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Cutting: Skin and Mucosal Incisions, Biopsy, Cysts, Abscesses, Tumors, Cosmetic Repairs, Development of Skin Flaps, Skin Tags, Nevi, Keratosis, Oculoplastic Procedures, Blepharoplasty, Aponeurotic Repair, Levator Resection, Arthroscopic Procedures; Blended Cutting and Coagulation: Skin Tags, Papilloma Keloids, Keratosis, Verrucae, Basal Cell Carcinoma, Nevi, Fistulas, Epithelioma, Cosmetic Repairs, Cysts, Abscesses, Development of Skin Flaps, Oculoplastic Procedures, Arthroscopic Procedures, ENT procedures; Hemostasis: Control of Bleeding, Epilation, Telangicctasia; Bipolar: Pinpoint, Precise Cutting and Coagulation, Pinpoint Hemostasis in any field (Wet or Dry)

The @llman Surgitron Radiolase II is a high frequency, medium power output electrosurgical medical device. The design is similar to currently marketed electrosurgical generators and provides the essential operational modes that are most often used in medium power electrosurgical applications. The unit consists of both a nominal 50 Watt maximum output power in monopolar mode and a nominal 55 Watt maximum output power in bipolar mode, providing the capability of precision cutting, coagulation, and hemostasis in a four megacycle frequency electrical current. The unit is designed to comply with the international safety standards.

Here's a breakdown of the acceptance criteria and study information for the ellman Surgitron Radiolase II device, based on the provided 510(k) summary:

This document is a 510(k) summary, which is a premarket notification to the FDA to demonstrate that a device is substantially equivalent to a legally marketed predicate device. It typically does not contain detailed primary study results, acceptance criteria, or comprehensive performance data as would be found in a full clinical study report. Instead, it focuses on demonstrating equivalence to existing devices.

Therefore, the information provided below will be based on what can be inferred from the 510(k) submission, particularly the comparison to predicate devices, rather than explicit statements of acceptance criteria and a detailed study proving performance against them.

Acceptance Criteria and Reported Device Performance

Note: The 510(k) summary does not explicitly state "acceptance criteria" in the typical sense of quantitative performance targets. Instead, the "acceptance criteria" are implicitly met by demonstrating substantial equivalence to the predicate devices in terms of intended use, technological characteristics, and safety standards. The reported device performance is described by its technical specifications and capabilities, which are compared directly to the predicate devices.

Study Information (Based on 510(k) Submission)

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

• Test Set: Not applicable for this type of submission. A 510(k) premarket notification primarily relies on a comparison of technological characteristics and intended use to predicate devices, rather than a new clinical study with a "test set" in the sense of clinical data. The submission indicates that the "indications for use is identical to the Surgitron as a preamendment device".
• Data Provenance: The document does not describe specific clinical data or a test set. The provenance of the comparison data is the existing specifications and regulatory clearances of the predicate devices: ellman Surgitron Radiolase (K992382) and ellman Surgitron 4.0 Dual RF/120 IEC (K013225).

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable. There is no mention of a test set with human-established ground truth in this 510(k) submission. Ground truth would be derived from the established safety and effectiveness of the predicate devices.

3. Adjudication method for the test set:

• Not applicable, as no human expert adjudication of a test set is described.

4. 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:

• No. This device is an electrosurgical unit, not an imaging or diagnostic device that would typically involve human readers or AI assistance in interpretation. Therefore, an MRMC study is not relevant here.

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

• No. This device is a physical electrosurgical unit. It does not contain an algorithm or AI component.

6. The type of ground truth used:

• For a 510(k) submission, the "ground truth" for demonstrating substantial equivalence is the established safety and effectiveness of legally marketed predicate devices, as determined by the FDA's original clearance of those devices. This includes adherence to recognized performance standards (e.g., IEC 60601-1, 60601-2-2).

7. The sample size for the training set:

• Not applicable. The device does not contain software or AI that would require a "training set."

8. How the ground truth for the training set was established:

• Not applicable, as no training set exists for this device.

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Cutting: Skin Incisions, Biopsy, Cysts, Abscesses, Tumors, Cosmetic Repairs, Development of Skin Flaps, SkinTags, Nevi, Keratosis, Oculoplastic Procedures, Blepharoplasty, Aponeeurotic Repair, Levator Resection, Arthroscopic Procedures.
Blended Cutting and Coagulation: Skin Tags, Papilloma Keloids, Keratosis, Verrucae, Basal CellCarcinoma, Nevi, Fistulas, Epithelioma, Cosmetic Repairs, Cysts, Abscesses, Development of Skin Flaps, Oculoplastic Procedures, Arthroscopic Procedures.
Hemostasis: Control of Bleeding, Epilation, Telangiectasia

Surgitron Radiolase is a high frequency, medium power output electrosurgical device. The design is unique, simple, energy efficiency, safe, and user friendly. Furthermore, it equips the essential operational modes that are most often used in electrosurgical application. The unit has a maximum 50 watt output power and provides the capability of precision cutting, coagulating, and hemostasis in four megacycle frequency electrical current. It is designed to comply with international safety standards.

This document describes the Surgitron Radiolase, an electrosurgical device, and its substantial equivalence to predicate devices, not acceptance criteria for a study proving device performance in the context of AI/medical imaging or diagnostics.

Therefore, many of the requested elements (like "device performance," "sample size for test set," "number of experts," "adjudication method," "MRMC study," "standalone performance," "ground truth type," "training set size," and "ground truth for training set") are not applicable to this 510(k) summary. This document is focused on demonstrating that the new device is as safe and effective as previously cleared devices.

Here's a breakdown of what can be extracted or inferred from the provided text, aligning with the intent of the request as much as possible given the nature of the document:

Acceptance Criteria and Study for Surgitron Radiolase

The "acceptance criteria" in the context of this 510(k) summary are primarily based on demonstrating substantial equivalence to existing predicate devices in terms of intended use, technological characteristics, and safety standards. There isn't a "study" reported in the traditional sense of a clinical trial proving a specific performance metric against a numerical acceptance criterion. Instead, the "study" is the comparison made by Ellman International to show that the Surgitron Radiolase is similar enough to its predicates.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not applicable. This is not a clinical study involving a test set of patients or data. The evidence for "performance" is based on technical comparison to predicate devices, compliance with standards, and the known safety/efficacy of the underlying technology (radiofrequency electrosurgery).
• Data Provenance: Not applicable. The data provided is a technical comparison of device specifications.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Not applicable. There is no "ground truth" established by experts in this context. The determination of substantial equivalence is made by the FDA based on the manufacturer's submission and comparison to predicate devices. The manufacturer's team (e.g., Frank Lin, Ph.D. Director of R&D Engineering) performs the comparative analysis.

4. Adjudication method for the test set

• Not applicable. There is no test set or adjudication process as typically understood in a clinical study. The FDA reviews the submitted technical data and makes a determination of substantial equivalence.

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 an electrosurgical unit, not an AI-powered diagnostic or imaging tool.

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

• Not applicable. This device is an electrosurgical unit, not an algorithm. The document explicitly states: "There is no software component in this new device."

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

• Not applicable in the traditional sense of a clinical study. The "ground truth" for demonstrating substantial equivalence relies on:
  • Pre-amendment device history / Established Clinical Practice: The safety and effectiveness of the technology (radiofrequency electrosurgery) and its indications for use are well-established through years of medical practice and prior FDA clearances. The predicate device "Surgitron IEC" is referenced as a pre-amendment device.
  • Regulatory Standards: Compliance with recognized international safety and performance standards (IEC, UL, BSI).
  • Technical Specifications: Direct comparison of physical and electrical characteristics with legally marketed predicate devices.

8. The sample size for the training set

• Not applicable. There is no training set for an algorithm.

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

• Not applicable. There is no training set for an algorithm.

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