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The radiofrequency energy delivery components of the Thermage CPT System and Accessories are indicated for use in:

• · Dermatologic and general surgical procedures for electrocoagulation and hemostasis;
• · Non-invasive treatment of periorbital wrinkles and rhytids including upper and lower eyelids;
• · Non-invasive treatment of wrinkles and rhytids.

The simultaneous application of radiofrequency energy and skin vibration by the Thermage CPT System and Accessories are indicated for use in:

• · Dermatologic and general surgical procedures for electrocoagulation and hemostasis;
• · Non-invasive treatment of periorbital wrinkles and rhytids:
• · Non-invasive treatment of wrinkles and rhytids;
• · Temporary improvement in the appearance of cellulite;
• Relief of minor muscle aches and pains;
• · Relief of muscle spasms;
• · Temporary improvement of local circulation (i.e., blood circulation).

The Thermage CPT System delivers radio frequency energy for selective coagulation of tissue while conductively cooling the epidermis. The Thermage CPT System delivers energy from the disposable tip to the patient. The System and its Handpiece monitor skin contact during treatment. The System employs radio frequency tuning to provide radio frequency energy across a range of impedances for delivery to the patient through single and multiple pass stamping motions of the tip.

The provided text describes a Special 510(k) submission for the Thermage CPT System and Accessories, demonstrating its substantial equivalence to a predicate device. This submission focuses on modifications to an existing device rather than a new AI/ML device, so it doesn't contain all the information requested about AI model performance.

Here's what can be extracted and inferred from the document regarding acceptance criteria and testing:

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

The document lists "Summary of Testing" with "Requirement" as the acceptance criteria and "Results" as the reported performance.

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

The document states, "The treatment tip design shall be capable of delivering up to the maximum REP count, and shall be verified or validated to show with 90% confidence that the tips will do so with a minimum of 90% reliability." This implies that a sample of treatment tips was tested to determine their reliability in delivering REP counts. However, the exact sample size or the provenance of the data (e.g., how many tips were tested, if they were from a specific country, or if the testing was prospective) is not explicitly stated in this document. The testing appears to be centered on the physical and functional aspects of the device and its accessories, not clinical data from patients.

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)

This information is not provided. The testing described appears to be engineering verification/validation, not human expert evaluation of clinical data.

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

Not applicable, as the testing described is not clinical 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/ML device and no MRMC study is mentioned.

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

Not applicable. This is not an AI/ML device. The testing described is for the device's physical and functional integrity.

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

The "ground truth" for the tests described is based on engineering specifications and performance requirements (e.g., maximum REP count delivery, snap fit, fluid barrier, dielectric strength, burst pressure). It's essentially "meets design specifications."

8. The sample size for the training set

Not applicable. This is not an AI/ML device, so there is no training set in the context of machine learning.

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

Not applicable. This is not an AI/ML device.

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