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ICX-Implant System is indicated for use in partially or fully edentulous patients to support maxillary and mandibular single-unit, multiple-unit, and overdenture dental restorations. ICX- Implant System is indicated for immediate loading when good primary stability is achieved and with appropriate occlusal loading. Implants with lengths less than 7.0 mm are indicated for delayed loading only.

ICX-Implant System CAD CAM abutments are intended for use with dental implants as a support for single unit or multiple unit prostheses in the maxilla of a partially or fully edentulous patient. All digitally designed abutments for use with ICX-Implant System CAD CAM abutments are intended to be manufactured at a medentis medical GmbH validated milling center.

The purpose of this submission is to obtain marketing clearance for an endosseous dental implant and abutment system. ICX-Implant System, from medentis medical GmbH. The ICX-Implant System includes a range of endosseous dental implants and prosthetic components. All implants have a selftapping apical thread with a tapered body and root-form designs with an internal hex implant/abutment connection. The implant body surface is blasted and acid-etched.

Abutments are available in multiple designs, including straight and angled abutments intended for single tooth and multi-unit restorations.

The provided text is a 510(k) summary for the "ICX-Implant System." This document is a premarket notification for a medical device and, as such, focuses on demonstrating substantial equivalence to previously cleared devices rather than proving the device meets specific acceptance criteria through a standalone performance study.

Therefore, the document does not contain the detailed information required to fully answer all aspects of your request, especially regarding specific acceptance criteria for AI/algorithm performance, multi-reader multi-case studies, or detailed ground truth establishment for a test/training set in the context of an AI device.

The document does describe non-clinical performance data for the dental implant system itself (e.g., sterilization, biocompatibility, mechanical testing) to show its safety and effectiveness, but not for an AI component.

Here's an analysis based on the provided text, highlighting what is present and what is missing:

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

• Missing: The document does not define "acceptance criteria" in the context of an AI/algorithm's performance (e.g., sensitivity, specificity, AUC). Instead, it discusses the substantial equivalence of the ICX-Implant System and its components to predicate devices based on technological characteristics, materials, and indications for use.

• The "Performance Data" section (Page 7) lists non-clinical tests performed, such as:

  • Validation of gamma irradiation sterilization to a sterility assurance level (SAL) of 10⁻⁶.
  • Bacterial endotoxin testing: < 20 EU/device.
  • Validation of moist heat sterilization cycle to SAL of 10⁻⁶.
  • Shelf life testing confirming seal integrity and sterility after 5 years.
  • Biocompatibility testing (in vitro cytotoxicity).
  • Characterization of implant surface (SEM, surface chemistry, hydrophilicity).
  • Mechanical testing according to ISO 14801 (static and dynamic loading).
  • Analysis of surface area and initial bone to implant contact area.
  • MR compatibility testing (supporting MR Conditional labeling).

  These are performance requirements for a dental implant and are confirmed to have been met, but they are not "acceptance criteria" for an AI algorithm's diagnostic performance.

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

• Missing: No information on test set size or data provenance for an AI/algorithm is provided. The document explicitly states: "No clinical data were included in this submission" (Page 8). The non-clinical tests listed above would have had specific sample sizes for those tests (e.g., number of implants for mechanical testing), but these are not detailed in the summary beyond stating the tests were performed "accordance with" relevant standards.

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

• Missing: Not applicable as no AI/algorithm performance test set is described.

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

• Missing: Not applicable as no AI/algorithm performance test set is described.

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:

• Missing: No MRMC study was done, as no AI component is mentioned.

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

• Missing: No standalone algorithm performance study was done, as no AI component is mentioned.

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

• Missing: Not applicable as no AI/algorithm performance is described. The "ground truth" for the implant itself is its conformance to material standards, mechanical properties, and biocompatibility, as verified by laboratory tests.

8. The sample size for the training set:

• Missing: No training set for an AI/algorithm is mentioned.

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

• Missing: No training set for an AI/algorithm is mentioned.

In summary:

This 510(k) pertains to a dental implant system (a physical device) and its components (e.g., abutments), not a software as a medical device (SaMD) or an AI-powered diagnostic/assistance tool. The entire submission is built on demonstrating substantial equivalence to existing, legally marketed predicate devices through a comparison of their technological characteristics, materials, and non-clinical performance data relevant to the physical implant and its function. It explicitly states that "No clinical data were included in this submission," further confirming that no human-in-the-loop or standalone diagnostic performance studies (which would be typical for AI/ML devices) were conducted or are required for this type of submission.

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