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The intended use of PerioGlas is to provide a safe, biocompatible synthetic bone graft material for oral/maxillofacial and dental intraosseous defects use. It is to be used alone in a manner comparable to autogenous bone graft chips or allograft bone particulate (DFDBA demineralized freeze dried bone) or may be mixed with each as a bone graft extender. Typical uses include:

• Periodontal/Infrabony defects .
• Ridge augmentation .
• Extraction sites .
• Cranio-facial augmentation .
• Cystic cavities .
• . Sinus lifts

PerioGlas® is a synthetic osteoconductive particulate bone/void filler that is intended for oral/maxillofacial and dental intraosseous defects use. The material composed of Bioglass® (24.5 wt % CaO, 24.5 wt % Na20, 45 wt % SiO2, 6 wt % P2O5) with a particle size range of 90-710 um. It is supplied sterile in a Tyvek sealed PET-G cup that is protected by a shrink wrapped cardboard box. It is mixed with sterile water (saline) or the patient's own blood to form a wet sandy paste which is applied to the defect.

The provided text describes the device testing and clinical data supporting the safety and efficacy of PerioGlas®. However, it does not explicitly define acceptance criteria in a structured table or directly compare performance against such criteria. Instead, it describes comparative studies and observations of equivalence or improvement.

Here's an interpretation of the implied acceptance criteria and reported performance, along with other requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a formal table of acceptance criteria. However, based on the conclusions and device testing sections, the implied acceptance criteria revolve around substantial equivalence to predicate devices and demonstrating safe and efficacious use.

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

Animal Models:

• Rabbit calvarial defect model: Sample size not specified.
• Canine split-rib model: Sample size not specified.
• Provenance: Not explicitly stated, but implies studies conducted in animal laboratories.

Clinical Data:

• Prospective, retrospective, and case studies: Sample sizes for individual clinical studies are not specified, except for:
  • Four clinician retrospective study: Focuses on implant success rate; the number of patients/cases included in this study is not specified, only the number of clinicians.
• Provenance: The text indicates "Clinical Data including prospective, retrospective and case studies were reviewed and evaluated," suggesting a mix of data types from various clinical settings. Specific country of origin is not mentioned.

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

• Animal Studies: Not explicitly mentioned, but typically, veterinary pathologists or researchers would evaluate outcomes in such studies.
• Clinical Studies: The "four clinician retrospective study" implies four clinicians were involved in evaluating cases and determining the 91% implant success rate. Their specific qualifications (e.g., "oral/maxillofacial surgeon with X years of experience") are not specified beyond being "clinicians." For other clinical data and case reports, the number and qualifications of experts are not described.

4. Adjudication method for the test set

• Not explicitly stated. For the "four clinician retrospective study," it's not described how potential disagreements among the clinicians were resolved or if there was a consensus process. For other clinical data and case reports, no specific adjudication method is mentioned.

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. The provided text describes the evaluation of a bone graft material, PerioGlas®, and its performance in animal models and clinical use. It does not describe an AI medical device or a multi-reader multi-case (MRMC) comparative effectiveness study involving AI assistance for human readers.

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

• Not applicable. This question pertains to AI/algorithm performance. PerioGlas® is a medical device (bone graft particulate), not an algorithm.

7. The type of ground truth used

• Animal Studies: Comparisons against "normal bone" for biomechanical properties, and direct observation of bone formation/graft site augmentation. This could be considered a combination of histological/pathological assessment and biomechanical measurements.
• Clinical Studies:
  • Periodontal studies: Clinical parameters (Clinical Attachment Level (CAL), Pocket Depth Reduction (PDR), osseous fill) are likely objective measurements taken directly from patients.
  • Implant success rate: This typically relies on established clinical criteria for implant stability, absence of infection, and functional integration, making it an outcomes-based ground truth determined by clinicians.
  • Case reports: These rely on clinical evaluations and radiographs interpreted by clinicians.

8. The sample size for the training set

• Not applicable. This question typically applies to machine learning models where a training set is used to develop the algorithm. PerioGlas® is a physical medical device. The animal and clinical studies described serve as testing/validation, not "training."

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

• Not applicable. As above, this pertains to machine learning models.

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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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