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The Elliptic Matrix attaches to the retentive anchor by functioning like a spring when the four lamellae are activated. The titanium housing gives the matrix more support and retention for the denture.

AI/ML Overview

This document is a 510(k) premarket notification for a medical device called the "Elliptic Matrix," an endosseous dental implant component. The purpose of this notification is to demonstrate substantial equivalence to a legally marketed predicate device, rather than to establish new performance criteria through extensive studies. As such, the information typically requested for AI/software-based devices (e.g., acceptance criteria, detailed study results, multi-reader multi-case studies, ground truth establishment for training) is not present in this type of submission.

Therefore, many of the requested fields cannot be filled as they pertain to performance testing that is not part of a substantial equivalence claim for a physical, mechanical medical device like this one.

Here's a breakdown of the available information:

Device Name: Elliptic Matrix
Intended Use: The Elliptic Matrix is attached onto the retentive anchor abutment to provide support and retention for a denture.

1. Table of acceptance criteria and the reported device performance

Acceptance Criteria	Reported Device Performance
Not specified in this document for the Elliptic Matrix.	The device is deemed substantially equivalent to the predicate Gold Matrix (K894844). The basis for this equivalence is that the intended use is identical, the design is "almost identical," and the labeling/instructions for use are similar. This implies that the Elliptic Matrix is expected to perform to the same standards as the predicate device.

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

Sample size for test set: Not applicable. This submission is for a physical medical device and relies on substantial equivalence to a predicate, not performance data from a specific test set.
Data provenance: Not applicable.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable. This is not an AI/software device and does not involve expert-established ground truth for a test set.

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

Not applicable.

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 physical dental implant component, not an AI-assisted diagnostic tool.

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

Not applicable.

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

Not applicable. The "ground truth" in this context is the performance and safety established for the predicate device to which it claims equivalence.

8. The sample size for the training set

Not applicable. This device does not involve machine learning or a training set.

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

Not applicable.

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