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Indications for use:
*Class III and V restorations

• • Restoration of minimally invasive cavity preparations (including small, non stress-bearing occlusal restorations)
    *Base/liner under direct restorations
    *Repair of small defects in esthetic indirect restorations
    *Pit and fissure sealant
    *Undercut blockout
    *Repair of resin and acrylic temporary materials

Apoller Flow-Light Cure Flowable Composite is a low viscosity light activated flowable nanocomposite device. The device is comprised of a syringe with dispensing tips. It consists of methmethacrylate monomers, inorganic fillers and nanoparticles. Apoller Flow Light Cure Flowable Composite contains BisGMA, UDMA, TEGDMA, photo initiator, stabilizer and inorganic fillers including barium glass powder, strontium glass powder and nanosilica. The filler loading is about 56% by weight. The particle size varies from 0.03 to 1 micron. Apoller Flow Light Cure Flowable Composite series is packed in a plastic syringe with a bend metal injection needle heads for ease of usage, its model is Flowable and comes with Refill Syringe of 3.0g /syringe and 1.5 g /syringe. It is available in a variety of 15 tooth-colored shades.

The provided FDA 510(k) summary for the "Apoller Flow Light Cure Flowable Composite" describes its substantial equivalence to a predicate device, "Filtek™ Supreme Ultra Flowable Restorative." The document outlines various performance aspects but primarily focuses on demonstrating equivalence to the predicate device rather than establishing specific acceptance criteria for the new device and then proving it meets those criteria with a standalone study. Instead, it compares the new device's properties to existing standards and the predicate device.

Here's an attempt to extract the requested information based on the provided text. It's important to note that many of the specific details regarding study design, sample sizes for test/training sets, expert qualifications, and adjudication methods (which are typical for AI/software device studies) are not present in this type of submission for a dental composite. This document focuses on material properties and biocompatibility.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly that the "Apoller Flow Light Cure Flowable Composite" performs comparably to the "Filtek™ Supreme Ultra Flowable Restorative" predicate device and meets relevant ISO standards. The performance is reported in terms of various physical properties and biocompatibility, demonstrating equivalence.

• Depth of cure (mm): Compared, results demonstrate substantial equivalence.
• Flexural Strength (MPa): Compared, results demonstrate substantial equivalence. |
  | | | - Water sorption (µg/mm³): Compared, results demonstrate substantial equivalence.
• Water solubility (µg/mm³): Compared, results demonstrate substantial equivalence.
• Shade Color stability after irradiation and water sorption: Compared, results demonstrate substantial equivalence. |
  | | | - Radio-opacity (mm): Compared, results demonstrate substantial equivalence. |
  | Biocompatibility | Substantially equivalent to predicate device per ISO 7405, ISO 10993-1, -3, -5, -11 | Concluded to be substantially equivalent to the primary predicate device based on comparative test report. |
  | Technological | Equivalent to predicate device | - Intended Use: Equivalent
• Method of Polymerization: Equivalent (Light Cured)
• Chemical composition: Equivalent (Glass filled Methmethacrylate monomer resins, Nanoparticle) |
  | | | - Mechanical/physical properties: Equivalent (Low viscosity, Flowable)
• Application process and use: Similar
• Camphorquinone / amine photoinitiator system: Equivalent |
  | | | - Methacrylate-based resin matrix: Equivalent
• Silane treated fillers: Equivalent
• Bonded with permanent dental adhesive: Equivalent |

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

The document does not specify exact sample sizes for the "comparison testing" of physical properties. These would typically be determined by the specific ISO standards (e.g., ISO 4049) applied to dental materials, which involve a certain number of specimens for each test. The data provenance is from non-clinical performance testing conducted by the manufacturer (SINO-DENTEX CO., LTD., Changchun, China). The data is retrospective in the sense that it was generated for the purpose of the 510(k) submission, not as part of an ongoing prospective study.

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

This information is not applicable to this type of device and submission. Dental composite materials do not typically involve expert review for "ground truth" in the same way an AI diagnostic image analysis device would. The "ground truth" for material properties is established through standardized laboratory testing (e.g., ISO 4049).

4. Adjudication method for the test set

This information is not applicable. There is no adjudication process involving multiple human readers for validating the performance of a dental material.

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 study was not done. This type of study is relevant for AI-powered diagnostic devices involving human interpretation, not for dental composite materials.

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

This information is not applicable. The device is a dental material, not an algorithm.

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

The "ground truth" for the performance claims (physical properties, biocompatibility) is based on standardized laboratory testing methods (e.g., ISO 4049 for physical properties; ISO 7405, ISO 10993-1, -3, -5, -11 for biocompatibility). The performance of the new device is then compared against that of the predicate device and the requirements of these standards.

8. The sample size for the training set

This information is not applicable. The device is a physical material, not a machine learning algorithm that requires a training set.

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

This information is not applicable. As the device is a physical material, there is no training set or ground truth in the context of machine learning.

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