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510(k) Data Aggregation
(154 days)
OptiFlow II Flowable Composite, LC is intended for use as:
- Repair of minimally invasive cavity (including non-stress bearing areas)
- Pit and fissure sealant
- Class III-V restorations
- Repair of porcelain restorations
- Repair of ceramic/composite veneers
OptiFlow II Flowable Composite, LC is a light cure resin-based flowable restorative dental composites. The restorative is packaged in capsules and syringes. The fillers are a combination of radiopaque inorganic fillers and advanced nano-silicas with an average particle size of 0.7 microns to produce a loading approximately 57% by weight (40% by volume). All shades have a radiopacity of 200%.
The available text describes the 510(k) summary for OptiFlow II Flowable Composite, LC, a dental material. The submission focuses on demonstrating substantial equivalence to a predicate device through physical tests.
Here is the information structured according to your request, with a note where the information is not provided in the text:
1. A table of acceptance criteria and the reported device performance
The document states that the device was evaluated for Flexural Strength, Young's Modulus, Compressive Strength, Diametral Tensile Strength, and Rockwell Hardness and compared to the predicate device. However, the specific acceptance criteria (e.g., minimum values or range for each test) and the reported device performance (the actual numerical results for OptiFlow II and the predicate) are not included in this summary. It only states that the device is "substantially equivalent."
| Acceptance Criteria | Reported Device Performance (OptiFlow II Flowable Composite) |
|---|---|
| Specific numerical criteria for each property (e.g., Flexural Strength > X MPa) | Not provided in the text. The document states "substantially equivalent" to predicate device. |
| Specific numerical criteria for each property (e.g., Young's Modulus > Y GPa) | Not provided in the text. The document states "substantially equivalent" to predicate device. |
| Specific numerical criteria for each property (e.g., Compressive Strength > Z MPa) | Not provided in the text. The document states "substantially equivalent" to predicate device. |
| Specific numerical criteria for each property (e.g., Diametral Tensile Strength > A MPa) | Not provided in the text. The document states "substantially equivalent" to predicate device. |
| Specific numerical criteria for each property (e.g., Rockwell Hardness > B) | Not provided in the text. The document states "substantially equivalent" to predicate device. |
2. Sample size used for the test set and the data provenance
The document mentions "data from bench testing" but does not specify the sample size used for these tests. It also does not indicate the provenance (e.g., country of origin, retrospective or prospective) of this test data. Bench testing is typically conducted in a laboratory setting.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This document describes physical, bench-top testing of a dental material. It does not involve human interpretation or subjective assessment by experts for establishing ground truth in the way an AI diagnostic device would. Therefore, this question is not applicable to the provided context.
4. Adjudication method for the test set
Since this is bench testing of physical properties and not an expert-driven assessment, no adjudication method (like 2+1 or 3+1) was used.
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 MRMC comparative effectiveness study was done, as this submission is for a dental material and not an AI-assisted diagnostic device involving human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This question is not applicable as the device is a dental material, not an algorithm.
7. The type of ground truth used
The "ground truth" in this context is the measured physical properties (Flexural Strength, Young's Modulus, Compressive Strength, Diametral Tensile Strength, and Rockwell Hardness) of the materials being tested. These are quantitative measurements derived from standardized laboratory tests.
8. The sample size for the training set
This is a physical material, not an AI model, so there is no training set in the typical sense. Physical properties are inherent to the material formulation and manufacturing process, not "trained" on data.
9. How the ground truth for the training set was established
As there is no training set for a physical material, this question is not applicable.
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