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Dentium Prosthetics are intended for use as an aid in prosthetic rehabilitation.

The purpose of this submission is to change the sterilization method of Healing Abutments and Cover Screws. These devices which have been provided non-sterilized by gamma radiation.

Healing Abutments are used provisionally as an accessory to endosseous dental implant during healing period to prepare gingival tissue for acceptance of a final abutment. Healing Abutments are designed to aid in soft tissue contouring during the healing period after implant placement, creating an emergence profile for the final abutment. Cover Screws are used provisionally as an accessory to protect the inner features of the implant.

The Healing Abutments and Cover Screws are prefabricated and made of Ti-6Al-4V ELI (ASTM F136). These devices are sterilized using gamma radiation method and intended for single use only.

The provided document is a 510(k) premarket notification for "Healing Abutments and Cover Screws." This type of submission focuses on demonstrating substantial equivalence to a predicate device, rather than proving a device meets specific performance acceptance criteria through the kind of rigorous, large-scale studies typically associated with AI/ML-based medical devices or novel technologies.

Therefore, many of the requested details, such as sample size for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, and training set details, are not applicable to this specific submission. This document describes a change in the sterilization method for existing devices, not a new device with performance metrics that require extensive clinical validation studies beyond sterilization and biocompatibility.

Here's an analysis based on the information available in the document:

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

For a 510(k) submission concerning a change in sterilization method for mechanical components like healing abutments and cover screws, the "acceptance criteria" revolve around demonstrating that the new sterilization method achieves the required sterility assurance level and does not adversely affect the device's material properties or function, maintaining its substantial equivalence to the predicate.

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

• Sample Size: Not explicitly stated as a separate "test set" in the context of clinical performance data typical for AI/ML devices. The "tests" here are primarily engineering and laboratory validations:
  • Sterilization Validation: ISO 11137 standards define the number of units and replicates required for sterility testing (e.g., bioburden determination, dose mapping, sterility testing), which are often small, specific lots. This is standard laboratory validation, not a patient-based test set.
  • Aging Studies: ASTM F1980 dictates sample sizes for accelerated aging, again, laboratory testing of physical samples.
  • Biocompatibility: Relies on a prior submission (K041368) which presumably included its own biocompatibility testing. No new "sample size" for a clinical test set is mentioned for biocompatibility here.
• Data Provenance: The studies are laboratory-based ("Non-clinical testing data"). The manufacturer is located in the Republic of Korea (Dentium Co., Ltd.). The data would be derived from their internal validation processes. It is neither retrospective nor prospective in the sense of patient studies.

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 submission does not involve image interpretation or clinical diagnosis where expert ground truth would be established. The "ground truth" for sterilization is a defined SAL, verified by microbiological and physical testing per ISO standards. The "ground truth" for material properties is based on ASTM standards and prior biocompatibility data.

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

• Not Applicable. As there is no clinical "test set" based on human interpretation or an AI algorithm's output requiring adjudication, this concept does not apply.

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 traditional medical device (dental implants and accessories), not an AI-assisted diagnostic or therapeutic device. Therefore, no MRMC study, human reader improvement, or AI assistance is relevant.

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

• Not Applicable. This is a physical medical device, not an algorithm.

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

• The "ground truth" for this submission is based on:
  • Standardized Sterility Assurance: Achieving a defined SAL of 10^-6, verified through validated sterilization processes and testing compliant with ISO 11137-1 and ISO 11137-2.
  • Material Standards: Biocompatibility established against Ti-6Al-4V ELI (ASTM F136) as per regulations and previous submissions.
  • Engineering Performance: Shelf-life demonstrated through accelerated and real-time aging studies per ASTM F1980.
  • Substantial Equivalence: Demonstrated by comparing engineering specifications and intended use against legally marketed predicate devices.

8. The sample size for the training set

• Not Applicable. This involved physical device manufacturing and validation, not machine learning model training.

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

• Not Applicable. (See point 8)

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