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The XiVE® 3.0 Dental Implant System is indicated for single tooth restorations and splinted tooth restorations in the region of 7 to 10 and 23 to 26.

The XiVE® 3.0 Dental Implant System consists of subgingival threaded dental implants with 11 - 15mm lengths. The implants are coated with the FRIADENT Surface M2.1. The XiVE® 3.0 Dental Implant System is comprised of dental implants, surgical and laboratory instruments and prosthetic components. The system is designed for single tooth and splinted tooth restorations in the anterior regions of the mouth.

The provided text does not contain detailed information about specific acceptance criteria or a study proving that the dental implant device meets those criteria in the form usually associated with AI/ML-driven device evaluations (e.g., sensitivity, specificity, AUC, human reader improvement).

Instead, this document is a 510(k) summary for a dental implant system, which is a physical device, and the evaluation focuses on its substantial equivalence to a predicate device. The "performance evaluations" mentioned are likely related to mechanical strength, biocompatibility, and similar engineering and biological assessments, rather than diagnostic AI performance metrics.

Here's an analysis based on the provided text, highlighting what is and is not present concerning your request:

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

This information is not explicitly provided in the format requested for an AI/ML device. The document states:

• "Performance evaluations of the XiVE® 3.0 dental implant system show that the device performs as intended."
• "Comparisons of the XiVE® 3.0 dental implants to the predicate devices show that the device is substantially equivalent."

These are general statements about the device meeting expectations, but specific quantitative acceptance criteria (e.g., minimum tensile strength, fatigue life cycles) and their corresponding performance values are not detailed in this summary. The 510(k) process for this type of device typically relies on demonstrating equivalence in design, materials, and mechanical properties to a previously cleared predicate device.

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

This information is not available in the provided text. For a physical device like a dental implant, "test set" might refer to the number of implants subjected to mechanical testing or animal/human studies for biocompatibility and integration. However, the details of such tests (sample size, nature of the data, origin) are not included in this summary.

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

This is not applicable and not mentioned. For a dental implant, "ground truth" would relate to its physical properties, biocompatibility, and osseointegration, which are established through engineering tests, material science, and clinical observations, not expert consensus on image interpretation.

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

This is not applicable and not mentioned. Adjudication methods like 2+1 or 3+1 are typically used in AI/ML performance studies where multiple human readers independently evaluate cases to establish a robust ground truth for diagnostic tasks.

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:

This is not applicable and not mentioned. MRMC studies and the concept of "human readers improving with AI assistance" are relevant to AI-powered diagnostic devices, not purely mechanical dental implants.

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

This is not applicable and not mentioned, for the same reasons as above. This is a physical medical device, not an algorithm.

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

As discussed, the concept of "ground truth" in the context of an AI device's diagnostic performance is not directly applicable here. For a dental implant, performance is assessed against established engineering standards, material specifications, and clinical outcomes related to successful osseointegration and long-term stability. The text indicates "complete surface characterization of the new FRIADENT Surface M2.1 has been detailed in a Device Master File," which would be part of the technical documentation establishing its characteristics.

8. The sample size for the training set:

This is not applicable and not mentioned. There is no AI/ML algorithm being "trained" in this context.

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

This is not applicable and not mentioned.

In summary, the provided document describes a 510(k) submission for a dental implant system, a physical device, and its clearance is based on demonstrating substantial equivalence to an existing predicate device. The information requested regarding AI/ML device performance metrics (acceptance criteria for diagnostic performance, test/training sets, expert adjudication, MRMC studies, standalone performance, etc.) is not present in this document because it is not an AI/ML device submission.

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