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510(k) Data Aggregation
(154 days)
Enamel Coating Resin
Proseal Enamel Coating Resin is a light curing material for sealing the enamel pits and fissures of teeth.
Proseal Enamel Coating Resin is a light-curing fissure sealant and is mainly composed of methacrylate resin, photo initiator system and inorganic fillers. It is packaged in syringes or bottles.
This document is a 510(k) Summary for the Proseal Enamel Coating Resin. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study proving a device meets specific acceptance criteria for performance in a diagnostic or clinical setting.
Therefore, many of the requested fields cannot be filled from the provided text as they relate to the performance of an AI/diagnostic device, which is not what this document describes.
Here's an analysis based on the available information:
1. A table of acceptance criteria and the reported device performance
The document states that in-vitro bench tests were performed and that the "test results indicated that the Proseal Enamel Coating Resin meets the pass/fail criteria and supports substantial equivalence when compared to the predicate device on physical properties." It also notes that the device is classified as Class 2 sealant in accordance with ISO 6874:2015.
The specific acceptance criteria (pass/fail criteria) are implied to be derived from ISO 6874:2015 and FDA guidance "Dental Composite Resin Devices - Premarket Notification [510(k)] Submissions Document issued on: October 26, 2005". However, the document does not list the specific numerical acceptance criteria.
The reported device performance is only described qualitatively as "meets the pass/fail criteria." Specific numeric performance values for each test (depth of cure, flexural strength, shear bonding strength, compressive strength, water sorption, solubility, film thickness, and elastic modulus) are not provided in this summary.
Acceptance Criteria (Derived from ISO 6874:2015 & FDA Guidance) | Reported Device Performance |
---|---|
(Specific numerical criteria not detailed in the document) | Meets criteria |
Depth of Cure | Meets criteria |
Flexural Strength | Meets criteria |
Shear Bonding Strength | Meets criteria |
Compressive Strength | Meets criteria |
Water Sorption | Meets criteria |
Solubility | Meets criteria |
Film Thickness | Meets criteria |
Elastic Modulus | Meets criteria |
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 mentions "in-vitro bench tests" for physical properties and "Biocompatibility tests" but does not specify the sample size for these tests. Data provenance (country of origin, retrospective/prospective) is not mentioned for the testing.
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 is a material science study, not a study evaluating human expert performance or diagnostic accuracy.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. This is a material science study.
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 material science product, not an AI or diagnostic device that would involve human readers.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
Not applicable. This is a material science product.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
For the physical property tests, the "ground truth" would be the scientifically established and standardized measurement protocols and evaluation criteria defined by ISO 6874:2015 and FDA guidance for dental composite resin devices. For biocompatibility tests, the ground truth would be established by ISO 10993 standards.
8. The sample size for the training set
Not applicable. There is no AI algorithm being trained.
9. How the ground truth for the training set was established
Not applicable. There is no AI algorithm being trained.
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