(269 days)
visio.lign color: Characterization with colour effects on the surface of composite restorations, denture base materials and artificial denture teeth.
visio.lign shield: Surface coating and wear resistance of composite restorations, denture base materials and artificial denture teeth.
visio.lign shield & color is a light-curing, transparent or coloured, acrylate-based glossy coating.
visio.lign color achieves colour effects on the surface of composite restorations, denture base materials and artificial denture teeth.
visio.lign color is available in 17 shades.
visio.lign shield provides a surface coating on composite restorations, denture base materials and artificial denture teeth. visio.lign shield is available in the thin-bodied version visio.lign shield LV and in the higher-viscosity version visio.lign shield HV.
The provided text describes a 510(k) premarket notification for dental coating materials (visio.lign color and visio.lign shield). This document focuses on demonstrating substantial equivalence to a predicate device (Optiglaze Color, K133836) through non-clinical bench testing.
Based on the content, the document does not describe a study involving an AI/Machine Learning device or a Multi-Reader Multi-Case (MRMC) comparative effectiveness study. The performance testing mentioned is entirely focused on "Bench testing" for material properties such as bond strength, color stability, surface roughness, and viscosity.
Therefore, many of the requested points related to AI/ML device performance, human reader studies, ground truth establishment, and training/test sets are not applicable to this submission.
Here's a breakdown of what can be answered based on the provided text:
1. A table of acceptance criteria and the reported device performance
The document states: "The design specifications of the subject device were met in the bench testings carried out. This demonstrates that the product fulfills its intended purpose and device description and shows substantial equivalence to the predicate device." However, specific numerical acceptance criteria or reported performance values (e.g., "bond strength was X MPa, meeting criteria of >Y MPa") are not provided in this summary.
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Not specified in text | "The design specifications of the subject device were met in the bench testings carried out." |
The types of tests conducted were:
- Bond strength
- Colour stability
- Surface roughness
- Viscosity
2. Sample sized used for the test set and the data provenance
- Sample Size: Not specified.
- Data Provenance: The tests are "Bench testing," implying laboratory-based testing of the physical material properties. No country of origin for data or retrospective/prospective nature is mentioned as it's not clinical data.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Not applicable. This submission is for material properties tested via bench studies, not diagnostic performance requiring expert interpretation of images or other clinical data.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not applicable. See point 3.
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
- No. An MRMC study was not conducted. This is a 510(k) for dental coating materials, not an AI/ML diagnostic device for human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not applicable. This device is a physical dental material, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- The "ground truth" for this device would be the established scientific and engineering standards and methods for testing material properties (e.g., ISO standards for dental materials, internal specifications for bond strength, color stability, etc.). It's based on objective physical measurements, not human interpretation or clinical outcomes in the same way as a diagnostic AI.
8. The sample size for the training set
- Not applicable. This is not an AI/ML device that requires a training set.
9. How the ground truth for the training set was established
- Not applicable. See point 8.
§ 872.3310 Coating material for resin fillings.
(a)
Identification. A coating material for resin fillings is a device intended to be applied to the surface of a restorative resin dental filling to attain a smooth, glaze-like finish on the surface of the filling.(b)
Classification. Class II.