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The EnSeal™ PTC is a bipolar electrosurgical instrument for use with an electrosurgical generator. It is intended for use during open and laparoscopic, general and gynerologic surgery to cut and seal vessels, cut, grasp and dissect tissue during surgery.

Indications for use include open and laparoscopic general and gynecological surgical procedures (including urologic, thoracic, plastic and reconstructive, bowel resetting, hysterectomies, cholecystectomies, gall bladder procedures, Nissen fundoplication, adhesiolysis, oophorectomies, etc.), or any procedure where vessel ligation (cutting and sealing), tissue grasping and dissection is performed. The devices can be used on vessels up to (and including) 7 mm and bundles as large as will fit in the jaws of the instruments.

The SurgRx EnSeal Vessel Sealing & Hemostasis System has not been shown to be effective for tubal sterilization or tubal coagulation for sterilization procedures. Do not use this system for these procedures.

EnSeal™ PTC with ERBE VIO 300 D. The functionality of the device is the same as the predicate device.

The provided text is a 510(k) summary for the EnSeal™ PTC with ERBE VIO 300 D, an electrosurgical device. This document focuses on demonstrating substantial equivalence to predicate devices rather than conducting a de novo study with specific acceptance criteria as one might see for novel AI/software devices. Therefore, much of the requested information regarding acceptance criteria, specific performance metrics, sample sizes, expert involvement, and ground truth establishment, as typically outlined for AI/ML device studies, is not present in this type of submission.

Here's an analysis based on the provided text, highlighting what is and is not available:

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

Explanation: In a 510(k) for an electrosurgical device like this, acceptance criteria would typically revolve around electrical safety, mechanical integrity, and functional performance (e.g., sealing strength, cut time, minimal thermal spread) compared to the predicate. However, these specific criteria and quantitative results are not detailed in this summary. The summary simply states that the tests "ensure the devices function as intended and meet design specifications."

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

• Test Set Sample Size: Not specified. The document only mentions "Preclinical laboratory (bench) and performance tests."
• Data Provenance: Not specified. The tests were "preclinical laboratory (bench)" tests, suggesting an in-house or contracted lab environment, but geographical origin is not mentioned. They would be considered prospective for the specific tests 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)

• Number of Experts: Not applicable/Not specified. This type of device performance testing does not typically involve human experts establishing "ground truth" in the way a diagnostic imaging AI algorithm would. Device performance is measured by objective metrics (e.g., burst pressure, temperature).
• Qualifications of Experts: Not applicable/Not specified.

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

• Adjudication Method: Not applicable/Not specified. Adjudication methods like 2+1 or 3+1 are typically used for establishing consensus ground truth in studies involving human interpretation (e.g., reviewing medical images). This is a physical device, and its performance is measured mechanically and electrically, not through human consensus on a diagnosis.

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

• MRMC Study: No. This is not an AI/ML diagnostic device, so an MRMC study comparing human readers with and without AI assistance is not relevant and was not conducted.

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

• Standalone Study: The device itself is "standalone" in its electrosurgical function, but the context of "standalone performance" typically refers to an algorithm's performance without human intervention. This device performs its function directly. Therefore, this question is not fully applicable in the context of an AI/ML algorithm. The "Preclinical laboratory (bench) and performance tests" assess the device's inherent function, which could be considered its standalone performance.

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

• Type of Ground Truth: For electrosurgical devices, "ground truth" is established through engineering and scientific principles. Examples might include:
  • Physical measurements: Tensile strength of sealed vessels, burst pressure, impedance, power output.
  • Histopathology: To assess thermal damage zones in sealed tissue (though not mentioned in the summary).
  • Objective functional assessments: Such as sealing time, cutting efficacy, and lack of electrical leakage.
    The summary does not detail the specific ground truth metrics but states tests were performed to ensure it "function[s] as intended and meet[s] design specifications."

8. The sample size for the training set

• Training Set Sample Size: Not applicable. This is not an AI/ML device, so there is no "training set" in the machine learning sense.

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

• Ground Truth Establishment for Training Set: Not applicable. As there is no training set for an AI/ML model, this question does not apply.

Study Description:

The study proving the device meets its "acceptance criteria" (which are generally implied to be equivalent performance to the predicate) is described as "Preclinical laboratory (bench) and performance tests." The conclusion drawn from these tests is that the device "function[s] as intended and meet[s] design specifications" and is "safe and effective and substantially equivalent to the predicate device." The study's focus was on demonstrating substantial equivalence to the previously cleared devices (EnSeal™ Vessel Sealing and Hemostasis System # K031133, and the ERBE VIO ESU, Model VIO 300 D, # K060484 and EnSeal PTC # K061526). This type of submission relies on comparative analysis of technological characteristics and performance data, rather than establishing de novo safety and effectiveness through a comprehensive multi-site clinical trial with specific performance endpoints often seen for novel therapeutic or diagnostic devices.

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