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The Osstem Implant is indicated for use in partially or fully edentulous mandibles and maxillae, in support of single or multiple-unit restorations including; cemented retained, or overdenture restorations, and final or temporary abutment support for fixed bridgework. It is intended for delayed loading. Ultra Wide Fixture System is intended to be used in the molar region.

The SS SA Fixture is a dental implant made of titanium metal intended to be surgically placed in the bone of the upper or lower jaw arches. Fixture is made of pure titanium metal and supplied sterile. The surface is SA, Sandblasting and Acid etching, treated.

This document is a 510(k) Premarket Notification from Osstem Implant Co., Ltd. to the FDA for their "SS SA Fixture" dental implant. It aims to demonstrate substantial equivalence to legally marketed predicate devices rather than proving the device meets specific acceptance criteria through a study with performance metrics as one might see for a diagnostic AI device.

Therefore, the requested information elements (acceptance criteria table, sample sizes, expert qualifications, adjudication methods, MRMC study, standalone performance, ground truth types, training set size, and training ground truth establishment) are generally not applicable in the context of this 510(k) submission for a non-AI dental implant.

However, I can extract information related to the device's technical specifications and the non-clinical testing performed to establish substantial equivalence.

Here's an adaptation of the requested format based on the available information:

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

For a dental implant, "acceptance criteria" usually refers to meeting established standards (e.g., ISO, ASTM) and demonstrating equivalence to predicate devices, rather than specific performance metrics like sensitivity/specificity for an AI algorithm. The device performance is primarily assessed through non-clinical testing to ensure its physical and mechanical properties are comparable or superior to the predicate.

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

• Test Set (for non-clinical studies): Specific sample sizes for each non-clinical test (BIC, Surface Area, Pullout, Fatigue) are not explicitly stated in the summary, only that these tests were conducted "with SS SA Fixture containing implants of lengths less than 7mm." The data provenance is implied to be from the manufacturer's internal testing. This is not patient data, but material/device performance data.
• Data Provenance: Not applicable in the sense of patient data origin as these are non-clinical (laboratory/bench) tests.

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

• Not applicable as this is a 510(k) for a physical medical device, not a diagnostic AI device requiring expert-established ground truth from images or clinical data. The "ground truth", in this context, refers to established engineering and material science standards.

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

• Not applicable for non-clinical bench testing of a physical device.

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-based device, and no clinical studies were submitted.

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

• Not applicable as this is not an AI algorithm.

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

• The "ground truth" for this device's evaluation relies on:
  • Regulatory Standards: Compliance with FDA regulations (21 CFR Part 872.3640), Class II Special Controls, and international standards (e.g., ISO 14801 for fatigue testing, ASTM F67 for material).
  • Predicate Device Equivalence: The established safety and effectiveness of the legally marketed predicate devices (K120847, K161604).
  • Scientific Principles: Established principles of biocompatibility, mechanical engineering, and material science.

8. The sample size for the training set

• Not applicable. This is a physical device, not an AI model, and therefore does not have a "training set."

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

• Not applicable. No training set as it's not an AI model.

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