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Copra Smile consists of machinable zirconia discs and blocks for preparation of single crowns, bridges with maximum of one pontic between two crowns and inlays, onlays and veneers.

Copra Supreme Hyperion consists of machinable zirconia discs and blocks for the preparation of full ceramic crowns, onlays and 3- and 4-unit bridges and inlay bridges (anterior and molar).

Pre-sintered zirconia blanks for the fabrication of individual dental restorations.

Copra Smile disks and blocks come in both white and pre-shaded in 0M1, 0M2, 0M3, A1-D4 and Joy Five-Nine in various sizes. Copra Supreme Hyperion disks and blocks come pre-shaded in 0M1, 0M2, 0M3, A1-D4 and Joy Five-Nine in various sizes.

The provided text describes a 510(k) premarket notification for dental zirconia blanks and does not contain information about a study proving the device meets acceptance criteria as typically found for AI/ML-enabled medical devices. The device in question, Copra Smile and Copra Supreme Hyperion, are "Porcelain Powder For Clinical Use" (Class II, Product Code: EIH), which are physical materials, not software or AI/ML components.

The "Testing Summary" in the document states:
"The physical properties of Copra Smile and Copra Supreme Hyperion were tested according to ISO 6872:2015 and all parameters meet the standard. A biocompatibility assessment of Copra Smile and Copra Supreme Hyperion was done in accordance with ISO 10993-1:2018."

This indicates that the acceptance criteria are adherence to the ISO 6872:2015 standard for physical properties of dental ceramics and ISO 10993-1:2018 for biocompatibility.

Here's the information, structured as requested, based on the provided text, with clarifications where details are not present for an AI/ML context:

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

Note: The detailed acceptance values within ISO 6872:2015 for "all parameters" are not explicitly listed in the document beyond Flexural Strength and Fracture Toughness. The document states that the physical properties of the subject devices, predicate, and reference devices all meet ISO 6872:2015.

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

• Sample Size: The document does not specify the sample size for the physical properties and biocompatibility testing. This would typically be detailed in the test reports, which are summarized here.
• Data Provenance: Not explicitly stated, but the testing would typically be performed by the manufacturer or a contracted lab to generate data for submission.

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 an AI/ML device requiring expert ground truth in the traditional sense. The "ground truth" here is established by the physical and chemical properties of the material and its biological interaction determined through standardized tests, rather than expert interpretation of images or other data.

4. Adjudication method for the test set

Not applicable as this is not an AI/ML device requiring adjudication of expert interpretations. The tests for physical properties and biocompatibility are objective, standardized measurements.

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 physical dental material, not an AI-assisted diagnostic tool or software.

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

Not applicable. This is a physical dental material, not an algorithm.

7. The type of ground truth used

The "ground truth" for this device (Copra Smile and Copra Supreme Hyperion) is established by:

• Standardized Physical Property Measurements: Adherence to the specifications outlined in ISO 6872:2015 for dental ceramic materials (e.g., specific values for flexural strength, fracture toughness, chemical composition, microstructure).
• Biocompatibility Testing: Results from tests conducted according to ISO 10993-1:2018 to evaluate the biological response to the material.

8. The sample size for the training set

Not applicable. This is not an AI/ML device, so there is no training set. The "training" in manufacturing would relate to process control and material formulation development, not data-driven model training.

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

Not applicable, as there is no training set for an AI/ML model. The formulation and manufacturing parameters for the dental blanks would be established through material science research, development, and quality control processes to ensure the desired physical and chemical properties are achieved consistently.

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Glass Ceramic are indicated for fabricating all-ceramic restorations such as veneers, inlays, onlays, crowns, 2-unit anterior bridges, using the CAD/CAM system.

Glass Ceramic is indicated for fabricating all ceramic restorations such as veneers, inlay/ onlay, partial crowns, anterior crowns, posterior crowns, using the CAD/CAM system.

The Glass Ceramic is composed of SiO2, Li2O, K2O, P2O5, Al2O3 and other oxides, the performance of the Glass Ceramic conforms to ISO 6872: 2015 Dentistry: Ceramic Materials.

The Glass Ceramic is disposable device, and provided as non-sterile.

The provided text describes a 510(k) premarket notification for a dental Glass Ceramic device and outlines non-clinical tests conducted to demonstrate substantial equivalence to a predicate device. It does not contain information about a study involving human readers, AI assistance, or expert ground truth for image analysis.

Here's a breakdown of the available information regarding acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are primarily based on the ISO 6872:2015 standard for Dentistry: Ceramic Materials and relevant ISO 10993 standards for biological evaluation.

Study Proving Device Meets Acceptance Criteria:

The study conducted was a series of non-clinical tests to verify that the proposed device met all design specifications and was Substantially Equivalent (SE) to the predicate device. The results are summarized in Section 7 and further detailed in the comparison tables (Table 5-2 for Performance and Table 5-3 for Biocompatibility).

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

• Sample Size: The document does not specify the exact sample sizes (e.g., number of test specimens) used for each non-clinical test. It only states that "Non clinical tests were conducted".
• Data Provenance: The tests were conducted by the manufacturer, Shenzhen Xiangtong Co.,Ltd., in China, as implied by their address and the submission origin. The tests are non-clinical, so "retrospective or prospective" doesn't directly apply in the human data sense. It refers to laboratory testing of material properties.

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

This section is not applicable as the document describes non-clinical material testing, not a study involving human interpretation or ground truth establishment by medical experts for diagnostic purposes. The "ground truth" for these tests is defined by the objective measurement standards outlined in the ISO standards.

4. Adjudication Method for the Test Set

This section is not applicable as the document describes non-clinical material testing, not a study involving human interpretation or adjudication processes.

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

There was no MRMC comparative effectiveness study done. The device is a dental material (Glass Ceramic) used for restorations, not an AI-assisted diagnostic or imaging device.

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

This section is not applicable as the device is a physical material, not an algorithm.

7. The type of ground truth used

The "ground truth" for the non-clinical tests was established by objective measurement against the specified criteria and methodologies detailed in the referenced ISO standards (e.g., ISO 6872 for ceramic materials, ISO 10993 for biological evaluation). These standards define acceptable ranges and test methods for properties like biaxial flexure strength, chemical solubility, and biocompatibility.

8. The sample size for the training set

This section is not applicable. The document describes the testing of a manufactured material, not a machine learning model that requires a training set.

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

This section is not applicable for the same reason as above.

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Medentika TiBase CAD/CAM Abutments are intended for use with dental implants as a support for single or multiple tooth prostheses in the maxilla or mandible of a partially or fully edentulous patient.

The Medentika TiBases are titanium bases to be used as the lower part of two-piece abutments. The upper part of the two-piece abutment is a CAD/CAM designed and manufactured restoration. The TiBases are provided in several models and dimensions, according to the compatible implant systems declared in the Indications for Use statement.

The design of the CAD/CAM restorations is to be carried out through the Straumann CARES Visual Plug-In for Dental Wings CAD System. The patient-specific restorations must be milled by a Straumann milling center.

This document is a 510(k) submission for the Medentika CAD/CAM TiBases, which are dental implant abutments. It focuses on demonstrating substantial equivalence to previously cleared predicate devices, rather than a de novo approval requiring extensive clinical studies with acceptance criteria for device performance in terms of diagnostic accuracy or clinical outcomes for AI/ML devices. Therefore, much of the requested information regarding AI/ML specific studies (MRMC, standalone performance, ground truth establishment for training/test sets, expert qualifications, adjudication methods) is not applicable to this type of device submission.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

For this device (dental implant abutments), the "acceptance criteria" are related to mechanical performance and biocompatibility, demonstrating that the new devices are as safe and effective as the predicate devices. The performance data presented are primarily comparative to predicate devices rather than against specific numerical thresholds in a table.

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

This document does not describe a "test set" in the context of an AI/ML device evaluating data. For mechanical testing, specific sample sizes are not provided in this summary, but would typically be defined by the relevant ISO standards (e.g., ISO 14801). The "data provenance" would be from laboratory testing performed on the physical devices.

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

Not applicable for this type of device submission. Dental implant abutments do not use expert-established ground truth in the same way an AI diagnostic algorithm would.

4. Adjudication Method for the Test Set

Not applicable.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, this is not an AI/ML device, so an MRMC study is not relevant.

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

Not applicable, as this is a physical medical device (dental implant abutment), not an algorithm.

7. The Type of Ground Truth Used

For biocompatibility and sterilization, the "ground truth" is established by adherence to international standards (ISO 10993-1, ISO 17665-1/2) and successful completion of the tests defined within those standards. For mechanical testing, the "ground truth" is the established performance of the predicate device under specified fatigue test conditions as per ISO 14801.

8. The Sample Size for the Training Set

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

9. How the Ground Truth for the Training Set was Established

Not applicable.

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Fabrication of occlusal veneers, thin veneers, veneers, inlays, crowns in the anterior and posterior region, 3-unit bridges in the anterior region, 3-unit bridges in the premolar region up to the second premolar as the terminal unit, crown or splinted crown on top of an implant abutment and 3-unit bridge up to the second premolar placed on top of an implant abutment.

Initial LiSi Press is a press-heated ceramic ingot formed through melting the raw materials at a very high temperature. The melting process eliminates all volatile substances and the final product is a complex oxide ceramic available in various shades and translucencies. All of the components of the applicant device have already been used in the predicate devices. The restorations may be further characterized through layering, glazing and staining, and are then cemented in place as the final restoration. The device is packaged in 5 ingots per tube and is available in a range of shades, including high, medium and low translucency, as well as high and medium opacity.

The provided text is a 510(k) premarket notification from the FDA, pertaining to a dental device named "Initial LiSi Press" (a porcelain powder for clinical use). The document primarily focuses on demonstrating substantial equivalence to already marketed predicate devices, rather than presenting a study proving a device meets specific acceptance criteria related to an AI/ML algorithm's performance.

Therefore, the document does not contain the information required to answer your request about acceptance criteria and a study proving a device meets those criteria, especially in the context of an AI/ML device.

The document states:

• "No clinical testing has been performed on this device."
• The performance testing was "Non Clinical Performance Testing" (biocompatibility assessment and bench performance testing).

It discusses the device's physical and chemical properties and how it compares to predicate devices, but there is no mention of an AI/ML component, human readers, ground truth establishment, or any of the AI/ML-specific criteria you've listed.

To answer your question, information from a document describing the development and validation of an AI/ML-powered medical device would be needed.

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The device is used to fabricate ceramic dental prostheses in the nature of crowns and bridges for posterior and anterior applications using CAD/CAM or hot-press methods.

The device is comprised of dental porcelain powder in the nature of a lithium silicate glass ceramic that is used in the form of ceramic blanks. The device has excellent casting and machining properties and can be used to obtain highly esthetic dental restorations with desirable characteristics including improved density and flexural strength compared to predicate devices.

The provided text describes Obsidian™ Ceramic Blocks, a dental porcelain powder used to fabricate ceramic dental prostheses. The document outlines the device's technical specifications, indications for use, and a comparison to predicate devices to establish substantial equivalence.

Here's an analysis of the provided information concerning acceptance criteria and the study that proves the device meets them, presented in the requested format:

Acceptance Criteria and Device Performance Study for Obsidian™ Ceramic Blocks

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set (Clinical Data): 28 custom-made restorations (27 crowns and 1 inlay) for 16 patients.
• Data Provenance: Retrospective clinical observation of restorations placed from October 2, 2009, through May 4, 2010. The geographical origin of the patients/clinic is not specified, but it can be inferred to be within the US given the context of a 510(k) submission to the FDA.

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

The document does not explicitly state the number of experts or their specific qualifications for establishing the ground truth in the clinical evaluation. It mentions "All of the restorations were placed...demonstrating excellent esthetics...All 28 restorations are performing as expected based on the physical properties...with no replacements required." This suggests that the assessment of performance and esthetics was likely made by the treating dentists or possibly an internal team at Prismatik Dentalcraft, Inc., based on their clinical judgment. There is no mention of external, independent expert review to establish a formal ground truth.

4. Adjudication Method for the Test Set

No formal adjudication method (e.g., 2+1, 3+1) is described for the clinical data. The assessment appears to be a direct observation of clinical outcomes by the practitioners involved or the device manufacturer, rather than an adjudicated review.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not done. The clinical data provided is an observational study of restorations made with the subject device, without direct comparison against human readers or AI assistance.

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

This question is not applicable. The device is a physical dental material (ceramic blocks) for fabricating prostheses, not an AI or software algorithm. Therefore, there is no "standalone algorithm performance" to evaluate.

7. The Type of Ground Truth Used

The ground truth for the clinical data was based on:

• Clinical Outcomes/Performance: Direct observation of the restorations' structural integrity and functionality in the oral cavity, including the absence of failures or replacements.
• Clinical Esthetics: Subjective assessment of the esthetic appearance of the restorations, described as "excellent esthetics."
• Correlation with Physical Properties: The clinical performance was deemed to be "as expected based on the physical properties of the subject device as determined in the nonclinical testing."

8. The Sample Size for the Training Set

This question is not applicable. The device is a physical material, not an AI or machine learning model that requires a "training set." The development of the ceramic material would involve material science research and engineering, not data training in the computational sense.

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

This question is not applicable for the same reason as point 8. The "ground truth" for the material's development would be established through material science principles, laboratory testing (e.g., flexural strength, density measurements), and chemical analysis, rather than a "training set" with established ground truth labels as typically seen in AI development.

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