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EnvoyCem is intended for use in otologic surgery for the following applications:

• Augmentation or coupling of the middle ear ossicles.
• Attachment of the middle ear ossicles to middle ear implants.
• Mechanical stabilization of middle ear prostheses.

EnvoyCem is glass ionomer cement that is provided as two components, a glass powder and polyalkenoic acid liquid. By mixing the two components, viscous moldable ionomeric cement is obtained which hardens in situ.

This submission is for a medical device (EnvoyCem, a glass ionomer cement) and as such, the performance testing described is focused on the device's physical and biological properties rather than an AI/ML algorithm's clinical performance. Therefore, many of the requested categories for AI/ML study components (like sample size for test/training sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, etc.) are not applicable to this 510(k) summary.

Here's a breakdown of the available information based on your request, with an explanation of why certain elements are not present:

1. Table of acceptance criteria and the reported device performance

The submission mentions that "All testing indicates that EnvoyCem meets its specification requirements." However, the specific acceptance criteria (numerical thresholds for success) and the detailed reported performance values for each test are not explicitly provided in this 510(k) summary. The document broadly states that the device successfully completed various tests.

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

This information is not provided. For non-AI/ML medical devices like this cement, "test sets" typically refer to lab-based studies on the material itself, not patient data.

3. 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 applicable. Ground truth for a cement's physical and biological properties is established through standardized laboratory testing methods, not expert consensus on patient data.

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

Not applicable, as this pertained to laboratory testing of device properties, not clinical assessment requiring expert 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

Not applicable. This is a medical device for surgical applications (cement), not an AI-assisted diagnostic tool.

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

Not applicable, as this is a medical device (cement), not an AI algorithm.

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

The "ground truth" for this device's performance is established through standardized laboratory testing protocols for:

• Physical properties (functional stability, hardening time, etc. – implied by "functional testing").
• Shelf life properties (implied by "accelerated shelf life testing").
• Biocompatibility (MEM Elution extract testing, Fourier transform infrared spectroscopy for chemical equivalence).
• Sterility (sterilization validation protocols).

8. The sample size for the training set

Not applicable for a medical device (cement). "Training set" is a concept specific to AI/ML algorithms.

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

Not applicable for a medical device (cement).

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