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Glasionomer FX-II is a glass polyalkenoate cement used for dental restorations. Glasionomer FX-II is intended for use as a final restorative for deciduous teeth; a geriatric restorative for Class I, II, III and V cavities and cervical erosions; a final restorative for Class I and II of adult dentition in non-load bearing situations; an intermediate restorative for heavy stress cavities; a core build up; and for pit and fissure fillings.

Glasionomer FX-II is a glass polyalkenoate cement used for dental restorations, for Minimal Intervention (MI) dentistry.

This document describes a 510(k) premarket notification for the "GlasIonomer FX-II" dental cement. The key information regarding performance and testing is found in the "Biocompatibility" section.

Here's the breakdown of the requested information based on the provided text:

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

2. Sample size used for the test set and the data provenance

The document does not specify the sample sizes used for each biocompatibility test. It also does not provide information on the data provenance (e.g., country of origin, retrospective/prospective). Dental cements are typically tested in vitro and in vivo (animal models) for biocompatibility, but the details are not included here.

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

This information is not provided in the document. Biocompatibility testing itself generates objective results (e.g., cell viability, mutation rates) rather than relying on expert interpretation for "ground truth" in the way an imaging AI model might. The interpretation of these results against established standards would be done by qualified toxicologists or biologists, but their number and specific qualifications are not mentioned.

4. Adjudication method for the test set

This is not applicable as the biocompatibility tests produce objective results, not requiring an adjudication method like those used for human-reviewed data sets in AI studies.

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

An MRMC comparative effectiveness study is not mentioned because this document is describing a dental cement, not an AI-powered diagnostic device.

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

This is not applicable as the document describes a dental cement, not an algorithm.

7. The type of ground truth used

The "ground truth" for the biocompatibility tests is based on objective biological and toxicological measurements obtained through standard laboratory protocols. For example:

• Acute oral toxicity: Measured physiological responses in test subjects after oral exposure.
• Bacterial reverse mutation: Observation of bacterial colony growth on specific media.
• In vitro cytotoxicity: Measurement of cell viability or death in culture.
• Subcutaneous implantation: Histopathological examination of tissue reaction at the implant site.
• Sensitization: Observation of allergic reactions in test subjects.

These are established scientific methods with defined endpoints, not expert consensus or pathology reports in the diagnostic sense.

8. The sample size for the training set

This is not applicable as the document describes a dental cement, not a machine learning model. Therefore, there is no "training set."

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

This is not applicable, as there is no training set for a dental cement.

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