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The Lumenis VersaCut™ Tissue Morcellator System is intended for use under direct or endoscopic visualization for the morcellation and removal of dissected tissue during pelviscopic, laparoscopic, percutaneous, and open surgical procedures whenever access to the surgical site is limited.

The VersaCut™ Tissue Morcellator System is a multiple-use clectrosurgical cutting and aspiration device that is intended for the morcellation and removal of dissected tissue under direct or endoscopic visualization. The cutting action of the VersaCut™ Tissue Morcellator System is driven by the motor in the handpiece and the treatment site is accessed through the sheath of a nephroscope using the endoscope adapter as needed to keep the cutting blades in the field of view. The VersaCut™ Tissue Morcellator System is comprised of main components as listed below. These main components are available separately when replacements are needed.

• Reusable, steam sterilizable handpiece (motor-body unit) with power cable .
• Limited reuse, steam sterilizable cutting blade sets .
• Reusable, steam sterilizable endoscope adapters .
• Reusable aspiration pump-control unit combination with main power cable and fuses
• Reusable, multi-position, multi-staged footswitch with power cable .
• Sterile, single use aspiration tubing ◆
• Reusable sterilization tray, including cleaning brushes .

The VersaCut™ Tissue Morcellator System is provided as a production-cleaned, non-sterile device. Before use in a sterile procedure, the handpiece, blade set(s), and endoscope adapter(s) are to be enzymatically-cleaned and steam-sterilized. Sterile aspiration tubing is provided with the device.

This document is a 510(k) Summary for the Lumenis VersaCut™ Tissue Morcellator System, which is a medical device. As such, it does not describe a study involving an AI/Machine Learning device or outline acceptance criteria and performance of such a device in the way a clinical trial for diagnostic tools would.

Instead, this submission is centered on demonstrating substantial equivalence to a predicate device, which is a different regulatory pathway focused on showing that a new device is as safe and effective as a legally marketed device, rather than proving a specific performance metric against a set acceptance criteria.

Therefore, many of the requested categories for AI/ML device studies (like expert adjudication, MRMC studies, training set details, etc.) are not applicable to this document.

However, I can extract the relevant information regarding the device's performance demonstration.

Acceptance Criteria and Device Performance for Lumenis VersaCut™ Tissue Morcellator System

The Lumenis VersaCut™ Tissue Morcellator System is a medical device seeking 510(k) clearance based on substantial equivalence. The "acceptance criteria" in this context refers to demonstrating that the device meets its product specifications and performs comparably to a predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: Not explicitly stated as a "test set" in the context of an AI/ML model. The evaluation involved "physical testing" and "in vitro bench testing." The specific number of tests or samples used for these physical and bench tests is not detailed in this summary.
• Data Provenance: The testing was "in vitro bench testing," meaning it was conducted in a laboratory setting. No country of origin for patient data (as it's not a clinical study involving patients) or retrospective/prospective nature is applicable here. The data originates from internal company testing.

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

• Not Applicable. This is a device performance test, not a diagnostic accuracy study requiring expert ground truth for classification. Performance was assessed against predefined engineering specifications and safety standards.

4. Adjudication Method for the Test Set

• Not Applicable. No ground truth adjudication by experts for a test set is relevant for this type of device submission.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done

• No. An MRMC study is not relevant for this type of device. This device is a surgical tool, not a diagnostic imaging or AI system intended to be used by multiple human readers for interpretation.

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

• Not Applicable. This is a physical electrosurgical device, not an algorithm. Its performance is inherent to its physical operation and design, and while it's used by a human, it does not have a "human-in-the-loop" interaction in the sense of an AI interpreting inputs for a human.

7. The Type of Ground Truth Used

• Engineering Specifications and Safety Standards. The ground truth for performance was defined by the device's product specifications (e.g., cutting capability, motor function, material strength, electrical safety parameters) and established biocompatibility and sterilization standards.

8. The Sample Size for the Training Set

• Not Applicable. This refers to an AI/ML model's training data. This document describes a physical medical device. Device design and development typically involve iterative prototyping and testing, which could be considered an analogous "training" phase for the physical design, but it's not a data-driven training set.

9. How the Ground Truth for the Training Set was Established

• Not Applicable. See point 8.

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