief of minor muscle aches and pain, relief of muscle spasm
• Temporary improvement of local blood circulation
• Temporary reduction in the appearance of cellulite

ENDYMED PRO™ MAX is a computerized system that generates pulses of radio frequency (RF) energy that are emitted onto patient skin. The device consists of a console and seven handpieces that emit either ablative or non-ablative radiofrequency.

The provided document is a 510(k) clearance letter for the EndyMed PRO MAX device. It indicates that the device has been cleared by the FDA, but it primarily focuses on establishing "substantial equivalence" to predicate devices rather than directly presenting the results of a clinical study designed to prove the device meets specific acceptance criteria based on performance endpoints.

The document describes performance testing but does not provide a table of acceptance criteria alongside detailed "reported device performance" in the context of a clinical study or specific performance metrics for the indications for use. Instead, it justifies substantial equivalence through comparison of specifications and generic performance testing.

Here's an attempt to extract the requested information based on what is available in the document:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document does not explicitly state quantitative acceptance criteria for each indication (e.g., a specific percentage reduction in pain, or a defined improvement in wrinkles). Instead, it focuses on demonstrating that the device can achieve and maintain a therapeutic temperature similar to its predicate devices, which is presumed to lead to the intended effects. Therefore, the "Acceptance Criteria" here are inferred from the safety and performance testing described.

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

• Sample Size for Test Set:
  • For Tissue Heating Testing: "3 subjects with 3 anatomical sites each." (Total of 9 test sites across 3 subjects).
  • For other tests (Electrical Safety, EMC, Software, Biocompatibility, etc.): The document does not specify sample sizes in terms of human subjects or data sets. These are typically engineering or lab-based tests on the device itself or materials.
• Data Provenance: The document does not specify the country of origin of the data or whether it was retrospective or prospective for the Tissue Heating Testing. Given the context of a 510(k) summary, these tests are typically part of a prospective verification and validation effort by the manufacturer.

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

The document does not mention the use of experts to establish ground truth for the "test set" in the traditional sense of clinical endpoints for the indications. The tissue heating test measures temperature, which is an objective physical parameter.

4. Adjudication Method for the Test Set

The document does not mention any adjudication method like 2+1 or 3+1. This is expected as the described performance testing (tissue heating, electrical safety) involves objective measurements rather than subjective expert assessment.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not done according to the provided document. The submission focuses on substantial equivalence based on technical specifications and bench/performance testing, not clinical comparative effectiveness with human readers.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The device described is a physical medical device (Radiofrequency system with handpieces). While it contains software, the "performance testing" described (e.g., tissue heating) refers to the device's physical output characteristics, not an AI algorithm's standalone diagnostic or detection performance. Therefore, the concept of "standalone performance" for an AI algorithm is not applicable in the context presented.

7. The Type of Ground Truth Used

For the "Tissue Heating Testing," the "ground truth" is the measured temperature (39-45°C) achieved and maintained on the tissue. This is an objective, physiological measurement, not expert consensus, pathology, or outcomes data in a clinical trial sense for efficacy.

8. The Sample Size for the Training Set

The document does not mention a training set. This is because the device is a physical RF energy delivery system, and the "performance testing" described is for verification of its physical properties and safety, not for training a machine learning or AI algorithm.

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

Since no training set is mentioned, this question is not applicable.

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Endy Gel is an Electroconductive gel media used with external electrode to reduce the impedance to alternating current) of the contact between the electrode surface and the skin.

EndyMed's EndyGel™ is an Electroconductive gel media used with external electrode to enhance electrical conductivity by reducing the impedance (resistance to alternating current) of the radiofrequency signals path from the electrode surface between the electrode surface and the skin.

This document is a 510(k) Pre-Market Notification for EndyGel™, an electroconductive gel media. The purpose is to demonstrate substantial equivalence to a predicate device, Electro-Gel (K111717).

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

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

Study proving device meets acceptance criteria:

The safety and efficacy of the EndyGel™ were established by a series of performance tests, including biocompatibility testing, electrical performance, and stability.

• Biocompatibility testing:
  • Complies with ISO 10993-1, ISO 10993-5 (Cytotoxicity), and ISO 10993-10 (Irritation and Sensitization).
• Electrical Performance testing:
  • The impedance of EndyGel™ (527.68 at 1 MHz) is within 4% of the predicate device (549.71).
• Stability testing:
  • The EndyGel™ has a shelf life of 2 years (compared to 3 years for the predicate).
• pH:
  • The pH of EndyGel™ (7.15-7.33) is within 2.2% of the predicate device (6.99).

The document states that "The difference in total impedance and in pH between the two gels is negligible and do not impact the safety and effectiveness of the EndyGel." Also, "V&V and compliance testing, including: Biocompatibility testing, Electrical Performance testing and Stability testing, were successfully conducted and did not raise any new safety questions or identify any new risks."

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

The document does not explicitly state the sample size for the test set or the data provenance for the performance tests (biocompatibility, electrical performance, stability). It broadly refers to "performance tests" that were successfully conducted.

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. This device is an electroconductive gel, and the "ground truth" for its performance is based on quantifiable physical and chemical properties and standard biological safety tests, not human expert interpretation of data.

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

Not applicable. This is not a study involving human interpretation or adjudication.

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/software device that involves human readers.

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

Not applicable. This is not an algorithm-based device. Performance is based on intrinsic physical, chemical, and biological properties.

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

The "ground truth" for the acceptance criteria for this device are established by:

• Industry standards (ISO 10993-1, ISO 10993-5, ISO 10993-10, ISO 13485, ISO 14971-1).
• Quantifiable physical properties (impedance, pH, shelf life).
• Chemical composition analysis.
• Comparison to an existing legally marketed predicate device with a history of safe and effective use.

8. The sample size for the training set

Not applicable. This is not a machine learning or AI device that requires a training set.

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

Not applicable.

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The EndyMed Contour Handpiece is intended for the treatment of the following medical conditions; using the Contour applicator for delivery of non-thermal RF combined with massage:

• · Relief of minor muscle aches and pain, relief of muscle spasm
• · Temporary improvement of local blood circulation
• · Temporary reduction in the appearance of cellulite.

EndyMed's EndyMed Contour Handpiece is a treatment handpiece to be attached to the FDA cleared EndyMed Imagine TC Skin Treatment System (Imagine K08346). The EndyMed Contour Handpiece combines suction module that creates vacuum energy and emits bipolar RF energy that flows between the electrodes to create thermal heating of the tissue.

The Vacuum is used for the massaging of deep tissues by creating mild to deep suction. The vacuum massage contributes to the sub-dermal and adipose tissues shrinkage and improves the contact surface between electrodes and tissue.

The provided document is a 510(k) premarket notification for the EndyMed Contour Handpiece. It details the device's intended use, technological characteristics, and a claim of substantial equivalence to predicate devices. However, this document does not contain the specific information requested regarding acceptance criteria for an AI/ML device study, and the detailed study description you've outlined.

The document discusses performance tests for the EndyMed Contour Handpiece itself (e.g., power output, temperature, vacuum pressure), but this is validation of a physical medical device, not a study proving an AI/ML algorithm meets acceptance criteria.

Here's why the requested information cannot be found in the provided text:

• No AI/ML Component: The EndyMed Contour Handpiece is described as an electrosurgical cutting and coagulation device accessory that uses RF energy and vacuum mechanical manipulation. There is no mention of an AI/ML component or algorithm in its description or intended use.
• Study Type: The "performance data" and "summary of clinical performance data" refer to lab performance tests, design validation, and software verification and validation for the physical device, and a claim that no clinical studies were necessary to show substantial equivalence with its predicate devices because it has the same intended use, clinical indication, and technology. This explicitly states new clinical studies were not performed for this submission.
• Ground Truth: Since no clinical studies were performed, there is no discussion of establishing ground truth, expert consensus, pathology, or outcomes data for a test set.
• Sample Sizes/Experts/Adjudication/MRMC: These are all concepts relevant to clinical or performance studies evaluating an AI/ML algorithm's effectiveness against a ground truth, which were not conducted for this submission.

Therefore, I cannot populate the table or answer the specific questions about acceptance criteria and study proving device meets acceptance criteria, as the provided text does not describe such a study for an AI/ML-driven medical device.

The document is a regulatory submission for a physical medical device (EndyMed Contour Handpiece), focusing on its technical specifications and substantial equivalence to existing devices, rather than the performance evaluation of a novel AI/ML algorithm.

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The EndyMed Newa™ is an over-the-counter home use device intended for non-invasive treatment of mild to moderate facial wrinkles for adult women who have Fitzpatrick Skin Types I-IV.

The Newa™ is an OTC, home use hand held device generating pulses of radiofrequency (RF) energy that are emitted into the skin. RF energy heats the tissue to improve the appearance of wrinkles and rhytides. It is a non-invasive, non-ablative device consisting of:

• User interface
• Programmable logic controller (PLC)
• RF power module
• Power supply
• RF electrodes

Acceptance Criteria and Device Performance Study for NEWATM

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a device for aesthetic use and not a diagnostic AI, many of the typical AI/ML study components (like training set details, MRMC studies, standalone performance with explicit metrics for algorithm output) are not directly applicable in the same way. The studies focus on safety, usability, and clinical effectiveness as a treatment device.

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

• Clinical Study (Effectiveness & Safety):
  • Enrollment: 69 participants (adult women, average age 54.4 ± 8.1 years, range 37-72; Fitzpatrick Skin Types I-IV).
  • Completers: 62 participants.
  • Provenance: Prospective, single-center study. Country of origin is not explicitly stated but implies the same location as the manufacturer or clinical trial site.
• Label Comprehension & Self-Selection Study:
  • Sample Size: 247 subjects.
  • Provenance: Not explicitly stated but implies a general population capable of reading English, recruited for the study.
• Usability Study:
  • Sample Size: 62 subjects (these were part of the clinical study participants).
  • Provenance: Part of the prospective clinical study.

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

• Clinical Study (Effectiveness):

  • Number of Experts: Three independent board-certified dermatologists.
  • Qualifications: "Board-certified dermatologists." Specific years of experience are not mentioned.

• Label Comprehension & Self-Selection Study:

  • Medical Expert for Validation: An interviewer (trained in assessing wrinkle severity) made an initial assessment. This was then provided to a "blinded outside expert" for final determination of correct self-selection.
  • Qualifications: The interviewer was "trained in assessing wrinkle severity." The "blinded outside expert" qualifications are not further detailed beyond being an "expert."

4. Adjudication Method for the Test Set

• Clinical Study (Effectiveness):

  • A patient was considered a "success" if at least 2 out of the 3 independent dermatologists agreed that the patient achieved at least one degree of wrinkle score reduction (per Fitzpatrick Wrinkle Severity Scale) when comparing baseline to 4-week follow-up. This is a 2+1 adjudication method.

• Label Comprehension & Self-Selection Study:

  • The subject's decision and reasons, along with the interviewer's assessment of wrinkle severity, were provided to a "blinded outside expert" for a final determination of whether the subject had correctly self-selected. This implies a single expert adjudicating the correctness of the subject's self-selection, informed by other inputs.

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 device is a treatment device, not a diagnostic AI. The studies performed were to demonstrate the device's effect on wrinkles, not to enhance human reader performance in diagnosis. The "readers" (dermatologists) in the clinical study evaluated before-and-after photographs, but their role was to assess treatment outcomes, not to interpret an AI's output.

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

• Not Applicable. This is a physical device intended for direct human use for treatment, not a standalone AI algorithm. The device itself performs actions (RF energy delivery) rather than providing diagnostic outputs that would be typically associated with a standalone AI algorithm's performance evaluation.

7. The Type of Ground Truth Used

• Clinical Study (Effectiveness): Expert Consensus. The ground truth for wrinkle reduction was established by the consensus of at least 2 out of 3 independent board-certified dermatologists, who assessed high-resolution photographs using the Fitzpatrick Wrinkle Severity Scale.
• Safety Adjudication: Investigator observation and patient diaries for adverse events.
• Self-Selection/Usability Studies: Expert opinion (interviewer + blinded outside expert) on the correctness of user actions and self-selection decisions.

8. The Sample Size for the Training Set

• Not Applicable (for the device's primary function). The NEWATM device is an electrosurgical device, not a machine learning algorithm in need of a "training set" in the conventional AI/ML sense for its core functionality. Its software controls basic operational and safety functions, which are validated through traditional software V&V processes and bench testing, not through a large-scale data-driven training set.

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

• Not Applicable. As noted above, a "training set" for an AI/ML algorithm is not described as being part of the device's development or validation for its primary function. Software validation relies on defined specifications and formal verification and validation protocols rather than a data-driven training approach.

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