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The StealthStation® System is intended as an aid for precisely locating anatomical locations in either open or percutaneous procedures. The StealthStation® System is indicated for any medical condition in which the use of stereotactic surgery may be considered to be safe and effective, and where a reference to a rigid anatomical structure, such as the skull, a long bone, or vertebra, can be identified relative to a CT or MR based model of the anatomy. The StealthStation™ System with the ENT option is also indicated for intranasal or sinus use.

This submission describes changes made to the StealthStation™ System to include the use of a camera array utilizing two 2-dimensional cameras as an alternative to the originally cleared camera array utilizing three 3-dimensional cameras.

The provided text is a 510(k) summary for a digitizer change to the StealthStation® System, indicating substantial equivalence to a previously cleared device. It does not contain primary study data or explicit acceptance criteria with specific performance metrics as would be found in a detailed clinical or technical study report.

Therefore, many of the requested elements about acceptance criteria, detailed study design, and performance metrics cannot be found in this document.

Here's an analysis based on the available information:

Acceptance Criteria and Device Performance

Based on the provided document, the primary "acceptance criterion" is a demonstration of substantial equivalence to the original StealthStation® System (cleared in K954276) despite a change in the digitizer.

Important Note: The specific performance metrics (e.g., accuracy, precision measurements) that were used to demonstrate substantial equivalence are not detailed in this summary. The summary only states that "Performance data was provided to support the claim of substantial equivalence."

Study Information (Based on available text)

1. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective):

   • Not provided. The document states "Performance data was provided," but does not specify any sample sizes, data provenance (e.g., country of origin), or whether the data was retrospective or prospective.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience):

   • Not provided. This type of information is not typically found in a 510(k) summary focused on hardware changes for an existing device.

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

   • Not provided.

4. 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/Not done (based on the device type and context). The device is a surgical navigation system, not an AI-assisted diagnostic tool for human readers. The change described is a digitizer hardware change.

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

   • Not applicable in the typical sense of "algorithm only." The "device" is a physical system involving hardware (digitizers) and software for surgical navigation. While its performance would be evaluated as a system, the concept of a "standalone algorithm" in the context of AI without human-in-the-loop doesn't directly apply here. The "performance data" mentioned would likely pertain to the accuracy and reliability of the navigation system's output.

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

   • Not explicitly stated in relation to specific "ground truth" establishment. For a surgical navigation system, "ground truth" would typically relate to known physical measurements, phantom studies, or potentially cadaveric studies with precise fiducial markers. The document does not specify the method used for the "performance data."

7. The sample size for the training set:

   • Not applicable/Not provided. This device is a hardware/software system for surgical navigation, not a machine learning model that undergoes a "training set" in the common sense.

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

   • Not applicable/Not provided. (See point 7)

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