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The Zimmer Zfx Titanium Abutment for Straumann Bone Level Implant System is designed for use as a terminal or intermediate abutment for cement retained prostheses. The abutment can be used with Straumann Bone Level implants with a Narrow CrossFit Connection (NC) Ø3.3mm or Regular Crossfit Connection (RC) Ø4.1mm or Ø4.8mm.

The Zimmer Zfx Titanium Abutment for the Straumann Bone Level implant system is designed for use with Straumann Bone Level implants to support single or multi tooth restorations. The abutment/implant interface is a conical connection with 4 grooves for insertion guidance.

The Zimmer Zfx Titanium Abutment for Straumann Bone Level Implant System is a patient specific dental implant abutment with a competitor compatible interface. The purpose of a Patient-Specific abutment is to satisfy customer needs that are otherwise difficult to meet with off-the-shelf abutments. They can be manufactured in multiple sizes, shapes, and angles within the limits established in this submission. They frequently incorporate the modifications typically done at a dental laboratory or "chair-side" by a dentist. Traditional methodologies require the customer (dentist/laboratory technician) to begin with a "stock" abutment and use manual subtractive techniques to remove material from this original "stock" design. However, a Patient-Specific abutment will incorporate these same modifications desired by the customer (dentist/laboratory technician) at the time of fabrication at the manufacturing facility.

The engineering drawings list ranges in areas (attributes) of the abutment that may be modified depending upon patient-specific needs.

The abutment is composed of Titanium alloy (Ti6Al4V), and secured to the implant with a separate Titanium alloy screw for retention.

The new abutment will be offered in Narrow CrossFit (NC) Ø 3.3mm and Regular CrossFit (RC) Ø 4.1mm or Ø 4.8mm implant connection sizes.

The provided document is a 510(k) Pre-Market Notification for a dental abutment, which focuses on demonstrating substantial equivalence to predicate devices rather than proving a device meets specific performance criteria through a study with a test set of data. Therefore, many of the requested elements for AI/machine learning device studies are not applicable to this document.

However, I can extract information related to the non-clinical testing performed to support the substantial equivalence claim.

Here's the breakdown based on the provided document:

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

The document does not explicitly define acceptance criteria in a quantitative table format for performance metrics like accuracy, sensitivity, or specificity, as would be expected for an AI/ML device. Instead, "acceptance criteria" are implied by demonstrating compatibility and equivalent mechanical performance to a predicate device through non-clinical testing.

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

• Sample Size for Test Set: The document does not specify a "test set" in the context of an AI/ML study, but for non-clinical testing:
  • Reverse Engineering: Based on "actual measurements taken from Straumann Bone Level implants, abutments and retaining screws." The exact number of units measured is not specified.
  • Fatigue Testing: The number of Zimmer fabricated abutments and OEM implants used for fatigue testing is not specified.
• Data Provenance: The data is internally generated from non-clinical laboratory testing performed by Zimmer Dental Inc. (USA) and references FDA guidance documents. This is prospective data collection for the purpose of regulatory submission.

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

Not applicable. This is not an AI/ML study involving human expert ground truth for classification or diagnosis. The "ground truth" for compatibility and mechanical performance was established through engineering analysis and physical testing against established standards and predicate device performance.

4. Adjudication method for the test set

Not applicable. No expert adjudication method was employed as it was not an AI/ML study requiring human interpretation or consensus for a "test set."

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 a medical device submission for a physical dental abutment, not an AI/ML software. Therefore, no MRMC study or assessment of human reader improvement with AI assistance was performed.

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

Not applicable. This is a physical dental abutment, not an algorithm.

7. The type of ground truth used

For the non-clinical testing:

• Compatibility: "Ground truth" was established by reverse engineering measurements of existing, legally marketed Straumann Bone Level implant components and developing dimensional specifications, and by conducting tolerance and rotational analyses to ensure proper fit.
• Mechanical Fatigue: "Ground truth" was established by comparing the fatigue test results of the new device to the fatigue testing data of the predicate device (#3, Straumann Bone Level Anatomic Abutment), as well as adherence to FDA guidance standards for dental implant abutments.
• Sterilization: Validation against a minimum sterility assurance level (SAL) of 10⁻⁶, a recognized standard.
• MRI Safety: Adherence to FDA guidance for assessing passive implants in an MR environment.

8. The sample size for the training set

Not applicable. This is not an AI/ML device, so there is no training set.

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

Not applicable. There is no training set for an AI/ML model.

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