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The implant is indicated for use in restoring masticatory function in the edentulous and/or partially edentulous patient.

The Steri-Oss implant is designed to serve as support for prosthetic devices to restore patient chewing function. Natural dentition is composed of a root (subgingival) and a crown (supragingival). Designs in existence are intended to mimic this structure to aid the patient in restoring natural masticatory function. The implant is designed to serve as the root of the artificial tooth and the abutment/prosthetic is designed to serve as the crown. The implants are 3.8, 5.0 or 6.0 mm in diameter, from 8 - 18 mm in length and are composed of titanium and hydroxylapatite (HA). They are tapered, have a hexed superior surface, and are threaded.

This document is a 510(k) summary for a medical device (dental implant) and as such does not contain the kind of detailed information about acceptance criteria and comprehensive study results that would typically be associated with AI/ML-based medical devices. The questions in your prompt are geared towards evaluating AI/ML device performance, which is not applicable here.

However, I can extract the information available in the document that somewhat aligns with your questions, adapting them to the context of a physical medical device.

Here's the breakdown based on the provided text, with explicit notes where the requested information is not available or not applicable due to the nature of the device:

1. Table of Acceptance Criteria and Reported Device Performance

For this physical device, "acceptance criteria" and "reported device performance" are framed in terms of equivalence to a predicate device, focusing on material, dimensions, and basic characteristics. There are no numerical performance metrics like sensitivity, specificity, or accuracy that would be found for an AI/ML device.

2. Sample Size Used for the Test Set and Data Provenance

• Not Applicable in the traditional sense for a physical device. This document does not refer to a "test set" for performance evaluation in the way an AI/ML device would. The "test" here is a comparison to a predicate device based on its design and material characteristics.
• The comparison is a design comparison, not a data-driven performance study.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

• Not Applicable. "Ground truth" in the context of this device refers to the established safety and effectiveness of the predicate device and the scientific principles of dental implants. There's no mention of a panel of experts specifically establishing ground truth for this new device's data. Regulatory clearance of the predicate device implies an existing "ground truth" of its performance.

4. Adjudication Method for the Test Set

• Not Applicable. There's no "adjudication method" described as there's no test set in the AI/ML sense. The "adjudication" is implicitly the FDA's review of the substantial equivalence claim based on the provided technical comparison.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No. This type of study is specifically for evaluating diagnostic or interpretive AI/ML systems where human readers interact with the AI. This document is for a physical implant.

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

• Not Applicable. This is a physical medical device, not an algorithm.

7. The Type of Ground Truth Used

• The "ground truth" here is the established safety and efficacy of the predicate device (Nobelpharma's 3.75 mm implant) and general scientific understanding of dental implant function and materials (titanium, HA, threaded geometry). This is based on historical clinical use and regulatory approvals of similar devices, rather than a specific set of pathology or outcomes data for this device.

8. The Sample Size for the Training Set

• Not Applicable. This is a physical medical device. There is no "training set."

9. How the Ground Truth for the Training Set Was Established

• Not Applicable. As there's no training set, there's no ground truth for it. The basis for the design and materials is the established clinical success and regulatory clearance of the predicate device and the scientific principles behind dental implants.

Summary of Approach for This Device:

Instead of detailed performance studies common for software/AI devices, this 510(k) relies on demonstrating substantial equivalence to a legally marketed predicate device. The "performance data" section explicitly states: "A mathematical justification demonstrates the substantial equivalence of the predicate to the Steri-Oss products." This implies comparative engineering analysis rather than clinical trials or data-driven algorithm validation.

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