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The FMwand Ferromagnetic Surgical System is indicated for cutting and coagulation of soft tissue during surgical procedures, including Gynecologic procedures (open, transabdominal only).

The FMwand Ferromagnetic Surgical System is a soft tissue cutting and coagulation device that consists of the FMwand Generator that is electrically connected to the sterile, single-use FMwand Handpiece by the FMwand Power Module (a resterilizable, reusable accessory cable) and a single-use, sterile air line. Like the predicate device, the handpiece includes actuation buttons that can be used to activate the handpiece tip. Also like the predicate device, an optional footpedal can be used to activate the handpiece. The connectors at both ends of the FMwand Power Module are designed to fit only the FMwand Generator and FMwand sterile, disposable accessories. The FMwand Power Module is provided non-sterile. It is intended to be cleaned and sterilized prior to the initial use and before each subsequent reuse.

The provided 510(k) summary for the FMwand Ferromagnetic Surgical System (K130606) does not describe a study involving an AI/Machine Learning device or a Multi-Reader Multi-Case (MRMC) comparative effectiveness study. This submission is for a traditional medical device (an electrosurgical system) and focuses on demonstrating substantial equivalence to a predicate device through bench testing and compliance with existing standards.

Therefore, many of the requested criteria related to AI/ML device testing (such as sample size for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, and training set information) are not applicable to this document.

The document primarily discusses that the new device is "substantially equivalent" to an existing predicate device (Domain Surgical System, K121881) by demonstrating that differences do not raise new questions of safety and effectiveness, and that the device functions as intended based on bench testing.

Here's an analysis based on the information available, noting where specific AI/ML related criteria are not met:

1. Table of acceptance criteria and reported device performance:

The document doesn't explicitly state "acceptance criteria" in a quantitative, measurable sense for clinical performance. Instead, it relies on demonstrating that the new device performs identically or equivalently to the predicate device through bench testing and compliance with standards. The "performance" is implicitly deemed acceptable if it matches the predicate and meets relevant safety standards.

Study Proving Device Meets Acceptance Criteria:

The document refers to "bench testing" as the primary study type to demonstrate safety and effectiveness and substantial equivalence.

• "All applicable bench testing was performed with the FMwand Ferromagnetic Surgical System to assure that it functions as intended. Bench tests verified that the generator output was within specification and that the thermal output of the handpiece and tip corresponded to the target values."
• "The FMwand Ferromagnetic Surgical System passed all bench tests performed. Details are found in Section 15: of this submission."
• Biocompatibility testing was performed according to ISO 10993-1 and 510(k) Memorandum G95-1.
• Compliance with electrical safety standards included IEC 60601-1, IEC 60601-1-1, IEC 60601-1-2, and IEC 60601-2-2.

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

• Sample Size: Not specified in the provided text. Bench testing typically involves a number of units or measurements, but specific quantities are not given here.
• Data Provenance: Not specified. Bench tests are usually conducted in laboratories by the manufacturer or third-party testing facilities. The country of origin of testing data is not mentioned, and the testing is inherent to the device's design and manufacturing rather than involving patient data. This is a retrospective analysis of the device's physical and electrical properties, not clinical data.

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

• Not Applicable. This is a traditional medical device (electrosurgical system), not an AI/ML device requiring expert ground truth for interpretation of outputs like images. Bench testing involves objective measurements against predefined specifications and standards.

4. Adjudication method for the test set:

• Not Applicable. See point 3. Testing involves objective measurements, not subjective expert reviews that would require adjudication.

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:

• No. This is not an AI/ML device. No MRMC study was conducted or is relevant for this type of device.

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

• Not Applicable. This is not an AI/ML device. Standalone performance for an algorithm is not relevant. The device's "standalone" performance refers to its ability to meet specifications when operated.

7. The type of ground truth used:

• For the technical performance of the device (generator output, thermal output, electrical safety): Predefined specifications and recognized international or national safety and performance standards (e.g., IEC 60601 series). These are objective criteria.
• For biocompatibility: ISO 10993 series standards define the "ground truth" for material safety.

8. The sample size for the training set:

• Not Applicable. This is not an AI/ML device. There is no "training set" in the context of machine learning.

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

• Not Applicable. See point 8.

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