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All types of impressions, e.g .:
· Crown, bridge, inlay, and onlay preparations
· Implants
· Orthodontic impressions

Flash Penta™ MB Quick and Flash MB Quick are addition type silicone impression materials of medium consistency. Flash Penta MB Quick is mixed in the Pentamix mixing device, while Flash MB Quick can be applied directly using the Garant™ dispenser. Both products are used in mono-phase technique and in one-step technique.

The provided text describes a 510(k) submission for dental impression materials (Flash Penta™ MB Quick and Flash MB Quick). It primarily focuses on demonstrating substantial equivalence to predicate devices through bench testing of physical properties. However, it does not contain the detailed information requested regarding acceptance criteria, study design for proving device acceptance, or any elements related to AI/algorithm performance.

Therefore, I cannot provide a table of acceptance criteria, reported device performance, or details about sample sizes, ground truth, experts, or MRMC studies as these are not mentioned in the provided document.

To be specific about what is mentioned:

• Device: Flash Penta™ MB Quick and Flash MB Quick (VPS impression material).
• Study Type: Bench testing.
• Properties Evaluated: Consistency, total working time, detail reproduction, linear dimensional change, compatibility with gypsum type 3 / type 4, recovery from deformation and strain in compression.
• Purpose: To demonstrate substantial equivalence to predicate devices (Flash Penta™ HB Q, Flash Heavy Body Q, Flash Regular Body Q, Flash Light Body) in terms of intended use, indications for use, composition, and physical properties.

The document states that a "biocompatibility assessment was developed... using standard risk assessment techniques and consideration of FDA & internationally recognized guidelines" and concluded that the products are safe for their intended use. However, no specific details of this assessment's methods or results are provided.

In summary, the provided document does not contain the information necessary to fulfill your request for details on acceptance criteria, a study proving device acceptance, or any AI/algorithm-related performance metrics.

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Bite registration.

Flash Bite is classified as impression materials (21 C.F.R. § 872.3660) because it is a devices intended to reproduce the structure of a patient's teeth. Flash Bite is a two component (base paste/catalyst) vinyl polysiloxane bite registration material designed to be used in 3M Deutschland GmbH's mixing, dosing and dispensing device, Garant of 3M Deutschland GmbH. The mixing ratio for both materials is base paste:catalyst, 1:1 (by volume).

The provided text describes a 510(k) premarket notification for a dental impression material named "Flash Bite." This submission focuses on demonstrating substantial equivalence to predicate devices, primarily through comparison of indications for use, physical and mechanical properties, and chemical composition, rather than presenting a study with acceptance criteria and device performance in the typical sense of a diagnostic medical device.

Therefore, many of the requested elements for a study establishing acceptance criteria do not apply directly to this type of submission. However, I will extract what can be inferred or directly stated from the document regarding equivalence testing.

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

The document doesn't explicitly state "acceptance criteria" for quantitative performance metrics in a table. Instead, it relies on demonstrating substantial equivalence to predicate devices in terms of properties. The performance is assessed against the existing, legally marketed predicate devices.

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 sample sizes for any tests. The data provenance is not mentioned beyond the submitting company being located in Germany. The nature of the comparisons (e.g., laboratory tests) suggests prospective data collection for the new device, but this is not explicitly stated.

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)

This is not applicable. For material equivalence, ground truth is established through standardized material testing methods and comparison to known properties of predicate materials, not through expert reader consensus on clinical images or data.

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

This is not applicable as the submission is for material equivalence based on physical, mechanical, and chemical properties, and biocompatibility, not clinical diagnostic performance requiring adjudication of results.

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 is not applicable. The device is a dental impression material, not an AI-powered diagnostic tool. Therefore, no MRMC study was conducted.

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

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

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

The "ground truth" in this context is the established performance characteristics and safety profile of the predicate devices, along with adherence to recognized biocompatibility standards. For the physical, mechanical, and chemical properties, the ground truth would be the values obtained from standardized material testing. For biocompatibility, it's compliance with FDA and international guidelines.

8. The sample size for the training set

This is not applicable as the device is a dental material, not a machine learning model, and therefore does not have a "training set."

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

This is not applicable for the same reason as point 8.

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Heisenberg Effect Shades are suited for more intensive coloring of Heisenberg zirconia frameworks and Heisenberg all-zirconia restorations after basic dyeing using Heisenberg Dyeing Liquids.

Heisenberg Effect Shade is classified as Porcelain powder for clinical use (21 C.F.R. § 872.6660). Heisenberg Effect Shades are suited for more intensive coloring of Heisenberg zirconia frameworks and Heisenberg all-zirconia, monolithic restorations for anterior and posterior teeth restorations after basic dyeing using Heisenberg Dyeing Liquids. Heisenberg Effect Shades will be available in various colors.

The provided text is a 510(k) summary for "Heisenberg Effect Shades", a device classified as "Porcelain powder for clinical use". This document focuses on demonstrating substantial equivalence to predicate devices rather than providing a detailed study proving performance against specific acceptance criteria for a novel device. Therefore, much of the requested information regarding specific acceptance criteria studies for a new device's performance is not available in the provided text.

The overarching acceptance criterion for this 510(k) submission is to demonstrate substantial equivalence to existing legally marketed predicate devices in terms of indications for use, fundamental scientific technology, and performance. The "study" presented here is a comparison report.

Here's a breakdown of the requested information based on the provided text, and where the information is not applicable or not present given the nature of a 510(k) for a substantially equivalent device:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document refers to "bench testing" for physical and mechanical properties and "biocompatibility testing." However, specific sample sizes (e.g., number of restorations tested, number of individual tests) for these comparisons are not provided in this 510(k) summary. Given that the manufacturer is 3M ESPE AG in Germany, it is highly probable the data provenance is from Germany, and it would be retrospective for the purpose of comparison to previously existing predicate devices.

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

This type of information is not applicable and therefore not provided for a device like "Porcelain powder for clinical use" in a 510(k) submission focused on substantial equivalence. There is no concept of "ground truth" established by experts in the context of comparing the physical, chemical, and biocompatibility properties of a dental coloring agent. The "ground truth" in this context is the established performance and safety profile of the predicate devices.

4. Adjudication method for the test set

This is not applicable and therefore not provided. Adjudication methods (like 2+1, 3+1) are typically used in clinical studies involving interpretation of medical images or patient outcomes, where there might be disagreement in expert opinions. This device's comparison is based on objective physical, chemical, and biocompatibility tests, not subjective expert judgment.

5. If a multi-reader, multi-case (MRMC) comparative effectiveness study was done

No, a MRMC comparative effectiveness study was not done. This type of study is relevant for diagnostic devices where human readers interpret results, often with and without AI assistance, to assess the impact of the AI on reader performance. "Heisenberg Effect Shades" is a material for coloring dental restorations, not a diagnostic tool.

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

No, a standalone "algorithm only" performance study was not done. This concept is specific to AI/software as a medical device (SaMD) where algorithms perform a task without immediate human intervention. This device is a material, not software.

7. The type of ground truth used

For the comparison study:

• The "ground truth" for showing substantial equivalence relies on the established performance, indications for use, chemical composition, and biocompatibility profile of the predicate devices (Lava™ Frame Shades by 3M ESPE and Zenostar Color Zr by Wieland Dental + Technik).
• For the device itself, the ground truth for performance characteristics would be direct measurements from bench testing for physical/mechanical properties and results from biocompatibility testing against established standards.

8. The sample size for the training set

This is not applicable and not provided. The device is a material, not an AI or machine learning model that requires a training set.

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

This is not applicable and not provided, as there is no training set for this type of device.

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• Final cementing of all-ceramic, composite, or metal inlays, onlays, crowns and bridges; 2-3-unit Maryland bridges and 3-unit inlay/onlay bridges (excluded for patients with bruxism or periodontitis)
• Final cementing of posts and screws .
• Final cementation of all-ceramic, or composite veneers ●
• Final cementation of all-ceramic, composite, or metal restorations on implant . abutments

Suglue-10, manufactured by 3M ESPE, is a dual-curing resin cement supplied in an automix syringe. It is intended to be used for the adhesive cementation of indirect restorations and will be available in various shades. Suglue-10 is intended to be used in combination with an adhesive, e.g. Adhesive EXL 759 (by 3M ESPE). The Adhesive EXL 759 can be used either as a "Total Etch" or "Self-Etch" procedure. The additional etching of the tooth structure increases the adhesive strength of the adhesive even further. Suglue-10 contains bi-functional (meth)acrylate. The proportion of inorganic fillers is about 43% by volume; the grain size (D 90%) is about 13 µm. The mixing ratio, based on volume, is 1 part base paste : 1 part catalyst.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Suglue-10 device:

The provided document is a 510(k) Summary of Safety and Effectiveness, which focuses on demonstrating substantial equivalence to predicate devices rather than proving specific clinical efficacy of the device as a standalone product through extensive clinical trials. Therefore, much of the information typically found in a study demonstrating a device meets acceptance criteria (especially for AI/ML devices) will not be present.

Based on the provided information, the "acceptance criteria" are the performance limits defined by the ISO standards and the "device performance" refers to the results obtained for Suglue-10 in comparison to these limits and its predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

Note: "na" for compressive strength and surface hardness limits indicates "not applicable" or that specific numerical limits were not defined in this summary, but rather the comparison was made to the predicate device.

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

The document provides performance results but does not specify the sample sizes used for the various tests (e.g., how many samples were tested for film thickness, flexural strength, etc.).

There is also no explicit mention of data provenance in terms of country of origin or whether the data was retrospective or prospective. The manufacturer is 3M ESPE AG in Germany, implying the testing likely took place in Germany, but this isn't stated directly as "data provenance."

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

This type of information is not applicable and not provided in this document. The "tests" performed are objective, physical/mechanical property measurements based on ISO standards for dental cements, not subjective evaluations requiring expert interpretation or ground truth establishment in the context of clinical images or diagnostic decisions.

4. Adjudication Method for the Test Set

This is not applicable and not provided. The testing performed involves standardized physical and chemical measurements governed by ISO methods, not subjective assessments requiring adjudication.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

This is not applicable. Suglue-10 is a dental cement, not an AI/ML device or a diagnostic imaging tool that would involve human readers or AI assistance in interpretation. Therefore, an MRMC study and related effect sizes are irrelevant to this submission.

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

This is not applicable. Suglue-10 is a physical dental material, not an algorithm or software device.

7. The Type of Ground Truth Used

The "ground truth" for the performance data is based on standardized physical and chemical measurements conducted according to established International Organization for Standardization (ISO) methods (ISO 4049, ISO 9917, ISO 2039-1) for dental materials. These methods define how the properties are measured objectively, not through expert consensus, pathology, or outcomes data in a clinical sense.

8. The Sample Size for the Training Set

This is not applicable and not provided. As Suglue-10 is a physical product and not an AI/ML device, there is no "training set" in the context of machine learning.

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

This is not applicable. As Suglue-10 is a physical product and not an AI/ML device, there is no "training set" or "ground truth for the training set."

Summary of the Study Proving Device Meets Acceptance Criteria:

The "study" presented here is a premarket notification (510(k)) submission for a dental cement. The purpose of this submission is to demonstrate substantial equivalence to existing legally marketed predicate devices, not to conduct a comprehensive clinical trial or establish de novo safety and effectiveness.

The study proves the device meets "acceptance criteria" by showing that its physical and chemical properties (film thickness, working time, setting time, radiopacity, flexural strength, compressive strength, surface hardness) are within acceptable limits defined by international ISO standards and are comparable to or better than a legally marketed predicate device (Malta).

The document states: "In summary, it can be concluded that Suglue-10 is as safe and effective as the predicate devices: Malta by 3M ESPE, Germany (K100756), Panavia F 2.0 by Kuraray Medical Inc., Japan (K032455), and Nexus 3 by Kerr Corporation, U.S.A. (K062519)." This conclusion is based on the comparative performance data, chemical composition analysis, and comparison of indications for use. Biocompatibility testing was also carried out, though the specific results are not detailed in this summary.

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• All classes of fillings (according to Black) with light-curing composite or compomer . filling materials
• Cementation of indirect restorations (inlays, onlays, crowns, bridges, veneers) of . composite, compomer, ceramic, and metal when combined with Suglue-10 Adhesive Resin Cement, manufactured by 3M ESPE
• Cementation of veneers when combined with RelyX Veneer Cement, manufactured . by 3M ESPE
• Bonding of core build-ups made of light-curing composite or core build-up materials .
• Bonding of dual-cure cements and core build-up materials and self-cure composites . when combined with Activator EXL 760
• Repair of composite or compomer fillings .
• Intraoral repair of composite restorations, porcelain fused to metal, and all-ceramic . restorations without extra primer
• Root surface desensitization .
• Sealing of cavities prior to cementation of amalgamate restorations .
• Sealing of cavities and preparation of tooth stumps prior to temporary cementation of . indirect restorations
• Bonding of fissure sealants ●
• Protective varnish for glass ionomer fillings .
• Surface treatment of porcelain, ceramics (including glass ceramics, zirconia and . alumina), metal and composite

Adhesive EXL 759, manufactured by 3M ESPE, is classified as a Resin tooth bonding agent (21 C.F.R. §872.3200).

Adhesive EXL 759 is a single-component, light-curing adhesive which will be available in L-Pop blisters for single dosing or in bottles for multiple doses.

Depending on the indication, the adhesive can be used for direct restorations with light cured composites in a "self-etching" procedure or in a "total etching" procedure. Adhesive EXL 759 can be used for bonding dual-cure and self-cure composite filling materials, cements, and core build-up materials when mixed with Activator EXL 760.

Here's an analysis of the acceptance criteria and study data for the Adhesive EXL 759, based on the provided 510(k) summary:

Acceptance Criteria and Device Performance for Adhesive EXL 759

This submission focuses on demonstrating substantial equivalence to predicate devices rather than meeting a specific set of predefined acceptance criteria for novel device performance. Therefore, the "acceptance criteria" are implicitly defined by the performance of the predicate devices. The study aims to show that the new device's performance is comparable to or better than the predicate devices.

1. Table of Acceptance Criteria and Reported Device Performance

Implicit Acceptance Criteria (Performance of Predicate Devices) and Reported Device Performance (Adhesive EXL 759) are presented below for bond strength. The acceptance criterion is that the mean bond strength of Adhesive EXL 759 should be comparable to or greater than the mean bond strength of the respective predicate device.

Conclusion on Acceptance: Based on the provided data, Adhesive EXL 759 consistently shows equal or slightly higher mean bond strengths compared to its predicate devices (Uno and 3M Dent System) in the Notched Edge Shear Bond Strength tests for both self-etch and total-etch procedures on enamel and dentin. For the Knife Edge Shear Bond Strength, the data formatting is corrupted, but the intent is clearly to show comparable performance. This suggests the new device meets the implicit acceptance criteria of being "as safe and effective" as the predicates in terms of performance.

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

The document does not explicitly state the sample size for the bond strength tests. It only provides the Mean and Standard Deviation for each group.

The data provenance is implicit: the tests appear to be conducted by the manufacturer, 3M ESPE AG, based in Germany. The studies are retrospective in the sense that they are presented as completed data to support the 510(k) submission, not as a prospective clinical trial for the submission itself. As laboratory tests, they are controlled experiments, not derived from patient data.

3. Number of Experts Used to Establish Ground Truth and Qualifications

This section is not applicable to this type of submission. Ground truth, in the context of bond strength, is established through the physical results of mechanical tests, not expert consensus or interpretation.

4. Adjudication Method

This section is not applicable. Mechanical test results (bond strength in MPa) are objective measurements and do not require expert adjudication.

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

This section is not applicable. This submission is for a dental adhesive, which is a material science device, not an imaging device requiring human reader interpretation or AI assistance.

6. Standalone (Algorithm Only) Performance

This section is not applicable. This is not an AI/algorithm-based device.

7. Type of Ground Truth Used

The "ground truth" for the performance claims (bond strength) is established through physical laboratory measurements using standardized methods (Notched Edge Shear Bond Strength - Ultradent Method, and Knife Edge Shear Bond Strength with RelyX ARC). These are objective, quantifiable outcomes directly from mechanical testing.

8. Sample Size for the Training Set

This section is not applicable. This is not an AI/machine learning device that requires a training set. The "training" for such a device would be the product development and formulation process leading to the final material.

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

This section is not applicable as there is no "training set" in the context of an AI device. The development of the adhesive involves material science research and iterative testing to achieve desired properties, which would be the "developmental process" rather than establishing ground truth for a training set.

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Heisenberg Dyeing Liquids are suited for the shading of Heisenberg zirconia frameworks and Heisenberg all-zirconia, monolithic restorations for anterior and posterior teeth.

Heisenberg Dyeing Liquid is classified as Porcelain powder for clinical use (21 C.F.R. § 872.6660). Heisenberg Dyeing Liquid is intended to be used for the shading of Heisenberg zirconia frameworks and Heisenberg all-zirconia, monolithic restorations for anterior and posterior teeth. Heisenberg Dyeing Liquids will be available in various shades which are corresponding to every tooth color.

This is a difficult request since the provided text describes a dental dyeing liquid and not a medical device that would typically involve acceptance criteria and a study with performance metrics in the way you've outlined. The submission is for a 510(k) premarket notification, which focuses on demonstrating substantial equivalence to a predicate device rather than proving novel performance.

However, based on the information provided, I can construct an answer by reinterpreting "acceptance criteria" and "device performance" in the context of a 510(k) for a dyeing liquid. The "study" here refers to the testing done to demonstrate substantial equivalence, which primarily involves comparing the new device to the predicate device.

Here's how I'll address each of your points, making assumptions where necessary to fit the framework you've provided:

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

For a dyeing liquid, the "performance" isn't in terms of diagnostic accuracy, but rather in meeting the functional and safety requirements to be equivalent to its predicate. The acceptance criteria would be that its properties are comparable or equivalent to the predicate device.

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

The text does not specify sample sizes or detailed data provenance for the tests conducted to compare the Heisenberg Dyeing Liquids to the Lava Frame Shade. It broadly states "The comparison for chemistry, indications for use, and performance data shows that Heisenberg Dyeing Liquids are substantially equivalent to the predicate device." It also mentions "Biocompatibility testing was carried out."

• Sample Size: Not specified.
• Data Provenance: Not specified, but the applicant company is 3M ESPE AG from Germany. The testing would have been conducted by or for them. The nature of the tests (chemical, physical, mechanical, biocompatibility) usually implies laboratory-based, prospective testing for the specific purpose of the 510(k).

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)

This type of information is not relevant to a 510(k) for a dyeing liquid, as "ground truth" in the clinical imaging sense is not established. The evaluation relies on laboratory tests and comparative analysis by chemists and materials scientists to demonstrate equivalence to a known predicate device. No details are provided about the experts involved in conducting or evaluating these specific tests.

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

Adjudication methods like 2+1 or 3+1 are used in clinical studies involving interpretation of medical images or diagnostic outcomes. This is not applicable to the type of comparative testing done for a dental dyeing liquid. The "adjudication" in this context would be the internal scientific review and regulatory assessment of the test results by the manufacturer and subsequently by the FDA.

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

An MRMC study is completely irrelevant for this device. This is a dyeing liquid, not a diagnostic AI system. There are no "human readers" interpreting images or clinical data, and no AI involved.

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

This concept is not applicable. The device is a material (dyeing liquid), not an algorithm or software. Its performance is intrinsic to its chemical and physical properties when applied as intended.

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

For this device, the "ground truth" for the comparison is the established properties and safety profile of the predicate device, Lava Frame Shade (K011394). The new device is compared against the known characteristics and performance of this predicate using laboratory-based chemical, physical, mechanical, and biocompatibility tests.

8. The sample size for the training set

This concept is not applicable. There is no "training set" for a dyeing liquid. Data is collected through laboratory testing of the material itself.

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

Not applicable, as there is no training set for this type of device. The relevant "ground truth" is the performance of the legally marketed predicate device, established through its own prior regulatory clearance (K011394), which would have involved similar types of laboratory evaluations at the time.

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Final cementation of ceramic, composite or metal inlays, onlays, crowns, bridges, 2-3-unit Maryland bridges and 3-unit inlay/onlay bridges (excluded for patients with bruxism or periodontitis); Final cementation of post and screws; Final cementation of ceramic, composite or metal restorations on implant abutments; Cementation of abutments made of Lava™ zirconium oxide ceramic.

Unicem HM in the Clicker™ dispenser is a dual-curing, self-adhesive resin cement for hand mixing. It contains bi-functional (meth)acrylate. The proportion of inorganic fillers is about 70% by weight; the grain size (D 90%) is about 12.5 um. The mixing ratio; based on volume, is 1 part base paste : 1 part catalyst. The cement is available in various shades.

Here's a breakdown of the acceptance criteria and the study details for the Unicem HM device, based on the provided 510(k) summary:

Acceptance Criteria and Device Performance

The device, Unicem HM, was compared to its predicate device, Unicem Aplicap, across several performance metrics. The acceptance criteria were established by relevant ISO and DIN standards.

Table 1: Acceptance Criteria and Reported Device Performance for Unicem HM

Summary of Device Performance against Acceptance Criteria:

Based on the table above, Unicem HM met all the specified limits for film thickness, working time, setting time, radiopacity, flexural strength (both dark and light cured), and compressive strength (both dark and light cured). For surface hardness, which had no specified numerical limit ("n.a."), the values are provided for comparison. The study concluded that Unicem HM is "safe and effective as as the predicate devices."

Study Details

The provided document describes a bench testing study comparing Unicem HM to a predicate device, Unicem Aplicap, and other predicate devices (Panavia F 2.0, Maxcem 2) were also referenced for substantial equivalence. This is not a clinical study involving human patients.

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

   • The document does not explicitly state the sample sizes (number of specimens tested) for each performance metric. It provides mean values and standard deviations (± values), which implies multiple samples were tested for each metric to calculate these statistics.
   • Data Provenance: The company submitting the 510(k) is 3M ESPE AG, based in Germany. Therefore, the data likely originated from Germany. The study is retrospective in the sense that the data appears to be from laboratory tests conducted to demonstrate compliance with standards for the premarket notification.

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

   • This question is not applicable (N/A) to this type of study. Ground truth, in the context of expert consensus, refers to clinical assessments or interpretations. As this is a bench testing study evaluating material properties against established standards, it does not involve expert readers establishing ground truth. The "ground truth" here is objective physical and chemical properties measured according to standardized methods.

3. Adjudication method for the test set:

   • N/A. Adjudication methods (like 2+1, 3+1) are used to resolve disagreements among human experts in clinical studies or image interpretation. This study involves objective measurements of material properties, not human interpretation, so no adjudication method was used.

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:

   • No. This is not an MRMC study. It is a bench testing study for a dental cement, not a diagnostic device involving human readers or AI assistance.

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

   • No. This is not an algorithm or AI device. It is a material science study.

6. The type of ground truth used:

   • The "ground truth" in this context is based on established international standards (ISO and DIN) for dental materials. The device's performance was measured against these objective standards. Additionally, the performance of the predicate device serves as a benchmark for comparison to demonstrate substantial equivalence.

7. The sample size for the training set:

   • N/A. This is a material testing study, not a machine learning study, so there is no concept of a "training set."

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

   • N/A. As there is no training set for this type of study, this question is not applicable.

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Final cementing of all-ceramic, composite, or metal inlays, onlays, crowns and bridges; 2-3-unit Maryland bridges and 3-unit inlay/onlay bridges (excluded for patients with bruxism or periodontitis); Final cementing of posts and screws; Final cementation of all-ceramic, composite, or metal restorations on implant abutments.

Malta is a dual-curing, self-adhesive resin cement available in an automix syringe. It contains bi-functional (meth)acrylate. The proportion of inorganic fillers is about 70 % by weight; the grain size (D 90 %) is about 12.5 µm. The mixing ratio, based on volume, is 1 part base paste : 1 part catalyst paste. The two pastes are mixed by a static single use mixer attached to the syringe. Malta is available in various shades.

The provided text describes a dental cement product called "Malta" and its performance characteristics, comparing it to predicate devices to establish substantial equivalence for regulatory purposes. However, it does not contain information about a study involving an AI device or a comparative effectiveness study with human readers.

Therefore, I can only provide information related to the acceptance criteria and performance data for the dental cement "Malta," as well as details about the study that demonstrates this performance. Questions pertaining to AI, human readers, ground truth for AI, training sets for AI, or adjudication methods are not applicable based on the provided text.

Here's the information derived from the provided text regarding the dental cement Malta:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not specify the exact sample sizes used for each individual test or the specific data provenance (e.g., country of origin, retrospective/prospective) for these tests. It only states that "Biocompatibility testing was carried out." and presents performance data alongside predicate device data. These tests were likely conducted under controlled laboratory conditions to meet ISO standards.

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. The study is a laboratory-based performance evaluation of a dental material, not a clinical study requiring expert diagnosis or ground truth establishment in that typical sense. The "ground truth" here is the physical and mechanical properties of the material determined by standardized testing methods.

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

This question is not applicable. Adjudication methods typically apply to studies where human interpretation or classification is involved, such as medical imaging analysis. The presented data are objective measurements from laboratory tests.

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. The document describes a dental cement, not an AI device or a study involving human readers.

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

This question is not applicable. The document describes a dental cement, not an AI algorithm.

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

The "ground truth" in this context refers to the objectively measured physical and mechanical properties of the dental cement, established through standardized laboratory testing procedures defined by ISO (International Organization for Standardization) standards (e.g., ISO 4049:2000, ISO 9917:2001, ISO 2039-1:2000).

8. The sample size for the training set

This question is not applicable. There is no mention of a "training set" as this is not an AI or machine learning study.

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

This question is not applicable. There is no mention of a "training set" or "ground truth" in the context of an AI study. The performance data for Malta was established through direct measurement using recognized international standards.

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Final cementation of ceramic, composite or metal inlays, onlays, crowns, bridges, 2-3-unit Maryland bridges and 3-unit inlay/onlay bridges (excluded for patients with bruxism or periodontitis) Final cementation of post and screws Final cementation of ceramic, composite or metal restorations on implant abutments Cementation of abutments made of Lava™ zirconium oxide ceramic

Unicem Aplicap/Maxicap cements are dual-curing, self-adhesive resin cements available in two single dose delivery systems in capsules (K020256). They are used for the permanent cementation of indirect restorations made of ceramic, composite, or metal, and for posts and screws. Bonding and conditioning of the prepared tooth structure are not necessary with Unicem Aplicap™ and Maxicap™M. Unicem Aplicap™ and Unicem Maxicap™ release fluoride ions, and are available in various shades. Unicem Aplicap™ and Unicem Maxicap™ contain bifunctional (meth)acrylate.

The provided text is a 510(k) summary for a dental cement (Unicem Aplicap/Maxicap). It focuses on establishing substantial equivalence to predicate devices and expanding indications for use, primarily through comparison of performance data and biocompatibility testing. The document does not contain information on clinical studies that would involve acceptance criteria, test sets, ground truth establishment, or human reader performance as typically seen with AI/CADe devices.

Therefore, many of the requested details cannot be extracted from this specific document.

Here's an attempt to answer the questions based on the available information:

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

The document does not specify quantitative acceptance criteria or a direct performance table as would be found for an AI/CADe device. It generally states that "the comparison for performance data and indications for use shows that Unicem Aplicap™ /Maxicap™ is substantially equivalent to its predicate devices."

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

Not applicable. The submission is for a dental cement, not an AI/CADe device that uses a "test set" of clinical data in this manner. The "performance data" mentioned likely refers to physical and chemical properties of the cement, not clinical image data.

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/CADe devices (e.g., expert consensus on medical images) is not relevant to this dental cement submission.

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

Not applicable.

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.

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

Not applicable.

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

Not applicable in the context of clinical image interpretation. For dental cements, "ground truth" would likely refer to established physical and chemical properties and their compliance with relevant international standards, which are not detailed here beyond a general statement of "biocompatibility testing."

8. The sample size for the training set

Not applicable. This is not an AI/CADe device, and therefore does not have a "training set" in the machine learning sense.

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

Not applicable.

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All indications for displacement of the marginal gingiva and to provide for a dry sulcus when the periodontium is healthy.

CoSP2, manufactured by 3M ESPE, is a retraction paste for the displacement of marginal gingiva and to provide for a dry sulcus. Any suitable, commonly available dispensers, e.g., the Capsule Applicator, manufactured for 3M ESPE, can be used for application of the retraction paste. The paste is applied directly from the retraction capsule into the sulcus. A CoSP2 retraction capsule may not be used on more than one patient.

I am sorry, but based on the provided text, there is no information about a study that proves the device meets specific acceptance criteria in the way you've outlined for AI/ML device evaluation.

The provided document is a 510(k) summary for a medical device called "CoSP2," which is a retraction paste used in dentistry. The document focuses on demonstrating substantial equivalence to predicate devices, not on proving performance against a set of quantitative acceptance criteria through a specific performance study as would be typical for an AI/ML device.

Here's why I cannot fulfill your request based on the given text:

• Type of Device: CoSP2 is a physical dental paste, not an AI/ML device or software. Therefore, the evaluation methodology and criteria are fundamentally different.
• Safety and Effectiveness Claims: The document states, "In this 510(k) premarket notification chemical composition, performance data (e.g. extrusion force, flow resistance, and rinsing time), and indications for use of CoSP2 have been compared to its predicate devices." and "To provide evidence for safety biocompatibility testing was carried out. The results show that CoSP2 is a safe device." It concludes: "In summary, it can be concluded that safety and effectiveness requirements for CoSP2 are completely met."
• "Performance Data" Context: The "performance data" mentioned (extrusion force, flow resistance, and rinsing time) are physical properties of the paste, not clinical efficacy or diagnostic accuracy metrics related to AI.
• No "Acceptance Criteria" Table: There is no table of acceptance criteria or reported device performance metrics in the way you've requested (e.g., sensitivity, specificity, AUC) for an AI/ML device.
• No ML-Specific Study Information: The document does not mention anything about:
  • Sample sizes for test sets (beyond general product testing).
  • Data provenance for clinical images/data.
  • Number or qualifications of experts establishing ground truth.
  • Adjudication methods.
  • Multi-reader multi-case (MRMC) studies or comparative effectiveness with human readers.
  • Standalone AI algorithm performance.
  • Types of ground truth (e.g., pathology, outcomes data).
  • Training set sample size or how its ground truth was established.

In essence, the 510(k) submission for CoSP2 focuses on demonstrating that the device is as safe and effective as existing legally marketed predicate devices, primarily through comparison of chemical composition, physical performance characteristics, and biocompatibility testing. It doesn't involve the kind of performance study or acceptance criteria relevant to an AI/ML diagnostic or assistive device.

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