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The T-FIT is designed to provide a fixed anchorage point for attaching orthodontic appliances, facilitating the orthodontic movement of teeth. It is used temporarily and removed upon completion of the orthodontic treatment for use in patients aged 12 and older. The screws are intended for single use only.

The T-FIT is designed to serve as a fixed anchorage point for attaching orthodontic appliances to facilitate the movement of teeth during orthodontic treatment. The system is intended for temporary use and is removed once treatment is complete. The T-FIT is available in thread diameters Ø1.4 mm, 1.6 mm, and 2.0 mm and thread lengths of 6.0 mm, 8.0 mm, 10.0 mm, 12.0 mm, and 14.0 mm. Thread lengths of 12.0 mm and 14.0 mm are only available with Ø2.0 mm diameter models. All screws are manufactured from Ti-6Al-4V ELI titanium alloy (ASTM F 136-13). The T-FIT is provided non-sterile and is intended for single use only. Additionally, the T-FIT is designed to be used with commonly available dental surgical instruments.

The FDA 510(k) Premarket Notification for the T-FIT device does not contain information typically associated with acceptance criteria and studies for AI/ML-driven devices. The T-FIT is an orthodontic anchorage screw, a physical medical device, and the submission focuses on its material, dimensions, and mechanical performance compared to a predicate device.

Therefore, the requested information regarding acceptance criteria, reported performance, sample sizes for test sets, data provenance, expert ground truth establishment, adjudication methods, MRMC studies, standalone performance, ground truth types, and training set details are not applicable to this specific submission.

The document describes non-clinical performance testing for a physical device, primarily focusing on mechanical and biocompatibility aspects, as well as sterilization:

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

The document describes performance testing conducted according to recognized standards, rather than providing a table of specific acceptance criteria and reported performance values. The objective of these tests is to demonstrate substantial equivalence to 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):

The document does not specify sample sizes for the mechanical tests, nor does it provide details on data provenance as these are physical device tests, not clinical data sets. The tests are "nonclinical," meaning they were conducted in a laboratory setting.

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. Ground truth, in the context of expert review, is not relevant for the mechanical and biocompatibility testing of a physical medical device.

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

Not applicable. Adjudication methods are typically used for establishing ground truth in clinical imaging or diagnostic studies, which is not the nature of the tests described here.

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 type of study is relevant for AI-assisted diagnostic devices, not for a physical orthodontic screw.

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

Not applicable. The T-FIT is a physical device, not an algorithm.

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

Not applicable. The "ground truth" for mechanical testing would be the physical properties measured under standardized conditions, and for biocompatibility, it would be the results from specified biological assays and tests against established safety limits for materials.

8. The sample size for the training set:

Not applicable. The T-FIT is a physical device; there is no "training set" in the context of machine learning.

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

Not applicable.

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