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NextDent Ortho Flex is a 3D print resin intended for the manufacturing of 3D printed dental splints and retainers. To retain the regulated dentition.

NextDent Ortho Flex is intended exclusively for professional dental work.

Light-Cure Resin, provided in a container.

NextDent Ortho Flex is a dimethacrylic based light-cure resin with pigments, polymerized via photo initiators in a 3D printer setting for fabrication of splints and retainers for long term repeated use.

Fabrication of splints and retainers with NextDent Ortho Flex requires a computer-aided and manufacturing (CAD/CAM) system that includes the following additive printer and post-cure unit:

Printer: Brand: 3D Systems, Type: NextDent 5100 Figure 4, Software: 3D Sprint
Post-cure unit: Brand: NextDent, Type: LC-3DPrint Box, Software: n.a.

Printer and resin must be optimized to each other in order to get complete and precise printed parts.

Both the NextDent™5100 Figure4® 3D printer and the post-curing lightbox NextDent™ LC-3DPrint Box make use of a UV light source to polymerize the NextDent Ortho Flex resin.

NextDent™5100 Figure4® 3D printer or NextDent™ LC-3DPrint Box is not included with the device.

Cured parts are finished using conventional dental methods and instruments. NextDent 3D printed cured parts should be cleaned with nonchemical products.

Materials of Use: dimethacrylate-based resins with photo-initiator and pigments.

The provided text is a 510(k) summary for a dental resin product, NextDent Ortho Flex, and primarily discusses its substantial equivalence to a predicate device based on material characteristics and performance in specific laboratory tests. It does not contain information related to an AI/ML-enabled medical device, diagnostic performance, or studies involving human readers or ground truth established by experts/pathology/outcomes data.

Therefore, I cannot extract the requested information regarding acceptance criteria and a study proving device performance in the context of an AI/ML device. The document focuses on the physical and chemical properties of a 3D printable dental resin.

To illustrate, here's what the document does discuss regarding "acceptance criteria" and "study" for NextDent Ortho Flex, which is very different from an AI/ML device:

Acceptance Criteria and Study for NextDent Ortho Flex (Dental Resin)

The "acceptance criteria" for this device are based on its compliance with established industry standards for dental materials, specifically ISO 20795-2:2013 and ISO 10993 series for biocompatibility. The "study" involves a series of bench tests to verify these properties.

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

The document does not provide a formal table with specific numerical acceptance criteria and corresponding reported values. Instead, it states compliance with standards.

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 does not specify the sample sizes used for any of the bench tests (e.g., how many specimens for flexural strength). It also does not mention data provenance in terms of country of origin or whether the data was retrospective or prospective, as this is typically irrelevant for material property bench 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. Ground truth as typically understood for AI/ML devices (e.g., expert consensus on image interpretation, pathology reports) is not relevant for the bench testing of a dental resin's physical and chemical properties.

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

Not applicable. There is no expert review or adjudication process described, as the tests are objective laboratory measurements against predefined standards.

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 device is a material for manufacturing dental products, not an AI/ML diagnostic tool. Therefore, no MRMC study, human reader improvement, or AI assistance is relevant.

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

Not applicable. As above, this is not an AI/ML device.

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

The "ground truth" for this device's performance is compliance with established international standards for dental materials (e.g., ISO 20795-2:2013 for mechanical properties and the ISO 10993 series for biocompatibility) as demonstrated through objective laboratory testing.

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.

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NextDent Denture 3D+ is a light-cured resin indicated for the fabrication of denture bases fabricated in dental laboratories, including full and partial removable dentures. The material is an alternative to traditional heat cured and auto polymerization resins. NextDent Denture 3D+ is intended exclusively for professional dental work. Fabrication of denture bases with NextDent Denture 3D+ requires a computer-aided and manufacturing (CAD/CAM) system that includes the following scanner, design software, additive printer and post-cure unit:

Light-Cure Resin, provided in a container. NextDent Denture 3D+ dimethacrylic system, polymerized via photo initiators in a 3D printer setting. The color of the denture is determined by the addition of pigments. NextDent™ Denture 3D+ must be used in combination with the NextDent™ 5100 Figure4® 3D printer. Printer and resin must be optimized to each other in order to get complete and precise printed parts. If printer and resin are not optimized to each other this may have an adverse effect on the accuracy and physical quality of printed parts. The NextDent™ 5100 Figure4® 3D printer and the post-curing lightbox NextDent™ LC-PrintBox make use of a light source to polymerize the NextDent resin.

The provided text describes the acceptance criteria and the study results for the NextDent Denture 3D+ device, which is a light-cured resin for fabricating denture bases.

Here's an breakdown of the requested information:

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

The device was tested for conformity with ISO 20795-1:2013 Dentistry – Base polymers - Part 1: Denture base polymers.
The acceptance criteria are the requirements defined in this standard for Type 4 materials.

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

The document does not specify the exact sample sizes for each test performed (e.g., number of test specimens for flexural strength, number of samples for biocompatibility).

The data provenance is not explicitly stated in terms of country of origin or whether it was retrospective or prospective. However, the submitter is Vertex-Dental B.V. from The Netherlands, suggesting the testing was likely conducted in Europe or by contractors for a European company.

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 (N/A) as the device is a material (resin) and not an AI/software device that requires expert judgment for ground truth establishment. The ground truth here refers to the compliance with established physical, chemical, and biological standards.

4. Adjudication method for the test set

This information is N/A for the same reasons as above. The evaluation of material properties against ISO standards does not typically involve human adjudication in the way an AI diagnostic tool would.

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

This information is N/A. The device is a material (resin) for 3D printing dentures, not an AI-assisted diagnostic tool.

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

This information is N/A. The device is a material, not an algorithm.

7. The type of ground truth used

The ground truth used for this device is based on established industry standards and regulatory requirements:

• Physical and Chemical Properties: ISO 20795-1:2013 Dentistry – Base polymers - Part 1: Denture base polymers.
• Biocompatibility: ISO 7405:2008/A1:2013 and ISO 10993-1:2009/C1:2010 (including parts 3, 5, 10, and 11).

8. The sample size for the training set

This information is N/A. The device is a material, not a machine learning model, so there is no "training set" in the context of AI.

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

This information is N/A. As stated above, there is no training set for this type of device.

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NextDent™ Denture / E-Denture is a light-cured resin indication of denture bases fabricated in dental laboratories, including full and partial removable dentures. The material is an alternative to traditional heat cured and auto polymerization resins. NextDent ™ Denture is intended exclusively for professional dental work. Fabrication of denture bases with NextDent ™ Denture / E-Denture requires a computer-aided and manufacturing (CAD/CAM) system that includes the following: scanner, design software, additive printer and post-cure unt.

NextDent™ Denture / E-Denture 3D-printing material is a light-cured resin indicated for the manufacturing of denture bases. The material is used in a 3D printer, which prints the shape determined by a 3D stereolithographic drawing. After printing, the printed product is placed in a UV-light curing box for final polymerization.

This document describes the premarket notification (510(k)) for the NextDent™ Denture/E-Denture, a light-cured resin for manufacturing denture bases. The focus of the provided text is on demonstrating substantial equivalence to a predicate device, primarily through bench testing and biocompatibility assessments, rather than an AI/ML-driven diagnostic or assistive device study.

Therefore, many of the requested criteria (e.g., sample size for test set, number of experts for ground truth, MRMC study, effect size of human reader improvement with AI, standalone algorithm performance, training set details) are not applicable to this type of medical device submission.

However, I can extract the relevant acceptance criteria and performance data related to the physical properties and biocompatibility of the material.

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

The acceptance criteria are generally defined by the relevant ISO standards, specifically ISO 20975-1 for "Dentistry - Base polymers - Part 1: Denture base polymers" for mechanical properties, and ISO 10993-1 for biocompatibility.

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

• Sample Size for Test Set: The exact sample sizes for each specific mechanical and biocompatibility test are not provided in this summary document. The document states that tests were "conducted on NextDent™ Denture / E-Denture using all the compatible CAD/CAM systems."
• Data Provenance: Not specified, but generally, such tests would be conducted in a controlled laboratory setting (likely within the manufacturer's R&D or QA facilities or by a certified testing lab). The summary does not indicate country of origin for actual data collection, or if it's retrospective or prospective, as these terms are usually more relevant for clinical studies than material verification testing.

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 a material (resin) used in manufacturing, not an AI-driven diagnostic device requiring expert interpretation of medical images or data. Ground truth here is established by standardized physical/chemical and biological testing methods, not expert consensus.

4. Adjudication method for the test set

• Not applicable. See point 3. Testing results are quantitative/qualitative measurements against established standards, not subject to human adjudication in the context of diagnostic interpretation.

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 device is a material, not an AI or imaging device involving human reader performance.

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

• Not applicable. This device is a material, not an algorithm.

7. The type of ground truth used

• The "ground truth" for this device's performance is established by validated laboratory testing methods and industry standards (ISO standards) for physical/mechanical properties and biocompatibility.
  • For mechanical properties: Quantitative measurements (e.g., flexural strength, water solubility) compared against specified limits in ISO 20975-1.
  • For biocompatibility: Biological assays (e.g., cytotoxicity, genotoxicity) performed according to ISO 10993 series and evaluated against pass/fail criteria.

8. The sample size for the training set

• Not applicable. This is a material, not an AI model, so there is no "training set."

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

• Not applicable. See point 8.

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