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Perioglas® is indicated for use in infraboney pockets caused by periodontal disease. The intended uses have been extended to extraction sites and ridge augmentation.

Perioglass® Bone Graft Particulate is a bioactive glass particulate (90-710 microns).

The provided text describes a 510(k) summary for the Perioglas®-Bioglass® Bone Graft Particulate. However, it does not contain information about specific acceptance criteria, a study designed to prove the device meets those criteria, or the detailed elements you've requested regarding AI/algorithm performance.

The document discusses a clinical study and its findings but does not frame these findings within predefined acceptance criteria for a new device submission. It focuses on demonstrating substantial equivalence to previously marketed devices and expanding intended uses.

Therefore, I cannot provide the requested information in the format you specified. I can only extract the details that are present in the provided text.

Here's a summary of what is available related to a study:

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

• Acceptance Criteria: Not explicitly stated or quantified in the provided text. The regulatory context is "substantial equivalence" and demonstration of "favorable results" and "significant new trabecular bone growth" for safety and efficacy.
• Reported Device Performance:
  • Significant new trabecular bone growth at two months after implantation.
  • Radiographic analysis indicated that Perioglas® integrated well into the bone tissue at 8 weeks.
  • Bone was pronounced solid by palpation of surgical sites at 8 weeks.
  • Radiographic differences between glass particles and bone tissue had nearly disappeared at 6 months.
  • Healing was uneventful without complaints from subjects.
  • Effective osseous grafting material for the prevention of alveolar bone collapse restoration in extraction sites at 2 years follow-up.
  • Physicians conclude that Perioglas® is both safe and effective in extraction sites and in reconstruction and augmentation of the alveolar ridge.

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

• Sample Size (Test Set): 16 patients and 20 sites were treated.
• Data Provenance: Human clinical study. Country of origin not specified, but typically conducted in the country where regulatory approval is sought (e.g., US for FDA 510(k)). Retro/Prospective: Implied to be prospective as it's a "recently completed human clinical study."

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

• Not specified. The text mentions "radiographic analysis" and "palpation of the surgical sites" and "Physicians conclude," but does not detail the number or qualifications of experts involved in these assessments or ground truth establishment.

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

• Not specified.

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:

• No, an MRMC study and AI assistance are not mentioned at all. This document predates widespread clinical AI application.

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

• No, this is about a physical bone graft material, not an algorithm.

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

• The assessment of success relied on:
  • Radiographic analysis (indicating integration, disappearance of particle differences).
  • Clinical palpation (bone pronounced solid).
  • Patient healing outcomes (uneventful, no complaints).
  • Long-term follow-up (2 years) for effectiveness in preventing alveolar bone collapse.
  • Physician conclusions on safety and effectiveness.
  • This blends expert clinical assessment and radiological findings. Pathology is not explicitly mentioned as the primary ground truth, though it might have been part of the broader clinical evaluation.

8. The sample size for the training set:

• Not applicable/Not specified, as this is a clinical study for a physical device, not an AI model.

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

• Not applicable/Not specified.

In summary, the provided text describes a classic medical device clinical study for a physical product, not an AI-powered diagnostic or assistive tool. Thus, many of your questions related to AI studies (MRMC, standalone algorithm performance, training sets, etc.) are not relevant to this document.

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