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S.I.N. Dental Implant System is intended for placement in the maxillary or mandibular arch to provide support for single-unit or multi-unit restorations. When a one-stage surgical approach is applied, the S.I.N. Dental Implant System is intended for immediate loading when good primary stability is achieved and with appropriate occlusal loading.

S.I.N. Dental Implants with lengths of 18, 20, 22, or 24 mm be tilted up to 30°. When used in the mandible or maxilla with implants with lengths of 18, 20, 22, or 24 mm at an angulation of 30°, a minimum of four implants must be used and must be splinted. When placed in the maxilla with lengths of 18, 20, 22, or 24 mm at angulations between 0° and less than 30°, the S.I.N. Dental Implants are only indicated for multiple unit restorations in splinted applications that utilize at least two implants.

The purpose of this submission is to add components to the S.I.N. Dental Implant System, which includes components cleared previously in K211921, K200992, and K170392.

This submission includes dental implants Epikut S with a Morse taper (CM) abutment interface and an acid-etched endosseous surface, and Epikut S Plus implants with an endosseous surface produced by acidetching followed by application of a hydroxyapatite coating (HA™M). The implant design and endosseous surfaces are nearly identical to the Epikut Plus CM implants cleared in K211921, with the exception of the implant-abutment connection (subject device 16° Morse taper, K211921 11.5° Morse taper), the additional body/platform diameter (4.0 mm), and the longer lengths (18, 20, 22, and 24 mm).

All subject device dental implants are manufactured from unalloyed titanium conforming to ASTM F67. The acid etching procedure is applied to all subject device dental implants. The acid etching process in this submission is identical to the process used to manufacture the dental implants cleared in K211921, and the HA100 surface treatment is identical to that cleared in K211921.

This FDA 510(k) summary (K222231) describes a dental implant system and focuses on demonstrating substantial equivalence to previously cleared predicate devices, rather than on presenting a study with specific acceptance criteria, test sets, or performance metrics in the way these terms are typically used for AI/ML-based diagnostic devices.

The document is a regulatory submission for a medical device (S.I.N. Dental Implant System), not a study evaluating algorithm performance. Therefore, it does not contain information about:

• A table of acceptance criteria and reported device performance in the context of an algorithm's diagnostic accuracy.
• Sample sizes, data provenance, number of experts, adjudication methods for a test set.
• Multi-Reader Multi-Case (MRMC) comparative effectiveness studies.
• Standalone algorithm performance.
• Sample size for training sets or how ground truth for training sets was established.

Instead, the document focuses on non-clinical performance data to show that the new components of the S.I.N. Dental Implant System (subject device) are as safe and effective as existing legally marketed devices.

Here's an breakdown of the acceptance criteria (or rather, the demonstration of equivalence) and the studies (non-clinical tests and analyses) that prove the device meets these criteria, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria here are based on demonstrating that the subject device's design, materials, manufacturing, sterilization, and performance characteristics are substantially equivalent to predicate devices already cleared by the FDA. The performance data presented are non-clinical and relate to the physical and biological properties of the implant.

2. Sample Size Used for the Test Set and Data Provenance

This is not applicable as this document describes a 510(k) submission for a physical medical device, not an algorithm's test set. The "test sets" here refer to batches of physical devices or materials undergoing non-clinical laboratory testing. The provenance of the data is the manufacturer (S.I.N. - Sistema de Implante Nacional S.A.) or its testing facilities, and the studies are non-clinical evaluations.

3. Number of Experts Used to Establish the Ground Truth and Qualifications

This is not applicable for a non-clinical device submission. Ground truth, in this context, would relate to objective measurements against established standards (e.g., ASTM, ISO standards) rather than expert consensus on medical images.

4. Adjudication Method

Not applicable. Adjudication methods are typically associated with resolving discrepancies in expert interpretations during clinical or algorithm performance studies. The non-clinical tests described have defined protocols and objective pass/fail criteria.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No. This type of study is relevant for evaluating the impact of an AI algorithm on human reader performance, which is not the subject of this 510(k) submission for a dental implant.

6. Standalone Performance Study

No. This refers to the performance of an algorithm without human intervention. This document details the performance characteristics of a physical implant device, not an algorithm.

7. The Type of Ground Truth Used

The "ground truth" for the non-clinical tests is established by compliance with recognized consensus standards (e.g., ISO, ASTM, AAMI) and the device's adherence to its design specifications, materials testing, and performance against these standards. For example:

• Sterility: Achieved according to ISO 11137-1 and ISO 11137-2.
• Bacterial Endotoxin: Meets limits (< 20 EU/device) as per ANSI/AAMI ST72.
• Packaging: Integrity verified against ASTM F1929 and F88/F88M.
• Biocompatibility: Evaluated against ISO 10993-1.
• MR Safety: Assessed against ASTM F2052, F2213, F2182, F2119.
• Mechanical Performance: Demonstrated through engineering analysis applying previous mechanical testing (K200992).
• Material Composition: Conforms to ASTM F67.

8. The Sample Size for the Training Set

Not applicable. This is not an AI/ML device.

9. How the Ground Truth for the Training Set Was Established

Not applicable. This is not an AI/ML device.

In summary, this 510(k) pertains to a physical dental implant and uses non-clinical testing and engineering analysis to establish substantial equivalence to previously cleared predicate devices, rather than performing clinical studies or AI/ML algorithm validation.

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