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The Valleylab FT10 Energy Platform is a high frequency electrosurgical generator intended for use with monopolar and bipolar accessories for cutting and coagulating tissue. When used with compatible sealing devices, it is indicated for sealing vessels up to and including 7 mm, tissue bundles, and lymphatics. The generator can also be used with compatible resectoscopes for endoscopically controlled removal or coagulation of tissue using 0.9% NaCl solution as the irrigation medium.

The tissue fusion function has not been shown to be effective for tubal coagulation for sterilization procedures. Do not use this function for these procedures.

The Valleylab FX8 FX Series Energy Platform is a high frequency electrosurgical generator intended for use with monopolar and bipolar accessories for cutting and coagulating tissue.

The Valleylab™ FT10 Energy Platform (VLFT10GEN) provides radio frequency (RF) energy for monopolar and bipolar surgical applications, and tissue-fusion and vessel-sealing applications (LigaSure/vessel-sealing function). It is a combination of a full-featured general-surgery electrosurgical unit and a bipolar vessel sealing system. The monopolar and bipolar sections, including the LigaSure section of the system, are isolated outputs that provide the appropriate power for cutting, desiccating, and fulgurating tissue during monopolar and bipolar surgery. The LigaSure/vessel-sealing section of the system provides power for vessel sealing.

The Valleylab FX8 Energy Platform provides radio frequency (RF) energy for monopolar and bipolar surgical applications. Unlike the Valleylab FT10, the VLFX8 does not include the tissuefusion and vessel-sealing applications (LigaSure function). It is a high-frequency electrosurgical generator intended for use with monopolar and bipolar accessories for cutting and coagulating tissue.

The provided document outlines the software updates for two electrosurgical generators, the Valleylab FT10 Energy Platform and the Valleylab FX8 Energy Platform. The submission is a Bundled Special 510(k) Notification, focusing on "incremental improvements while maintaining the same basic functionality and intended use."

Here's an analysis of the acceptance criteria and study information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample Size for Test Set and Data Provenance:

The document mentions "ex vivo testing using porcine tissue." However, it does not specify the sample size for this ex vivo testing. The provenance of this data is described as "ex vivo using porcine tissue," implying laboratory-based testing on animal tissue rather than human data. It is inherently retrospective in the sense that it's a controlled lab study, not collected from real-world clinical application.

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

The document does not provide information on the use of experts to establish ground truth or their qualifications. The ex vivo testing relies on objective measurements of thermal effects and system performance against pre-defined specifications.

4. Adjudication Method for the Test Set:

The document does not describe any adjudication method. Given the nature of the ex vivo and system verification tests, which involve objective measurements against specifications, a traditional adjudication method for subjective interpretation (like in imaging studies) would not be applicable.

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

No Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done. The document explicitly states: "This premarket submission did not rely on the assessment of clinical performance data to demonstrate substantial equivalence." The improvements are software-based and evaluated through engineering verification and validation, and ex vivo testing.

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

This question is not applicable in the context of an electrosurgical generator. The devices are tools used by surgeons; there isn't an "algorithm only" performance that operates independently of human interaction. The "software updates" are integral to the device's function, not a separate diagnostic algorithm.

7. Type of Ground Truth Used:

The ground truth used for the performance evaluations primarily involved:

• Objective measurements of thermal effects on porcine tissue.
• System specifications for functionality.
• Adherence to recognized industry safety and performance standards (e.g., IEC 60601-1, IEC 62304).

8. Sample Size for the Training Set:

The concept of a "training set" is not applicable in this context. These are electrosurgical generators with software updates, not AI/machine learning models that undergo a training phase with a distinct dataset. The software changes are refined and verified against specifications and performance criteria.

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

As there is no "training set" in the machine learning sense, this question is not applicable. The software updates were developed and verified against engineering specifications and relevant regulatory standards.

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