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InSeca ARC Stylus: The InSeca ARC Stylus is indicated for use in otorhinolaryngology (ENT) surgery for the coagulation of soft tissue in the nasal airway, to treat nasal airway obstruction by shrinking submucosal tissue.

Aerin Console: The Aerin Console is an electrosurgical system intended to generate radiofrequency electrical current for the use of an ARC Stylus (e.g., InSeca ARC Stylus). The Aerin Console is indicated for use in small clinic, office or hospital environments.

InSeca ARC Stylus: The InSeca ARC Stylus is a handheld bipolar radiofrequency (RF) probe designed for use in otorhinolaryngology (ENT) surgery. The Stylus comprises a handle, shaft and treatment tip. The treatment tip consists of an array of bipolar electrodes and a temperature sensor that allows for monitoring of tissue temperature during RF energy delivery. The Stylus is designed for use with the Aerin Console. It includes features to allow compatibility with and authentication by the Aerin Console. The Stylus connects to the Aerin Console via a flexible cable.

The InSeca ARC Stylus is used to treat patients experiencing chronic nasal airway obstruction. During a treatment procedure, the clinician inserts the tip of the InSeca ARC Stylus into a patient's nostril to deliver low power RF energy to the target tissue of the nasal airway. Radiofrequency treatment of tissue creates a coagulative lesion which fibroses and retracts as it heals, thereby shrinking the tissue to lessen the degree of obstruction.

Aerin Console: The Aerin Console is an RF generator designed to be used with the InSeca ARC Stylus to deliver bipolar RF energy to tissue. The Aerin Console consists of an RF generator, a power cord, and a foot switch. It incorporates user interface software to control, monitor and regulate RF power delivery to soft tissues via a cableconnected electrosurgical hand piece and electrode.

The provided document discusses a 510(k) premarket notification for the InSeca ARC Stylus and Aerin Console. This submission focuses on demonstrating substantial equivalence to a predicate device, rather than providing detailed acceptance criteria and a study to prove meeting those criteria in the way a clinical trial or a performance study for a novel device would.

Based on the provided text, here's a breakdown of the information requested, with "N/A" where the information is not provided because the submission is for substantial equivalence rather than a full performance study with specific acceptance criteria in the traditional sense:

1. Table of Acceptance Criteria and Reported Device Performance

The document describes non-clinical performance testing. The "acceptance criteria" are implied by the statement "The subject devices met all the performance testing requirements." Specific quantitative acceptance criteria for each test are not explicitly listed in a table, but the areas of testing are detailed.

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

The document describes non-clinical bench testing. Specific sample sizes for each test (e.g., number of styluses tested for force load, number of tissue samples for heating time) are not specified. The data provenance is generally "bench testing" and "tissue heating time testing performed using tissues representative of the submucosal tissues of the nasal airway." There is no mention of country of origin for bench testing, and it is entirely retrospective in the sense that it's laboratory testing, not a prospective human clinical trial.

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

Not applicable. The ground truth for bench and functional testing is based on engineering specifications, regulatory standards, and objective measurements (e.g., temperature, force, voltage, thermal lesion volume). There is no mention of human experts establishing "ground truth" for the non-clinical tests described.

4. Adjudication Method for the Test Set

Not applicable. As the testing described is non-clinical bench and laboratory testing against established specifications and regulatory standards, an adjudication method for a "test set" in the context of expert review or consensus is not relevant or described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No. A Multi-Reader Multi-Case (MRMC) comparative effectiveness study typically involves human readers (e.g., radiologists, clinicians) evaluating cases (e.g., images) to determine the effectiveness of an intervention (like an AI algorithm). This type of study is not mentioned in the document as it pertains to a physical electrosurgical device rather than an AI or image-based diagnostic system. Therefore, no effect size of human readers improving with AI assistance is provided.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

Not applicable. The InSeca ARC Stylus and Aerin Console are electrosurgical devices used by a clinician during a procedure; they are not an AI algorithm designed to operate in a standalone diagnostic or predictive capacity. While the Aerin Console incorporates "user interface software to control, monitor and regulate RF power delivery," its performance is intrinsically linked to its use by a human operator with the stylus. No "algorithm only" performance is discussed.

7. The Type of Ground Truth Used

The "ground truth" for the non-clinical tests described in the document is based on:

• Engineering specifications and design requirements: For mechanical integrity, electrical safety, and software functionality.
• Regulatory standards: Such as AAMI/ANSI/ISO 10993-1 for biocompatibility, ANSI/AAMI/ISO 11135 and ISO 10993-7 for sterilization, IEC 60601-1/60601-2-2 for electrical safety, and IEC 60601-1-2 for EMC.
• Physical measurements and objective comparisons: For thermocouple accuracy, tissue heating time, and thermal lesion volumes (compared to the predicate device).

8. The Sample Size for the Training Set

Not applicable. This document describes a 510(k) submission for a medical device based on substantial equivalence, with non-clinical performance and safety testing. It does not involve machine learning or AI models with "training sets."

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

Not applicable. As there is no "training set" referenced for a machine learning model, the establishment of its ground truth is not relevant to this document.

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