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Perfit CL can be used as an accessory to zirconium dioxide dental restorative material to provide individual tooth (or teeth) shading. It is intended to be used solely by certified dental technicians for fabrication of zirconium dioxide restorations for individual dental patients.

This medical device is used to color the zirconia pre- sintered body, and it is a color solution that makes the color similar to natural teeth by using a brush and immersion.

The provided document is a 510(k) summary for a dental coloring liquid named "Perfit CL." Based on the content, here's a breakdown of the requested information:

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

The document does not specify discrete "acceptance criteria" with numerical targets in the same way one might for diagnostic accuracy metrics (e.g., sensitivity, specificity). Instead, the acceptance criteria are implicitly tied to demonstrating substantial equivalence to the predicate device through various non-clinical tests and technical characteristic comparisons. The reported performance is that the device met these criteria by demonstrating equivalence.

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 primarily describes non-clinical bench testing rather than clinical or user performance studies on a "test set" of patient data. For the listed non-clinical tests (e.g., biocompatibility, shelf-life, physical properties), the sample sizes are not specified. The provenance of the data (country of origin, retrospective/prospective) is also not stated beyond the applicant's origin in South Korea.

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)

This information is not applicable as the document describes non-clinical testing of a dental coloring liquid, not a diagnostic or AI-assisted device requiring expert-established ground truth. The "ground truth" for the tests would be established by standard laboratory methods and equipment as per the referenced ISO standards. The document mentions that differences in packaging volume, shade, and storage conditions "can be differentiated depending on experts' determination," implying that dental technicians/experts evaluate the aesthetic outcome in practice, but this is not defined as part of the formal 'test set' ground truth establishment for the 510(k) submission.

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

This information is not applicable as the document describes non-clinical testing of a dental coloring liquid and does not involve human adjudication of results in a clinical study context.

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 was not done. This device is a dental coloring liquid, not an AI-assisted diagnostic tool.

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

This concept is not applicable to a dental coloring liquid. There is no algorithm or AI component in "Perfit CL."

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

For the non-clinical tests, the "ground truth" is established by adherence to internationally recognized standards (e.g., ISO 10993 for biocompatibility, ISO 6872 for performance) and precise laboratory measurements of physical and chemical properties. It is based on standardized laboratory methods and physical/chemical criteria, not expert consensus, pathology, or outcomes data in a clinical sense.

8. The sample size for the training set

This information is not applicable as the document describes non-clinical testing of a dental coloring liquid, not a machine learning or AI-based device that requires a "training set."

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

This information is not applicable as the document describes non-clinical testing of a dental coloring liquid, not a machine learning or AI-based device.

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