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Dental Glass Ceramics Blocks are indicated for fabricating all-ceramic restorations such as veneers, inlay/ onlay, partial crowns, anterior crowns, using the hot press technique or CAD/CAM system.

Dental Glass Ceramics Blocks are derived from dental porcelain powder that has been processed into their final net shapes. These blanks are then being further fabricated (using hot press or CAD/CAM technologies) into all-ceramic restorations such as veneers, inlay/ onlay, partial crowns, anterior crowns, posterior crowns. The ceramics material is composed of SiO2, Li2O, K2O, Al2O3 and other oxides. It also contains inorganic pigments to provide different shades on the product surface.

The provided text is a 510(k) Premarket Notification from the FDA regarding "Dental Glass Ceramics Blocks". This document focuses on demonstrating substantial equivalence to an already legally marketed predicate device, rather than proving that a device meets specific acceptance criteria through a study involving a diagnostic algorithm or AI.

The information requested in your prompt (acceptance criteria for device performance, ground truth establishment, sample sizes for AI training/testing, MRMC studies, etc.) is typically found in submissions for devices that employ diagnostic algorithms, machine learning, or AI, particularly those where the device's output is an interpretative result that a human uses for diagnosis or patient management.

The "Dental Glass Ceramics Blocks" are a material used for dental restorations. The "study" referenced in the document is primarily non-clinical bench testing to ensure the physical and chemical properties of the material meet established standards (like ISO 6872:2015) and biocompatibility.

Therefore, I cannot provide all the requested information as it is not present in this document. I will fill in what can be extracted and explain why other parts are not applicable.

Device Name: Dental Glass Ceramics Blocks (HT, LT, MT)
Regulation Number: 21 CFR 872.6660
Regulation Name: Porcelain Powder For Clinical Use
Regulatory Class: Class II
Product Code: EIH

Acceptance Criteria and Device Performance (Material)

Explanation for Not Applicable (N/A) or Not Provided fields:

1. Sample size used for the test set and the data provenance:

   • N/A. This device is a material, not a diagnostic algorithm. The "test set" for performance evaluation refers to samples of the material used in bench tests (e.g., test pieces for flexural strength, chemical samples for biocompatibility). The document does not specify the number of material samples tested, but it states "Bench testing was performed per ISO 6872:2015 and internal procedures."
   • Data provenance (country of origin, retrospective/prospective) is relevant for patient data used in AI/diagnostic device studies, not for material testing.

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

   • N/A. Ground truth, in the context of diagnostic algorithms, refers to a definitive disease status or interpretation established by medical experts or pathology. For material performance, the "ground truth" is defined by the technical specifications in standards like ISO 6872:2015 and biocompatibility guidelines, and measured by laboratory instruments and protocols. There are no "experts" establishing "ground truth" in the diagnostic sense for this type of device.

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

   • N/A. Adjudication methods are used in diagnostic studies to resolve discordant interpretations among readers/experts. This is not applicable to
     material testing where measurements are objective and performed according to standardized protocols.

4. 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:

   • N/A. This device is a dental material, not an AI or imaging device with human-in-the-loop interaction for diagnosis. Therefore, MRMC studies are not relevant.

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

   • N/A. This is a material, not an algorithm.

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

   • Technical Specifications/Standards and Bench Testing Results. For this device, the "ground truth" for its performance is defined by the established technical requirements and test methods outlined in ISO 6872:2015 (for physical/chemical properties) and ISO 10993 series (for biocompatibility). The device performance is then measured against these standards through laboratory bench tests.

7. The sample size for the training set:

   • N/A. There is no "training set" as this is not a machine learning or AI device.

8. How the ground truth for the training set was established:

   • N/A. Not an AI/ML device.

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Dental Glass Ceramics Blocks are indicated for fabricating all-ceramic restorations such as veneers, inlay/ onlay, partial crowns, anterior crowns, posterior crowns, using the hot press technique or CAD/ CAM system.

Dental Glass Ceramics Blocks are derived from dental porcelain powder that has been processed into their final net shapes. These blanks are then being further fabricated (using hot press or CAD/CAM technologies) into all-ceramic restorations such as veneers, inlay/ onlay, partial crowns, anterior crowns, posterior crowns. The ceramics material is composed of SiO2, Li2O, K2O3 and other oxides. It also contains inorganic pigments to provide different shades on the product surface. It has three model: HT,LT,ST, and totally 23 colors(A1,A2,A3,A3.5,A4,B1,B2,B3,B4,C1,C2, C3,C4,D2,D3,D4,BL1,BL2,BL3,BL4, OM1, OM2 and OM3).

This FDA 510(k) summary is for a dental device (Dental Glass Ceramics Blocks) and focuses on demonstrating substantial equivalence to a predicate device, rather than providing a detailed study report with acceptance criteria and performance metrics for a novel AI/software device. Therefore, much of the requested information regarding AI/software performance studies (like sample sizes for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, and training set details) is not applicable to this document.

However, I can extract the relevant information regarding acceptance criteria and device performance based on the provided text for this specific type of medical device.

Device Name: Dental Glass Ceramics Blocks (HT,LT,ST)

Acceptance Criteria and Reported Device Performance:

Study to Prove Device Meets Acceptance Criteria:

A non-clinical test and biocompatibility testing were conducted.

• Physical and mechanical properties of the subject device were evaluated according to ISO 6872:2015/AMD 1:2018. This standard classifies the device into:
  • Type II: All other forms of ceramic products.
  • Class 4: Monolithic ceramic for prostheses involving partially or fully covered substructure.
  • The document states that the new model "ST" and the existing models (HT, LT, which correspond to the predicate device's models) were tested and found to have physical/mechanical properties that met the requirements of ISO 6872.
• Biocompatibility testing was performed to verify the equivalent safety of the materials used. The results comply with ISO 10993-1:2018 and FDA Guidance.

Information Not Applicable to this Submission (as it is not an AI/software device):

• Sample size used for the test set and data provenance: Not applicable. This is a physical material device, not a software/AI system. The testing involved material properties, not a "test set" of data in the AI sense.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for material properties is established by standardized physical and chemical testing, not expert consensus on medical images or patient data.
• Adjudication method for the test set: Not applicable.
• If a multi-reader multi-case (MRMC) comparative effectiveness study was done: Not applicable. This is not an AI-assisted diagnostic or predictive device.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
• The type of ground truth used: For material properties, the "ground truth" is defined by the objective measurements obtained through standardized physical, mechanical, and chemical tests to meet the specified ISO standard. For biocompatibility, it's defined by compliance with ISO 10993-1 and FDA guidance through specific biological evaluation tests.
• The sample size for the training set: Not applicable (no AI/machine learning involved).
• How the ground truth for the training set was established: Not applicable.

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Dental Glass Ceramics are indicated for fabrications such as veneers, inlay/ onlay/ onlay/ partial crowns, anterior crowns, posterior crowns, using the hot press technique or CAD/CAM system.

This product is composed of SiO2 , Al2O3 , Li2O , K2O , Na2O , CeO2 , Pr6O11 , ZrO2 , P2O5 , СаО , МпО2 , Ег2Оз .

The provided document is a 510(k) Premarket Notification for a medical device called "Dental Glass Ceramics". This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving novel effectiveness or developing an AI algorithm. Therefore, many of the requested categories for AI-based device studies are not applicable to this document.

Here's an analysis based on the information available:

1. Table of acceptance criteria and the reported device performance

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Once finalized into a suitable design, the Dental Glass Ceramics are indicated for use as inlays, onlays, veneer, partial crowns and crowns.

Dental Glass Ceramics is composed of SiO2, Li2O, K2O,P2O5,Al2O3 and other oxides. The block is intended to be processed into the dental restorations such as crowns, bridges, veneers, inlays and onlays based on the anatomical rendering of the patient's teeth using CAD/CAM (computer aided design / computer aided manufacturing) method or manual milling method. The block is a single-use device and provided non-sterile.

The performance of the dental blanks conforms to ISO 6872, Dentistry - Ceramic materials.

The provided document is a 510(k) Premarket Notification from the FDA for a dental material (Dental Glass Ceramics), not an AI/ML medical device. Therefore, it does not contain the information requested in your prompt regarding acceptance criteria and study details for an AI-powered device.

Specifically, the document focuses on demonstrating substantial equivalence of the Dental Glass Ceramics to a predicate device based on material properties, intended use, and biocompatibility, as per ISO 6872 and ISO 10993 standards. It includes:

• A comparison table (Table 1) showing the proposed device and predicate device are "Same" across numerous characteristics like product code, classification regulation, indications for use, materials, crystallization state, device design, shades, single use, principle of operation, sterility, type/class per ISO 6872, mechanical properties (flexural strength, chemical solubility, radioactivity, linear thermal expansion, glass transition temperature) and biocompatibility.
• Biocompatibility testing results (Table 2) demonstrating that the material passed cytotoxicity, oral mucosa irritation, skin sensitization, subacute systemic toxicity, acute systemic toxicity, in vitro mammalian cell gene mutation, bacterial reverse mutation, and muscle implant tests. These tests are standard for evaluating the safety of implantable or device-contacting materials.
• A statement that no clinical study was included in the submission.

Therefore, it is impossible to extract the requested information about acceptance criteria for an AI device, sample sizes for test sets, expert ground truth establishment, MRMC studies, standalone performance, or training set details from this document. The nature of the device (dental material) and its regulatory pathway (510(k) for substantial equivalence to a material predicate) do not necessitate or include such information.

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Dental Glass Ceramics Blocks are indicating all-ceramic restorations such as veneers, inlay/ onlay, partial crowns, anterior crowns, posterior crowns, using the hot press technique or CAD/CAM system.

Dental Glass Ceramics Blocks are derived from dental porcelain powder that has been processed into their final net shapes. These blanks are then being further fabricated (using hot press or CAD/CAM technologies) into all-ceramic restorations such as veneers, inlay/ onlay, partial crowns, anterior crowns, posterior crowns. The ceramics material is composed of SiO2, Li2O, K2O, Al2O3 and other oxides. It also contains inorganic pigments to provide different shades on the product surface.

The provided document (K232438, a 510(k) premarket notification) describes the acceptance criteria and the study proving that "Dental Glass Ceramics Blocks" meet these criteria. However, it's crucial to understand that this document is about a material, not a medical imaging or AI-driven diagnostic device. Therefore, the questions related to AI assistance, human-in-the-loop performance, expert readers, and ground truth establishment in the context of diagnostic algorithms are not applicable to this submission.

The "device" in this context is a material used to fabricate dental restorations, and the acceptance criteria relate to its physical, chemical, and biocompatibility properties, primarily benchmarked against the ISO 6872 standard and a predicate device.

Here's the information extracted from the document based on the provided questions, with clarifications where the questions are not applicable:

1. Table of acceptance criteria and the reported device performance

The document states that the performance of the dental blanks conforms to ISO 6872, Dentistry - Ceramic materials, and that "All tests were verified to meet acceptance criteria." It then lists various properties and their compliance with ISO 6872:2015 requirements. The specific numerical values for the reported performance are not provided in this summary, but rather a statement of compliance with the standard is given.

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

The document does not specify a distinct "test set" sample size in terms of numbers of units tested. It states that "Bench testing was performed per ISO 6872:2015 and internal procedures." ISO standards typically define the minimum number of samples required for specific tests (e.g., number of specimens for flexural strength). The provenance of the data is not explicitly stated in terms of country of origin, but the manufacturer is based in China. The testing described is non-clinical bench testing, not retrospective or prospective data collection from human subjects.

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

This question is not applicable as this is not a diagnostic device or an AI algorithm requiring expert consensus for ground truth. The "ground truth" for this device is established through physical, chemical, and biological laboratory testing against international standards (ISO 6872 and ISO 10993 series).

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

This question is not applicable. Adjudication methods like 2+1 or 3+1 are typically used for establishing ground truth in medical imaging studies involving multiple human readers, which is not relevant to the testing of dental ceramic blocks.

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 question is not applicable. This is not an AI-assisted diagnostic device.

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

This question is not applicable. This is not an algorithm.

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

The "ground truth" for this device is established by compliance with international standards for dental ceramics (ISO 6872:2015) and biocompatibility (ISO 10993 series, specifically ISO 10993-1:2018 for evaluation and subsequent specific parts for various tests like cytotoxicity, irritation, sensitization, toxicity, and genotoxicity). This is based on bench testing and laboratory analyses of the material's properties.

8. The sample size for the training set

This question is not applicable. As this is not an AI/ML device, there is no "training set."

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

This question is not applicable. There is no training set for this type of device.

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Dental Glass Ceramics Blocks are indicating all-ceramic restorations such as veneers, inlay/ onlay, partial crowns, anterior crowns, posterior crowns, using the hot press technique or CAD/CAM system.

Dental Glass Ceramics Blocks are derived from dental porcelain powder that has been processed into their final net shapes. These blanks are then being further fabricated (using hot press or CAD/CAM technologies) into all-ceramic restorations such as veneers, inlay/ onlay, partial crowns, anterior crowns, posterior crowns. The ceramics material is composed of SiO2, Li2O, Al2Os and other oxides. It also contains inorganic pigments to provide different shades on the product surface.

This document describes a 510(k) premarket notification for a dental device, specifically "Dental Glass Ceramics Blocks." It is not for a software-as-a-medical-device (SaMD) or an AI/ML-driven device. Thus, the questions about acceptance criteria for AI/ML performance, sample sizes for test/training sets, expert adjudication, MRMC studies, standalone performance, and ground truth establishment are not applicable to this document.

The document focuses on demonstrating substantial equivalence to a predicate device (Dental Lithium Disilicate Glass Ceramic Block, K141727) through non-clinical bench testing and biocompatibility testing. The "acceptance criteria" in this context refer to the physical, chemical, and biocompatibility properties of the dental material, not the performance of an AI model.

Here's how to interpret the provided information in the context of the requested questions, noting the inapplicability of many of them:

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

The document doesn't provide a direct "table of acceptance criteria and reported device performance" in the way one would expect for an AI/ML device (e.g., accuracy, sensitivity, specificity thresholds). Instead, it lists various characteristics and states whether the proposed device is "Same" or "Comparable" to the predicate, and whether it "Meet the requirements of ISO 6872:2015" for certain properties.

Here's a partial interpretation based on the "Substantial Equivalence Comparison" table and "Non-clinical Testing" section:

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

• Sample Size: Not specified for the bench testing. The testing would involve a specific number of material samples, but the document does not quantify this.
• Data Provenance: Not applicable in terms of "country of origin of the data" or "retrospective/prospective" studies as this is bench testing of physical materials, not clinical data collection. The manufacturer is Aidite (Qinhuangdao) Technology Co., Ltd. in China.

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

• Not Applicable. Ground truth, in the context of material properties like density or tensile strength, is established by laboratory measurement and adherence to international standards (e.g., ISO 6872:2015), not by expert consensus in the way medical image interpretation would be.

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

• Not Applicable. Adjudication is a concept for human interpretation consistency or resolution of discrepancies, not for physical material property measurement.

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-driven device.

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

• Not Applicable. This is not an AI-driven device.

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

• Physical/Chemical Properties based on International Standards: The "ground truth" for this device's performance is objective measurement of its physical and chemical properties (e.g., density, flexural strength, biocompatibility) as defined by and tested according to international standards (e.g., ISO 6872:2015, ISO 10993 series).

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. This is not an AI/ML device that requires a "training set."

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