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Resinous Material for repairing cranial defects.

Bone Cement for Cranioplasty (skull repair) is a self-curing acrylic that a surgeon uses to repair a skull defect in a patient. It is comprised of two sterile components (liquid and powder), which are mixed to form the cement.

The provided document, K040152, is a premarket notification for a medical device (Bone Cement for Cranioplasty) and does not describe acceptance criteria, performance studies, or AI algorithm validation in the way requested. This document is a 510(k) summary demonstrating substantial equivalence to a predicate device, not a performance study report for an AI or software as a medical device.

Therefore, most of the requested information cannot be extracted from this document, as it pertains to a different type of device and regulatory submission.

Here's what can be gathered, with caveats:

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

The document states: "Performance testing demonstrated that the proposed Bone Cement is substantially equivalent to currently marketed Cranioplastic with regard to functional characteristics."

However, it does not provide specific acceptance criteria (e.g., tensile strength range, curing time limits) or quantitative reported device performance values. It only states substantial equivalence.

Remaining questions (2-9) are not applicable or cannot be answered from the provided document because:

• This document is for a traditional medical device (bone cement), not an AI/software medical device. Therefore, concepts like test sets, training sets, ground truth establishment by experts, AI adjudication methods, or MRMC studies do not apply to this submission.
• The summary indicates "Non-clinical Test Results," implying physical and chemical property testing of the bone cement, not performance of a diagnostic algorithm.

Summary of non-applicable/unanswerable points:

• 2. Sample sized used for the test set and the data provenance: Not applicable. This refers to a physical product, not a data-driven algorithm.
• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for an AI algorithm is not relevant for bone cement.
• 4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
• 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 for an AI-assisted diagnostic tool.
• 6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable.
• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable.
• 8. The sample size for the training set: Not applicable.
• 9. How the ground truth for the training set was established: Not applicable.

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