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Digitek Titanium Abutments are premanufactured prosthetic components directly connected to endosseous dental implants and are intended for use as an aid in prosthetic rehabilitation. They are compatible with the ASTRA TECH Implant System OsseoSpeed™ 3.5mm, 4.0mm, 4.5mm, 5.0mm implants.

Digitek Titanium Abutments are endosseous implant abutments which are placed into a corresponding dental implant to provide support for a prosthetic restoration. These abutments are made of titanium grade Ti-6AI-4V ELI (meets ASTM Standard F136). The abutment is mounted into the implant with a screw. These abutments are compatible with the ASTRA TECH Implant System OsseoSpeed™ implants.

Digitek Titanium Abutments are provided straight only and are not intended to be modified to provide an angle correction.

Digitek Titanium Abutments are manufactured in two models "3.5" and "4.0". And a hexagonal prism at the base of the Digitek Titanium Abutments acts as an anti-rotation feature.

Digitek titanium Abutments are supplied in a non-sterile state and should be sterilized prior to installation.

The provided document is a 510(k) premarket notification for a medical device, specifically a "Digitek Titanium Abutment." This type of document is focused on demonstrating substantial equivalence to a previously approved predicate device, rather than proving a device meets specific performance criteria through clinical or analytical studies in the same way an AI/software device would.

Therefore, many of the requested categories for acceptance criteria and study data are not applicable to this document. The document describes engineering and bench testing rather than performance outcomes with humans where experts establish ground truth.

Here's an analysis of what can be extracted or inferred from the provided text regarding acceptance criteria and testing:

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

The document does not explicitly state "acceptance criteria" in a numerical or categorical format for performance outcomes. Instead, it demonstrates equivalence to predicate devices and describes adherence to relevant standards and guidance.

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

• Fatigue Testing (ISO 14801:2007): The exact sample size is not specified, but it would typically involve a statistically relevant number of abutment-implant assemblies. Data provenance is implied to be laboratory testing conducted by or for Digitek Dental Solutions Limited.
• Cytotoxicity Testing (ISO 10993-5): The exact sample size is not specified but would involve a sufficient number of samples of the "final finished sterilized Digitek Titanium Abutment" to assess biological response. Data provenance is implied to be laboratory testing.
• Sterilization Validation (ANSI/AAMI ST79): Sample size would be determined by the standard for validating sterilization processes (e.g., bioburden testing, sterility assurance level verification). Data provenance is implied to be laboratory testing.
• Reverse Engineering Analysis: The document mentions "OEM abutments" but doesn't specify the number or provenance beyond being used as a basis for design.

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

Not applicable. This device is a mechanical component, and its "ground truth" is established through engineering specifications, material properties, and adherence to performance standards, rather than expert interpretation of complex data (like medical images in AI).

4. Adjudication method for the test set

Not applicable. Adjudication methods like 2+1 or 3+1 are used for establishing ground truth in human-in-the-loop studies, particularly when there is inter-reader variability. This is a physical device testing scenario using standardized methods.

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/software device that would involve human readers or AI assistance.

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

Not applicable. This is not a standalone algorithm.

7. The type of ground truth used

The "ground truth" for this medical device is the adherence to established engineering standards (e.g., ISO 14801:2007 for fatigue, ISO 10993-5 for biocompatibility), material specifications (Ti-6Al-4V ELI), and design equivalence to predicate devices as determined by mechanical and material properties.

8. The sample size for the training set

Not applicable. There is no "training set" as this is a physical medical device, not a machine learning model. The closest analogy would be the data from "OEM abutments" used for reverse engineering and design, but this isn't a training set in the AI sense.

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

Not applicable.

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