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Porcine Anorganic Bone Mineral 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 infrabony periodontal defects
• Filling of defects after root resection, apicoectorny, and cystectorny
• 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.

Porcine Anorganic Bone Mineral is a porous bone graft material consisting predominantly of calcium phosphate supplied in granular form for use in dental surgeries. The anorganic bone mineral is produced by removal of the organic components from porcine bone. The composition of Porcine Anorganic Bone Mineral meets the requirements of ASTM F1581 Standard Specification for Composition of Anorganic Bone for Surgical Implants. The anorganic bone mineral matrix is biocompatible, having interconnecting macro- and microscopic porous structure that supports the formation and ingrowth of new bone at the implantation site. The use of Porcine Anorganic Bone Mineral may be considered when autogenous bone is not indicated, or insufficient in quantity to fulfill the needs of the proposed surgical procedure. The granular product is supplied sterile, non-pyrogenic, and for single use only.

The provided text is a 510(k) summary for a medical device (Porcine Anorganic Bone Mineral), not a study describing the acceptance criteria and performance of an AI/ML device. Therefore, much of the requested information, such as sample sizes for test sets, expert qualifications, and details about AI performance, is not present.

However, I can extract information related to the acceptance criteria for the physical properties of the Porcine Anorganic Bone Mineral device and the types of studies conducted to demonstrate its substantial equivalence to predicate devices.

Here's the analysis based on the provided text, focusing on what is available:

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

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

• Sample Size for Test Set: Not applicable in the context of an AI/ML device. For the material characterization and biocompatibility studies, specific sample sizes are not provided in this summary. For the animal efficacy studies, it mentions "two separate animal efficacy studies," but the number of animals used in each study is not stated.
• Data Provenance:
  • Material Characterization & Biocompatibility: Performed by the applicant, Collagen Matrix, Inc. The location of testing is not specified, but the company address is Oakland, New Jersey, USA.
  • Animal Efficacy Studies: Conducted in "a dog dental intrabony defect model" and "a rabbit femoral condyle defect model." The geographical location of these studies is not specified.
• Retrospective or Prospective: These non-clinical and animal studies are inherently prospective, as they are designed experiments to evaluate the device.

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 as this is not an AI/ML device requiring expert ground truth for classification. The "ground truth" here is established through objective physical/chemical measurements and biological assessment according to recognized standards and protocols.

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

• Not applicable for a physical device evaluation. Adjudication methods are typically relevant for human interpretation tasks, especially in AI/ML performance evaluation where ground truth might be debatable.

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/ML device.

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

• Not applicable as this is not an AI/ML device.

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

• For Material Characterization: The "ground truth" is based on the specifications defined by ASTM F1581, general material science principles, and comparison to the predicate devices. This involves objective physical and chemical testing.
• For Biocompatibility: The "ground truth" is established by adherence to ISO 10993 standards for biological evaluation of medical devices, which includes tests for cytotoxicity, genotoxicity, systemic toxicity, local effects after implantation, carcinogenicity, and reproductive toxicity. The outcome (safe/unsafe) is determined by the results of these standardized tests.
• For Animal Efficacy Studies: The "ground truth" is assessed through the observed biological response in the animal models (e.g., new bone formation, integration) as compared to the predicate device. This would typically involve histological analysis, imaging, and other measures of tissue regeneration and healing.
• For Viral Inactivation: The "ground truth" is established by adherence to ISO 22442 standards, demonstrating that the manufacturing process effectively eliminates or inactivates potential viruses and transmissible agents.

8. The sample size for the training set

• Not applicable. This is not an AI/ML device that requires a training set. The development of the device itself would involve numerous R&D iterations, but not a formally defined "training set" in the AI sense.

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

• Not applicable. See point 8.

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