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The Sinusway Dilation System is intended to access and treat the frontal, maxillary and sphenoid sinuses in sinus procedures in adults using a trans-nasal approach, by dilation and displacement of the anatomic structures along the sinus drainage pathways.

Sinusway Dilation System combines the tissue expansion effect of balloon dilation with the features of a curved sinus seeker, and by that allows the user to track the dilation device into the sinus drainage pathways. The shape of the distal end of the dilation system can be changed by inserting pre-shaped seekers into it. The system includes:

1. A Dilation Kit (Single use, provided sterile) consists of the following components:
   a. A Dilation Device includes an inflatable balloon at its distal end and connects to the inflation device at its proximal end.
   b. Three interchangeable pre-shaped Seekers (also referred to as stylets).
   c. An Inflation Device connects to the dilation device and inflates it while providing visual and tactile pressure indication.
   All Dilation Kit components are disposed of at the end of the procedure.
2. A Holder (re-processible and auto-clavable) - holds the components of the Dilation Kit in place and locks them, allowing the user to operate the dilation tool.

The provided document is a 510(k) premarket notification for the Sinusway Dilation System. The information required in the request pertains to the performance criteria and studies for a device, typically AI/ML-based software. However, the Sinusway Dilation System is a physical surgical instrument (Ear, Nose, And Throat Manual Surgical Instrument). Therefore, many of the requested fields, such as "effect size of how much human readers improve with AI vs without AI assistance," "standalone (i.e. algorithm only without human-in-the-loop performance)," and "sample size for the training set," are not applicable to this type of medical device.

The document focuses on demonstrating substantial equivalence to a predicate device through comparison of technological characteristics and bench testing, rather than clinical performance metrics typically associated with AI/ML devices.

Nevertheless, I will extract the available information related to acceptance criteria and device performance based on the provided text, while explicitly noting when requested information is not applicable.

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

The document states that "All tests met the predefined acceptance criteria," but it does not explicitly list the acceptance criteria or the specific numerical performance results for each test. Instead, it lists the types of bench tests performed.

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

For the bench testing, the document does not specify sample sizes for each test or the data provenance (e.g., country of origin, retrospective/prospective). It generally refers to "tests" being performed.

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

Not applicable. This device is a physical surgical instrument, and its performance was evaluated through bench testing and compliance with standards, not through comparison against expert-established ground truth in a diagnostic context.

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

Not applicable. Adjudication methods are typically relevant for clinical studies or studies involving human interpretation of diagnostic results, which is not the case for this device's performance evaluation.

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 physical device, not an AI-assisted diagnostic tool.

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

Not applicable. This is a physical device, not an algorithm. Its functionality is dependent on human use during surgery.

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

The "ground truth" for the device's acceptable performance was established by adherence to recognized international standards (e.g., ISO 14971:2012 for risk analysis, ISO 10993-1 for biocompatibility, ISO 11135-1 for sterilization) and internal predefined acceptance criteria for bench tests. These are engineering and safety standards, rather than clinical "ground truth" for diagnostic accuracy.

8. The sample size for the training set

Not applicable. This is a physical device. The concept of a "training set" is relevant for AI/ML models.

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

Not applicable. As above, this is a physical device.

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