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Synthetic Mineral - Collagen Bone Graft Matrix is intended for use in dental surgery. The products may be used in surgical procedures such as:

• Augmentation or reconstructive treatment of alveolar ridge .
• Filling of periodontal defects .
• Filling of defects after root resection, apicocectomy, and cystectomy .
• Filling of extraction sockets to enhance preservation of the alveolar ridge
• Elevation of maxillary sinus floor .
• Filling of periodontal defects in conjunction with products intended for Guided Tissue Regeneration (GTR) and Guided Bone Regeneration (GBR)
• Filling of peri-implant defects in conjunction with products intended for Guided . Bone Regeneration

Synthetic Mineral -- Collagen Bone Graft Matrix is a composite of synthetic calcium phosphate based granules and type I collagen. The calcium phosphate mineral has an apatite structure similar to that of natural bone. The type I collagen is derived from bovine Achilles tendon. The composite material is a resorbable, porous, osteoconductive bone graft matrix. The product is supplied in granular or block/plug form, and it is sterile, non-pyrogenic, and for single use only.

The provided text describes a 510(k) premarket notification for a medical device called "Synthetic Mineral - Collagen Bone Graft Matrix." This submission focuses on establishing substantial equivalence to previously marketed predicate devices rather than proving effectiveness through a standalone clinical study with specific acceptance criteria that lead to performance metrics, as would be typical for a new device.

Therefore, the specific details requested in the prompt, such as acceptance criteria based on performance studies, sample sizes for test and training sets, expert qualifications, adjudication methods, MRMC studies, and detailed ground truth methodologies, are not explicitly present in this type of submission.

Instead, the "effectiveness" section states: "The characteristics of the Synthetic Mineral – Collagen Bone Graft Matrix meet the design requirements for an effective bone grafting material in dental surgery." This implies that the device's inherent properties and its resemblance to predicate devices are considered sufficient to meet the general design requirements for bone grafting materials.

Here's how the available information relates to your request:

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

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

• Not Applicable. The submission does not describe a clinical study with a "test set" in the context of device performance metrics. Its effectiveness is based on material characteristics and comparison to predicate devices, not on direct clinical performance data from a specific patient cohort for performance evaluation.

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

• Not Applicable. The submission does not involve a "test set" for which ground truth would be established by experts.

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

• Not Applicable. There is no "test set" or adjudication method described.

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 not an AI-powered diagnostic device, and therefore, an MRMC study with human readers assisting or being assisted by AI is not relevant to this submission.

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

• Not Applicable. This device is a bone grafting material, not an algorithm.

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

• The "ground truth" in this context is based on the established regulatory standards for biocompatibility (FDA Blue Book tests) and the material characteristics that are demonstrably similar to legally marketed predicate devices. There is no "ground truth" derived from patient outcomes or expert consensus on diagnostic interpretations for this type of device.

8. The sample size for the training set:

• Not Applicable. The submission does not describe a "training set" in the context of machine learning or an algorithm.

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

• Not Applicable. See point 8.

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