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The GeniCon Laparoscopic Suction/Irrigation System is available with an array of probe designs to facilitate lavage during laparoscopic surgery. This device has applications in laparoscopic gynecologic, general, thoracic and urology procedures to provide suction and irrigation functions to help flush blood and tissue debris from the operative site during laparoscopy to aid visualization.

The Genicon Laparoscopic Suction Irrigator system is indicated for use in patients undergoing a laparoscopic surgical procedure. It is designed to deliver sterile irrigation fluids to surgical sites during laparoscopic procedures and to evacuate blood, surgical sites and smoke from the surgical site.

The system consists of a hand piece equipped with two trumpet style valves, a probe, and connecting lines of tubing, one set designed to attach to a supply of irrigation fluid, and the other designed to attach to an aspiration pump. The valves allow controlled irrigation and aspiration during a surgical procedure.

The hand piece of the suction irrigator is designed to allow instruments to be introduced through the suction irrigator probe to reach the surgical site. The probes are available in a variety of instruments and diameters.

It is a single use, disposable device and is sold sterile, and the probes may be available as single use or reusable depending on the purpose.

This looks like a 510(k) premarket notification for a medical device called the "Genicon Laparoscopic Suction Irrigation System." Based on the provided text, it's clear that this is not a study to prove a device meets acceptance criteria involving AI or advanced performance metrics.

This document is a regulatory submission for a Class II medical device, seeking clearance based on substantial equivalence to a predicate device. Therefore, many of your specific questions regarding AI-related studies and detailed performance metrics are not applicable to this type of submission.

Here's a breakdown of what can be extracted and why other questions are not relevant:

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

• Not applicable in the context of this document. This 510(k) submission states, "Performance – There are no performance standards for this product." This means there aren't specific quantitative acceptance criteria or a formal performance study in this document that measures the device against such criteria. The "performance" described is in the context of its intended use and functional capabilities, not a statistical demonstration of efficacy or accuracy.

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

• Not applicable. There is no "test set" in the sense of a clinical trial or performance evaluation data provided in this regulatory submission. This is a submission for a mechanical surgical device based on substantial equivalence.

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. No ground truth establishment for a test set is mentioned.

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

• Not applicable. No adjudication method for a test set is mentioned.

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 laparoscopic suction/irrigation system, a mechanical tool, not an AI-powered diagnostic or assistive technology for "human readers."

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

• Not applicable. There is no algorithm.

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

• Not applicable. Ground truth in the context of performance metrics or AI is not part of this submission. The "ground truth" for this device's effectiveness relies on established surgical practices and the functional demonstration that it can perform its stated mechanical tasks (suction and irrigation).

8. The sample size for the training set

• Not applicable. No training set for an algorithm is applicable here.

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

• Not applicable. No training set for an algorithm is applicable here.

Summary based on the document:

The Genicon Laparoscopic Suction Irrigation System is a Class II device seeking 510(k) clearance. The basis for its acceptance (clearance) is its substantial equivalence to a legally marketed predicate device (Stryker K963646).

• Acceptance Criteria Implied by 510(k): The primary "acceptance criterion" for a 510(k) submission is demonstrating that the new device is as safe and effective as a predicate device and does not raise new questions of safety or effectiveness. This is typically achieved by comparing the new device's indications for use, technological characteristics, and performance data (if applicable and available) to the predicate device.
• Study Proving Acceptance: The "study" isn't a traditional clinical trial or performance study with quantified metrics against acceptance criteria. Instead, the submission itself is the "proof," asserting:
  • Indications for Use: They are aligned with existing laparoscopic procedures (gynecologic, general, thoracic, urology) to provide suction and irrigation.
  • Technological Characteristics: It consists of a handpiece with valves, a probe, and tubing for irrigation fluid and aspiration pump attachment. It's single-use, disposable. These characteristics are compared to the predicate device to show similarity.
  • Conclusion: "Based on the indications for use and technological characteristics, the Genicon Suction Irrigation system is shown to be safe and effective for its intended use and substantially equivalent to the predicate devices."

Therefore, the document describes a regulatory pathway for a conventional medical device, not a performance study as typically understood for AI or novel technologies requiring extensive clinical data or performance metrics.

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