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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.

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.

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BioHPP polymer is used for the fabrication of definitive crown and bridge frameworks with no more than 2 pontics and for definitive removable restorations. BioHPP can also be used for fully anatomical pressed bridge structures - with or without buccal composite veneering.

• · Fully anatomical crowns and bridges (max. 2 pontics)
• · Crown copings and bridge substructures for composite veneers (max. 2 pontics)
• · Telescopic primary and secondary crowns and frameworks
  • Secondary bar structures on primary bars made of titanium alloy, CoCr alloys, gold alloy, zirconium dioxide

breCAM.BioHPP is used for the fabrication of permanent restorations using CAD/CAM techniques.
Fully anatomical crowns and bridges (max. 2 pontics and min. 13 mm² connector crosssection)
Crown copings and bridge substructures for composite veneering (max. 2 pontics and min. 13 mm² connector cross-section))
Telescopic primary and secondary crowns and frameworks Secondary bar structures on primary bars made of titanium alloy, CoCr alloys, gold alloy, zirconium dioxide. Reference is made to the instructions for use "BioHPP elegance prefab for SKY" to fabricate an individual abutment.

BioHPP is a tooth-colored thermoplastic high-performance polymer based on polyether ether ketone (PEEK), which was developed especially for the fabrication of dental restorations. Bio HPP is available in two different variations - as a granular material and prefabricated cylinders with diameters of 15 mm and 25 mm (so-called pellets).
breCAM.BioHPP is based on filled polyether ether ketone (PEEK) and used for the fabrication of permanent crowns and bridges using CAD/CAM techniques. Three sizes are available.

This document is a 510(k) Pre-Market Notification from the FDA regarding the dental material BioHPP and breCAM.BioHPP. It is a regulatory approval document and not a scientific study report. Therefore, it does not contain the information requested about acceptance criteria and a study proving device performance as it pertains to AI/ML devices.

The questions refer to the validation of an AI/ML device, which involves concepts like:

• Acceptance Criteria for AI/ML performance (e.g., sensitivity, specificity, AUC): Not applicable to a dental material's physical properties.
• Sample Size for Test Set and Data Provenance: Not applicable. The document refers to physical property testing, not data sets for AI.
• Number of Experts and Qualifications for Ground Truth: Not applicable. Ground truth for an AI model's output (e.g., image annotation) is not relevant for evaluating the mechanical properties of a dental material.
• Adjudication Method: Not applicable.
• Multi-Reader Multi-Case (MRMC) Study: Not applicable. This is for evaluating human performance with and without AI assistance.
• Standalone Performance: Not applicable.
• Type of Ground Truth (Expert Consensus, Pathology, Outcomes Data): Not applicable. The "ground truth" here would be the actual physical properties measured in a lab, not expert interpretations of data.
• Sample Size for Training Set, and How Ground Truth for Training Set was Established: These are concepts for machine learning models and are not present or relevant in this document about a dental material.

Therefore, I cannot provide the requested information based on the provided text because the document describes the regulatory approval of a dental material based on its physical and mechanical properties, not the validation of an AI/ML device.

The tables in the document compare the physical characteristics (e.g., water absorption, flexural strength, density) of the new device (BioHPP and breCAM.BioHPP) against predicate devices. These are material properties, not performance metrics of an AI algorithm.

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The bredent novo.lign A / novo.lign P are preformed plastic denture teeth as a prefabricated device, composed of materials such as polymethylmethacrylat and methylmethacrylat that are intended for use as veneers. The bredent novo:lign P are used for temporary or partial or full dentures.

Permanent veneering:

• telescopic and conical crowns
• CoCr clasp restorations
• crowns and bridges
• implant-supported restorations
• coverdenture techniques

Veneer-up:

• selection of esthetic shade, shape and tooth position

Temporary restorations:

• laboratory-made temporaries based on impression and wax-up
• veneer on temporary abutments after placement of the implant
  The devices are offered in non-sterile condition.

Bredent novo.lign A / novo.lign P artificial are multi-layer veneers for anterior and posterior teeth. Theses teeth devices are chemically based on polymethacrylate-polymers and their chemical properties. These reformed plastic dentures are used when fabricating any kind of dental restauration (see application range beneath).

The provided text describes a 510(k) premarket notification for "bredent novo.lign A / novo.lign P" artificial teeth, which are preformed plastic denture teeth. The submission aims to demonstrate substantial equivalence to a predicate device.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based only on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state numerical acceptance criteria or specific performance metrics as typically seen for AI device evaluations (e.g., sensitivity, specificity, AUC). Instead, it focuses on demonstrating equivalence to a predicate device through compliance with recognized standards and a summary statement of similar performance.

2. Sample Size Used for the Test Set and Data Provenance:

The document does not describe a traditional "test set" or a study involving patient data in the context of AI/diagnostic device evaluation. The evaluation appears to be based on adherence to standards for material properties and biocompatibility.

• Sample Size: Not applicable in the context of an AI-like test set. The material testing would involve specific quantities of the artificial teeth but these are not disclosed as "sample sizes" for a clinical study.
• Data Provenance: Not applicable for a traditional test set. The compliance tests would have been performed in a laboratory setting. No country of origin for specific "data" or whether it's retrospective/prospective is mentioned for a clinical evaluation.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:

This information is not applicable. The device is a physical product (artificial teeth) and the evaluation is based on engineering and material standards, not diagnostic interpretation by experts. There is no concept of "ground truth" established by experts in the way an AI diagnostic algorithm would require.

4. Adjudication Method for the Test Set:

Not applicable. There is no "test set" requiring expert adjudication for this type of device.

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 not an AI diagnostic device. No human-in-the-loop study, MRMC study, or AI assistance is mentioned.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

Not applicable. This is not an algorithm or software device.

7. The Type of Ground Truth Used:

Not applicable in the context of AI evaluation. The "ground truth" for this product would be the established scientific and engineering specifications and performance requirements defined in the referenced ISO and ADA/ANSI standards for implantable/dental materials.

8. The Sample Size for the Training Set:

Not applicable. This is not an AI/machine learning device; therefore, there is no "training set."

9. How the Ground Truth for the Training Set Was Established:

Not applicable. There is no training set for this device.

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