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Indications for CEREC Cercon 4D™ CAD/CAM Blocks are:

• Crowns and bridges in the posterior and anterior tooth region
• Bridges with a maximum of two pontics
• Inlays, onlays and veneers

CEREC Cercon 4D™ CAD/CAM Block are pre-sintered zirconia blocks composed of yttria stabilized zirconia, which are designed for CAD/CAM milling. The proposed CEREC Cercon 4D™ CAD/CAM Blocks possess a 3-dimensional contour of dentine powder to mimic the natural tooth build-up. The aim of the 3D contour technology is to achieve more aesthetic restorations than with blocks based on the current multi-layer technology. The CEREC Cercon 4D™ CAD/CAM Blocks are used for fabrication of a dental restoration. The CEREC Cercon 4D™ CAD/CAM Blocks are not provided as the finished, fully finished dental restoration. The blocks are single use, meaning that they can only be milled once and are not recommended for re-milling. The blocks are materials supplied to dental professionals that must be further processed/manufactured using CAD/CAM milling and subsequent sintering to fabricate all ceramic restorations and they are not intended to be reused as in the context of direct patient-applied devices and materials. Therefore, no reprocessing, cleaning or disinfection instructions apply because it is a dental material and not a finished dental restoration itself. After sintering of the restoration, the dental professional will finish the restoration via polishing or glazing, before insertion into the patient's mouth.

This document describes a 510(k) premarket notification for the "CEREC Cercon 4D CAD/CAM Blocks," a dental material. The information provided is for regulatory clearance and focuses on demonstrating substantial equivalence to existing predicate devices, rather than a clinical effectiveness study of an AI-powered diagnostic device.

Therefore, many of the requested fields related to AI performance, ground truth, expert adjudication, and comparative effectiveness studies are not applicable or cannot be extracted from this document.

Here's the information that can be extracted and a clear indication of what is not applicable or not provided in the document:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are generally "Pass" for conformance to ISO standards and biocompatibility tests. The reported device performance is that it passed these tests.

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

This document describes non-clinical bench testing and biocompatibility assessments, not a study involving a "test set" of patient data for an AI algorithm. Therefore, this information is not applicable in the context of an AI device. The tests performed are on material samples, and the document does not specify the number of samples used for each test. The provenance of the test samples (e.g., country of origin) is not provided.

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

Not applicable. This is for a dental material, not an AI diagnostic device requiring expert interpretation of a test set.

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

Not applicable. This document pertains to materials testing, not diagnostic performance with a test set requiring adjudication.

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

Not applicable. This is not an AI diagnostic device.

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

Not applicable. This is not an AI device.

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

The "ground truth" in this context is adherence to established international standards (ISO standards) for ceramic dental materials and biocompatibility assessment. The "truth" is whether the material meets the specified physical, mechanical, and biological performance requirements defined by these standards.

8. The sample size for the training set

Not applicable. This is not an AI device that requires a training set.

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

Not applicable. This is not an AI device that requires a training set.

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