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The indications for use for DC-Cristall is as a substructure for single unit porcelain fused ceramic fixed dental restorations; namely crowns. Substructures of DC-Cristall are machined using the DCS Precident CAD/CAM System.

The DC-Cristall material is a glass ceramic material, furnished in a block form, designed for use as feed stock in the DCS Precident CAD/CAM System.

This describes the acceptance criteria and the study that proves the device meets the acceptance criteria for the DC-Cristall material.

1. Table of Acceptance Criteria and Reported Device Performance

Note: The provided document states that "The safety and efficacy of DC-Cristall is assured by compliance with ISO 6872:1999 Dental Ceramics." However, it does not provide specific numerical values or detailed test results for each criterion. It only asserts overall compliance.

2. Sample Size and Data Provenance for the Test Set

The document does not explicitly specify a "test set" in the context of an AI/ML device. Instead, it refers to standard testing of the material itself.

• Sample Size: Not explicitly stated for specific tests, but testing would have been conducted on an appropriate number of DC-Cristall material samples to satisfy the requirements of ISO 6872:1999.
• Data Provenance: Not specified, but standard material testing would typically be performed in a laboratory setting, likely in the country of origin of the manufacturer (USA, based on the address). This would be analogous to a prospective study of material properties.

3. Number of Experts and Qualifications for Ground Truth - Test Set

Not applicable in the context of an AI/ML device. This refers to material scientists and engineers who would conduct the tests and assess compliance with ISO 6872:1999. Their qualifications would be expertise in dental materials testing and adherence to international standards.

4. Adjudication Method for the Test Set

Not applicable in the context of an AI/ML device. Compliance with ISO 6872:1999 would be determined by whether the test results meet the specified thresholds and requirements of the standard, not by expert adjudication of interpretations.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

Not applicable. The DC-Cristall is a material for dental restorations, not an AI/ML diagnostic or assistive device that would involve human readers.

6. Standalone (Algorithm Only) Performance Study

Not applicable. This is a material, not an algorithm. The "performance" is its compliance with material standards.

7. Type of Ground Truth Used

The ground truth used is the standards set forth in ISO 6872:1999 Dental Ceramics. This standard defines the acceptable physical, mechanical, chemical, and biological properties for dental ceramic materials. Compliance with all specified tests and thresholds within this standard constitutes the "ground truth" for the material's safety and efficacy.

8. Sample Size for the Training Set

Not applicable. This is a material, not an AI/ML model that requires a training set. The development of the material would involve R&D and formulation iterations, but not "training data" in the AI sense.

9. How Ground Truth for the Training Set Was Established

Not applicable. As noted above, this is a material, not an AI/ML model. The "ground truth" for material development would be established through established scientific principles, material science research, and iterative testing against desired performance specifications, which would eventually lead to the formulation meeting ISO standards.

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Myerson Economy Denture Base Material is intended for use in the fabrication of full and partial dentures.

The Myerson Economy Denture Base Material is a conventional dough pack heat cure denture base material that consists of a polymethyl methacrylate polymer powder with a heat cure monomer consisting of methyl methacrylate, crosslinker (either EGDMA or TEGDMA), 0-1% UV Light Absorber.

The polymer is shaded to simulate the color of gum tissue using pigments that appear on the FDA list of approved products.

Here's an analysis of the provided text in the context of your request for device acceptance criteria and study details.

Based only on the provided text, it's immediately apparent that this document describes a traditional medical device (denture base material) submission from 1997, not an AI/ML-driven device. Therefore, many of the typical questions for AI/ML device evaluations (like ground truth establishment, MRMC studies, training sets, etc.) are not applicable to this specific submission.

The "acceptance criteria" here are more about compliance with existing standards and substantial equivalence to predicate devices, rather than performance metrics from a clinical study for a diagnostic AI.

Analysis of Provided Text for K970522: Myerson Economy Denture Base Material

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

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Not Applicable. The provided text does not describe a clinical study with a "test set" in the context of an AI/ML device. The submission relies on substantial equivalence and compliance with material standards, not performance against a specific test dataset.

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 establishment, as typically understood for AI/ML devices, is not a concept relevant to this type of traditional material device submission.

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

• Not Applicable. No test set or human adjudication process is described.

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 device, not an AI-assisted diagnostic tool.

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

• Not Applicable. This is not an algorithm; it's a physical material.

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

• Not Applicable. The "truth" here is compliance with material specifications and established dental standards, and the physical properties of the material itself, not clinical outcomes directly measured with a "ground truth" dataset for performance evaluation.

8. The sample size for the training set

• Not Applicable. There is no "training set" for this type of device.

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

• Not Applicable. There is no "training set" or corresponding ground truth.

Summary for K970522:

This 510(k) notification for Myerson Economy Denture Base Material is a pre-AI era submission. The "study" proving it meets acceptance criteria is primarily based on:

• Formulation Compliance: The material's composition (polymethyl methacrylate, methyl methacrylate, crosslinker, UV absorber, FDA-approved pigments) explicitly meets the described specifications.
• Substantial Equivalence: The device is compared to existing, legally marketed predicate denture base systems. This implies that the new device shares similar technological characteristics and is as safe and effective as the predicates.
• Adherence to Standards: The product is formulated to comply with applicable American Dental Association (ADA) Standards for denture base materials and repair denture base materials. These standards themselves are the "acceptance criteria" and meeting them is the "demonstration."
• Documentation: The safety and effectiveness of similar systems (predicates) are "well documented in the dental literature," which supports the substantial equivalence claim.

There are no direct performance metrics, clinical studies, or AI-related evaluations described in this summary. The "proof" is foundational to material science and regulatory compliance of the time.

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The above name products are intended for use as base metal casting alloys for casting removable partial denture frameworks.

The family of Base Metal Casting Alloys are cobalt chrome casting alloys substantially equivalent to the alloys currently used to produce partial denture frameworks.

The provided text describes material properties of dental alloys, not a medical device in the context of typical FDA 510(k) AI/ML device submissions (which usually involve diagnostic or therapeutic software/hardware). Therefore, many of the requested categories in your prompt are not applicable to this document.

However, I can extract the relevant information regarding acceptance criteria and the study that proves the device meets them based on the provided text.

Here's the information parsed according to your request, with "N/A" for categories that do not apply to this type of submission:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not explicitly stated, however, the data presented in the tables implies that samples of each alloy (Vitallium 2000 Alloy, Vitallium 2000 Plus Alloy, Cobalt Chrome Casting Alloy) were tested. The specific number of specimens or batches tested for each property is not provided.
• Data Provenance: The data appears to be from laboratory testing performed by the submitter (Austenal, Inc.). The country of origin of the data is implied to be the United States, given the Chicago address of the submitter. The data is prospective in the sense that it's a test of the specific new products against established standards, but it's not a clinical trial.

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

• Number of Experts: N/A. Ground truth for material properties is established by adherence to international and national standards (ISO 6871, ANSI/ADA #14) and laboratory testing protocols, not by expert consensus in the diagnostic sense.
• Qualifications of Experts: N/A.

4. Adjudication method for the test set

• Adjudication method: N/A. Material property testing adherence to a standard does not typically involve an adjudication method in the way a diagnostic study would. Results are quantitative measurements against defined thresholds.

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

• MRMC Study: No. This is not applicable to material property testing.

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

• Standalone Performance: N/A. This is not an algorithm or AI device. The "performance" is the inherent physical and chemical properties of the alloys.

7. The type of ground truth used

• Ground Truth Type: International and National Product Standards/Specifications.
  • ISO Product Standard: ISO 6871, Base Metal Casting Alloys- Part I Cobalt Based Alloys
  • ANSI/ADA Standard Specification ANSI/ADA # 14 Base Metal Casting Alloys

8. The sample size for the training set

• Training Set Sample Size: N/A. This material does not involve a "training set" in the context of machine learning or AI.

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

• Ground Truth for Training Set: N/A.

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