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510(k) Data Aggregation
(158 days)
Dentis i-Clean System
Dentis i-Clean System is indicated for use in partially or fully edentulous mandibles and maxillae, in support of single or multiple unit restorations including; cemented retained, screw retained, or overdenture restorations, and terminal or intermediate abutment support for fixed bridgework. This system is dedicated for one and two stage surgical procedures. This system is intended for delayed loading.
Dentis i-Clean system is intended for use as an aid in prosthetic restoration. It consists of Abutments and Abutment screws.
The Dentis i-Clean System is a dental implant system consisting of abutments and abutment screws. The device is not an AI/ML device, and therefore the standard acceptance criteria for such devices, along with the study design elements listed, do not apply.
Here's an overview of the non-clinical testing performed to demonstrate substantial equivalence, as described in the provided document:
1. A table of acceptance criteria and the reported device performance
Since this is not an AI/ML device, there are no performance metrics like sensitivity, specificity, or AUC with acceptance criteria described in the document. The substantial equivalence is based on meeting engineering and biological safety standards for medical devices.
The non-clinical tests performed and their respective standards are:
| Acceptance Criteria (Test) | Reference Standard | Reported Device Performance (Compliance) |
|---|---|---|
| Fatigue Testing | ISO 14801:2016 | Performed under worst-case scenario. |
| End-user Sterilization Validation (PEEK, CCM) | ISO 17665-1, -2, ISO 11737-1, FDA guidance "Reprocessing Medical Devices..." (March 17, 2015) | Validated the recommended sterilization for all subject devices delivered non-sterile to be end-user sterilized. |
| End-user Sterilization Validation (Ti-6Al-4V ELI) | ISO 17665-1, -2, ISO 11737-1 (leveraged from K111364) | Leveraged from predicate device, demonstrating substantial equivalence. |
| Biocompatibility (Ti-6Al-4V ELI) | ISO 10993-1:2009 (leveraged from K171027 and K150344) | Leveraged from predicate device, demonstrating substantial equivalence. |
| Biocompatibility (PEEK, CCM) | ISO 10993-1:2009 (leveraged from K171027) | Leveraged from predicate device, demonstrating substantial equivalence. |
| MRI Safety Review | FDA guidance "Testing and Labeling Medical Devices for Safety in the Magnetic Resonance (MR) Environment" | Non-clinical worst-case MRI review performed using scientific rationale and published literature. |
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 a "test set" in the context of AI/ML. The tests mentioned are non-clinical (mechanical, sterilization, biocompatibility, MRI review). The sample sizes for these engineering and biological tests are not detailed in this summary but are typically defined by the respective ISO standards. The data provenance is presumed to be from laboratory testing performed by, or on behalf of, Dentis Co., Ltd. (Korea, as per submitter address) or the referenced predicate device manufacturers. These are not human data, so "retrospective or prospective" does not apply.
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, as this is not an AI/ML device involving human experts for ground truth establishment.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable, as this is not an AI/ML 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, as this is not an AI/ML device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable, as this is not an AI/ML device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
Not applicable in the context of AI/ML. For medical devices, "ground truth" is typically defined by adherence to established engineering standards (e.g., ISO 14801 for fatigue) and biological safety standards (e.g., ISO 10993 for biocompatibility, ISO 17665 for sterilization).
8. The sample size for the training set
Not applicable, as this is not an AI/ML device.
9. How the ground truth for the training set was established
Not applicable, as this is not an AI/ML device.
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