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The s-Clean Tapered II RBM Implant System is an endosseous dental implant is indicated for surgical placement in the upper and lower jaw arches, to provide a root form means for single or multiple-units prosthetic appliance attachment to restore a patient's chewing function. Implants can be placed with a conventional two stage surgical process with an option for transmucosal healing or they can be placed in a single stage surgical process for immediate loading. Immediate loading is restricted to the anterior mandible based on four splinted Interforaminal placed implants.

The s-Clean Tapered II RBM Implant System is a dental implant made of titanium metal (Titanium grade 4) intended to be surgically placed in the bone of the upper or lower jaw arches. This implant system has internal hex connection, 1.5° tapered body, bone level and submerged type that are similar to other commercial available products based on the intended use, technology used, the claims, the material composition employed and performance characteristics. The fixture has been treated with RBM (Resorbable Blasted media).

The s-Clean Tapered II RBM Implant System diameter and lengths are below:

• Diameter Ø 3.7 with lengths of 7mm, 8mm, 10mm, 12mm and 14 mm -
• Diameter 0 4.1 with lengths of 7mm, 8mm, 10mm, 12mm and 14 mm -
• Diameter Ø 4.3 with lengths of 7mm, 8mm, 10mm, 12mm and 14 mm -
• -Diameter Ø 4.8 with lengths of 7mm, 8mm, 10mm, 12mm and 14 mm

The packaging has composed of fixture with cover screw. The fixtures are supplied sterile by gamma sterilization. The fixtures are provided as set-packing with the cover screw. The purpose of this submission is to add new fixtures.

The provided text describes a 510(k) premarket notification for a dental implant system. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving safety and effectiveness through extensive standalone studies and acceptance criteria for performance metrics.

Therefore, the information requested (acceptance criteria, specific study design for meeting these criteria, sample sizes, ground truth establishment, expert roles, MRMC studies, and standalone performance) is largely not applicable in the context of this 510(k) submission as it is presented.

Here's why and what information can be extracted:

• No specific acceptance criteria listed for device performance: The document does not define numerical performance targets (e.g., specific accuracy, sensitivity, specificity values) for the "s-Clean Tapered II RBM Implant System." Instead, it aims to demonstrate that its characteristics are "substantially equivalent" to predicate devices.
• No standalone study to "prove" device meets acceptance criteria: The submission relies on comparison to predicate devices and existing test data from those predicates.
• No sample sizes, data provenance, expert ground truth, adjudication, or MRMC studies for "device performance" in the AI sense: These concepts are typically relevant for AI/ML device submissions where classification, detection, or other diagnostic performance metrics are being evaluated. This document concerns a physical medical device (dental implant).

However, I can extract information related to the non-clinical testing that was performed to support substantial equivalence. While these are not performance metrics in the AI sense, they serve as the "proof" that the device is equivalent to its predicate.

Here's a summary of the relevant information from the document, tailored as much as possible to your request, but highlighting the differences in context:

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

As mentioned, there are no acceptance criteria for "performance" as one might expect for a diagnostic AI device. Instead, the "performance" demonstrated is substantial equivalence to predicate devices, supported by adherence to manufacturing standards and existing test data.

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 specified in terms of clinical subjects. The non-clinical tests (fatigue, sterilization, shelf-life) would have involved specific numbers of implant units or samples, but these are not disclosed in this summary. The submission references data from predicate devices, implying those predicate devices underwent testing.
• Data Provenance: Not explicitly stated as "country of origin for data." However, the device manufacturer (Dentis Co., Ltd.) is from South Korea. The predicate devices are also manufactured by Dentis Co., Ltd. The testing referenced aligns with FDA guidance documents, suggesting it would meet U.S. regulatory expectations. The type of data is non-clinical testing data rather than patient data (e.g., retrospective or prospective clinical data).

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 pertains to clinical ground truth, often for diagnostic devices. For a physical implant, "ground truth" is established by manufacturing specifications, material properties, and engineering standards. There is no mention of human experts establishing "ground truth" in this context; instead, the evaluation is based on engineering tests and comparison to established, legally marketed devices.

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

• Not Applicable: This is relevant for subjective assessments, particularly in clinical or imaging studies where multiple readers' opinions need to be reconciled. For a physical device undergoing non-clinical engineering tests (like fatigue or sterilization), the "adjudication" is based on objective measurements against predetermined standards.

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: MRMC studies are specific to evaluating diagnostic performance, especially for AI-assisted systems, and typically involve human readers interpreting cases. This submission is for a physical dental implant and does not involve AI or human interpretation of medical images/data.

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

• Not Applicable: This refers to the performance of an AI algorithm. This device is a physical dental implant.

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

• For Non-Clinical Testing: The "ground truth" for non-clinical tests like fatigue, sterilization, and shelf-life is defined by established engineering standards, material specifications, and regulatory guidance documents. For instance, a fatigue test determines if the implant can withstand a certain number of stress cycles without fracture, as dictated by standards like ASTM or ISO. The "truth" is the device's physical response measured against a quantitative standard, not expert consensus on a diagnosis.
• For Substantial Equivalence: The ultimate "ground truth" for this 510(k) submission is that the device is as safe and effective as a legally marketed predicate device. This is established through the detailed comparison of design, materials, indications for use, and existing testing data.

8. The sample size for the training set

• Not Applicable: This refers to training data for AI/ML algorithms. This submission is for a physical device and involves no "training set."

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

• Not Applicable: As above, no training set or AI involved.

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