Search Results

This device is intended for the cutting and removal of bone and tissues in ENT, otorhinolaryngology / head and neck surgical procedures.

Indications: Any ENT, otorhinolaryngological, or head and neck surgery requiring the incision and removal of bone or tissue, including removal and shaping of bone during rhinoplasty procedures and removal of soft tissue during plastic, reconstructive, and/or athestic surgery of the head and neck.

The XPS microdebrider system is composed of the Power Control unit, a footswitch and a handpiece combined with various accessory blades and burs. The XPS system and replaceable blades and burs are intended for use by health care professionals and are labeled as prescription devices. The disposable blades and burs are provided in styles and sizes to remove the various tissues and bone typically resected in ENT and Head and Neck surgery.

This looks like a 510(k) premarket notification for a surgical device, not an AI/ML device. Therefore, the typical acceptance criteria and study designs relevant to AI/ML (like sensitivity, specificity, MRMC studies, ground truth establishment for training sets) do not directly apply in the same way.

However, I can extract information related to the device's intended use and the justification for substantial equivalence, which serves a similar purpose to demonstrating the device meets "acceptance criteria" for regulatory clearance based on a predicate device.

Here's an attempt to answer your questions based on the provided document, adapting where necessary for a non-AI/ML device.

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

For a traditional surgical device like this, the "acceptance criteria" are typically related to safety, effectiveness, and substantial equivalence to a predicate device for its intended use, rather than quantifiable performance metrics like sensitivity/specificity.

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

This information is not provided in a way that aligns with an AI/ML device's test set. The submission refers to a "multi-institutional experience for these indications (article of Becker, et al.)" to support the safety and effectiveness for soft tissue removal. However, the specific sample size, study design, or data provenance (e.g., country of origin, retrospective/prospective) of this medical literature is not detailed in the 510(k) summary. This is typical for a 510(k) that relies on existing clinical experience and predicate device comparison rather than de novo clinical trials for new functionality.

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

This concept is not applicable in the context of this 510(k) submission. The "ground truth" for a surgical device is typically established through clinical practice, medical literature, and regulatory precedent. The "experts" would be the surgeons who published the "multi-institutional experience" or who are generally recognized in the field for performing these types of surgeries, but their specific qualifications or role in establishing a "ground truth" for a test set are not described here.

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

Not applicable. There is no mention of a "test set" requiring an adjudication method as would be relevant for an AI/ML performance study.

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 is a surgical device, not an AI-assisted diagnostic or interpretive tool. Therefore, MRMC studies and "human readers" are not relevant.

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

Not applicable. This is a physical surgical device intended for human use, not an algorithm.

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

For this type of device, the "ground truth" for safety and effectiveness is established by:

• Clinical experience/outcomes data: Referenced implicitly through the "multi-institutional experience (article of Becker, et al.)" which suggests safe and effective use of powered cutting blades for soft tissue removal.
• Regulatory precedent and predicate device functionality: The device's substantial equivalence is based on its similarity to other legally marketed devices, whose safety and effectiveness have presumably been established through clinical use and regulatory review.
• Medical literature and accepted surgical practices: The document refers to the commonality of the procedures and that the indications are "commonly carried out by the ENT/Head and Neck surgeon."

8. The sample size for the training set

Not applicable. This is a physical surgical device, not an AI/ML algorithm requiring a training set.

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

Not applicable. (See answer to #8).

Ask a specific question about this device