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510(k) Data Aggregation
(3 days)
Denture Base Resin is a light-curable polymerizable resin intended to be used for the fabrication of full and partial removable dentures. Fabrication of denture base Resin requires a digital denture file, 3D printer and post-curing unit.
Denture Base Resin is a liquid light-curable material. The product should be used in combination with the 3D printer. Printer and resin must be optimized to each other in order to get complete and precise printed parts. The 3D printer and the post-curing unit of SHINING3D make use of a light source to polymerize the Denture Base Resin.
I am sorry, but the provided text does not contain information about the acceptance criteria and study that proves the device meets the acceptance criteria in the format you requested, as it pertains to a medical device's AI/algorithm performance.
The document is a 510(k) premarket notification for a Denture Base Resin (a material used for making dentures). It focuses on:
- Substantial Equivalence: Comparing the new resin to an existing predicate resin based on material composition, intended use, manufacturing process, and various performance and biocompatibility tests for dental materials.
- Non-Clinical Performance Tests: These tests are for the physical and biological properties of the resin material itself, such as mechanical properties according to ISO 20795-1, color stability according to ISO 7491, biocompatibility according to ISO 10993-1 and ISO 7405, and shelf-life.
- No Clinical Study: The document explicitly states, "No clinical study is included in this submission."
Therefore, I cannot provide a table of acceptance criteria and reported device performance related to AI/algorithm, nor can I answer questions about sample sizes for test sets, data provenance, ground truth establishment by experts, adjudication methods, MRMC studies, or standalone algorithm performance, as these concepts are not addressed in the provided text which describes a physical dental material, not an AI medical device.
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(84 days)
Denture Base resin is a light-curable polymerizable resin intended to be used for the fabrication and repair of full and partial removable dentures and baseplates. The material is an alternative to traditional denture base material.
Fabrication of dental prosthetics with Denture Base resin requires computer-aided design and manufacturing system that includes the following components not part of the device: oral casting impression, digital denture base file created in an optical impression system, 3D printer, and curing light equipment.
The Denture Base consists of a curable dental acrylate resin that is designed to be used in conjunction with a scanned 3D image of a patient's teeth, and 3D printer assembly, to locally manufacture out a dental appliance in dental offices based on the clinician's judgment of patient need.
Denture Base resin is intended exclusively for professional dental work.
Denture Base is designed to meet appropriate ISO standards for flexibility, sorption, and solubility to withstand prolonged use in the oral cavity. It is delivered non-sterile, and instructions are provided on cleaning the material prior to providing it to a patient. Curing is performed with a UV lamp. The appliance is then cleaned, trimmed, and verified to fit in the dental office before the patient leaves.
I am sorry, but the provided text does not contain the information needed to answer your request. The document is an FDA 510(k) clearance letter and summary for a denture base resin, focusing on the substantial equivalence to a predicate device through biocompatibility and bench testing.
Specifically, the document does not describe acceptance criteria for a study, nor does it detail a study that proves a device meets such criteria in the way you've outlined for AI/software-based medical devices.
The document describes material testing for a physical product (denture resin), not the performance of an algorithm or AI model. Therefore, information such as sample sizes for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, type of ground truth, training set size, and how training ground truth was established, are not present.
The "performance data" mentioned in the document refers to:
- Biocompatibility Testing: According to ISO 10993-1, covering tests like Cytotoxicity, Genotoxicity, Acute Systemic Toxicity, Subchronic toxicity, Irritation, and Sensitization.
- Bench Testing: According to ISO 20795-1, covering tests like Ultimate Flexural Strength and Modulus, Water Sorption and Solubility, Residual Methyl Methacrylate Monomers, Homogeneity, Surface Characteristics, Shape Capability, Translucency, Polishability, Colour, Freedom from Porosity, Color Stability, Maximum stress intensity factor, Total fracture work, and Bonding to synthetic polymer teeth.
These are tests of the physical properties and biological safety of the material, not algorithmic performance.
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(126 days)
Denture Base Resin is a light-curable resin indicated for the fabrication of:
•individual and fixed permanent full single crowns, permanent partial crowns in front and posterior area
•denture bases
Denture Base Resin is intended exclusively for professional dental work.
The Denture Base Resin is an alternative to traditional heat cured and auto polymerization resins. The resins are available in two (2) different colors ( white, red). Denture Base Resin can be used with PioNext D Series. PioNext D Series printers include a 3D printing system that utilizes Digital Light Process (DLP) technology, with automatic feeding process, and a UV LED (405nm) curing process. The dental appliance is then cured in the PioNext UV-02 curing chamber and sent back to the dentist for try-in and final adjustment.
I'm sorry, but this document does not contain the information required to answer your request. The provided text is a 510(k) premarket notification letter from the FDA regarding a "Denture Base Resin" device.
It does not provide details about acceptance criteria or a study proving that an AI/software-based device meets these acceptance criteria. Instead, it focuses on dental resin material properties and non-clinical performance tests, not AI or software performance.
Therefore, I cannot provide:
- A table of acceptance criteria and reported device performance for an AI/software.
- Sample sizes used for test sets or data provenance for AI/software.
- Number of experts or their qualifications for establishing ground truth for AI/software.
- Adjudication methods for AI/software test sets.
- Information about MRMC comparative effectiveness studies or effect sizes for AI assistance.
- Standalone performance of an AI algorithm.
- Type of ground truth for an AI/software.
- Sample size for training sets for an AI/software.
- How ground truth was established for training sets for an AI/software.
The document discusses "Denture Base Resin" and its properties, and confirms its substantial equivalence to predicate devices based on non-clinical performance tests related to dimensional stability, color stability, translucency, flexural strength, freedom from porosity, and water solubility. There is no mention of AI, machine learning, or software performance evaluation in this context.
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(59 days)
Denture Base Resin is used for the fabrication of removable dentures.
The Denture Base Resin mainly consist of denture base resin (powder), polymethyl methacrylate (PMMA), methyl methacrylate, ethylene glycol dimethacrylate, titanium dioxide, ferric oxide, iron oxide yellow and ferric tetroxide. The resin block is milled using the CAD/CAM technique to form the removable dentures. The product combines the prosthetic denture teeth with the denture base.
The provided document is a 510(k) premarket notification for a medical device called "Denture Base Resin." This type of submission focuses on demonstrating substantial equivalence to a predicate device, rather than proving novel clinical effectiveness or safety through new clinical trials. Therefore, the information typically requested in your prompt regarding AI/ML device performance (e.g., acceptance criteria for a specific AI metric, human-in-the-loop performance, large test sets, expert ground truth adjudication) is not applicable to this submission.
This document describes a traditional dental material. The performance data presented are for material properties, not an AI/ML algorithm.
Here's why many of your detailed questions cannot be answered by this document:
- AI/ML Device: This is not an AI/ML device. It's a physical material used for fabricating dentures.
- Acceptance Criteria for AI Performance: The acceptance criteria are for physical material properties as defined by ISO standards, not for AI metrics like sensitivity, specificity, AUC, or F1-score.
- Sample Size for Test Set (AI): There's no AI test set. Instead, there are samples of the material tested for its physical and chemical properties.
- Data Provenance (AI): Not applicable. The "data" are laboratory measurements of material properties.
- Experts for Ground Truth (AI): Not applicable. Ground truth for material properties is established through standardized laboratory testing methods.
- Adjudication Method (AI): Not applicable.
- MRMC Study (AI): Not applicable. This refers to human reader performance with/without AI assistance for diagnostic tasks, which is irrelevant here.
- Standalone Performance (AI): Not applicable.
- Type of Ground Truth (AI): For this device, "ground truth" refers to the measured physical and chemical properties of the material against established standards (e.g., ISO, FDA guidance).
- Training Set (AI): Not applicable. This device is not developed using machine learning.
- Ground Truth for Training Set (AI): Not applicable.
Based on the provided document, here's what can be extracted regarding the "acceptance criteria" (which are performance specifications for the material) and its "study" (which are non-clinical bench tests):
1. Table of Acceptance Criteria and Reported Device Performance
The acceptance criteria are implicitly defined by the relevant ISO standards (ISO20795-1: 2013, ISO 4049: 2019, ISO 7491: 2000) and the comparison to the predicate device. The performance data demonstrate compliance with these standards and substantial equivalence.
| Item | Acceptance Criterion (Implicit: Meet relevant ISO standards and be similar to predicate) | Reported Device Performance (Denture Base Resin) | Predicate Device Performance (IvoBase CAD for Zenotec) |
|---|---|---|---|
| Ultimate flexural strength | > Predicate's Performance (or within acceptable range to prove SE) and meet ISO standards | 87 Mpa | 82 Mpa |
| Flexural modulus | > Predicate's Performance (or within acceptable range to prove SE) and meet ISO standards | 2340 Mpa | 2032 Mpa |
| Residual methyl methacrylate monomer | ≤ Predicate's Performance (or within acceptable range to prove SE) and meet ISO standards | 1.29% | 1.34% |
| Sorption | ≤ Predicate's Performance (or within acceptable range to prove SE) and meet ISO standards | 23.64 µg/mm³ | 19.48 µg/mm³ |
| Solubility | ≤ Predicate's Performance (or within acceptable range to prove SE) and meet ISO standards | 0.25 µg/mm³ | 0.65 µg/mm³ |
| Maximum stress intensity factor for materials with improved impact resistance | > Predicate's Performance (or within acceptable range to prove SE) and meet ISO standards | 2.89 MPa m¹ᐟ² | 2.35 MPa m¹ᐟ² |
| Total fracture work | > Predicate's Performance (or within acceptable range to prove SE) and meet ISO standards | 1609 J/m² | 1411 J/m² |
| Biocompatibility | Pass all required biocompatibility tests (ISO 10993-1) for surface device, permanent contact (>30 d) with mucosal membrane | Passed (Cytotoxicity, Sensitization, Irritation, Acute systemic toxicity, Subchronic systemic toxicity, Implantation, Material-mediated pyrogenicity, Genotoxicity) | Passed (Assessed as equivalent) |
| Other Performance Bench Tests | Meet all design specifications and relevant ISO standards (Surface characteristics, Shape capability, Colour, Colour stability, Translucency, Freedom from porosity, Bonding to synthetic polymer teeth) | Complies with ISO standards | Complies with ISO standards |
2. Sample size used for the test set and the data provenance:
- Sample Size: The document does not specify the exact sample sizes for each bench test conducted (e.g., how many specimens for flexural strength). It generally states that "Performance testing were conducted to verify that the subject device met all design specifications." Specific sample sizes would be detailed in the full test reports, which are not part of this summary.
- Data Provenance: The tests are non-clinical bench tests performed in a laboratory setting, presumably by the manufacturer (Aidite (Qinhuangdao) Technology Co., Ltd) or a contracted lab. The country of origin for the data is implicitly China, as the manufacturer is based there. The data are retrospective in the sense that they were collected prior to the submission.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not applicable as this is not an AI/ML device requiring expert interpretation for ground truth. The "ground truth" for material properties is established through standardized and validated laboratory testing procedures as per ISO standards.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- Not applicable. This concept applies to human reader studies often seen with diagnostic AI/ML devices, not material property testing.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:
- No, an MRMC comparative effectiveness study was not done. This is not an AI/ML device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- No, a standalone algorithm performance study was not done. This is not an AI/ML device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
- The "ground truth" for this device's performance is derived from standardized laboratory measurement methods as described in the cited ISO standards (e.g., ISO20795-1 for denture base polymers, ISO 4049 for polymer-based restorative materials, ISO 7491 for color stability) and biocompatibility testing according to ISO 10993-1. Comparison is also made to the performance characteristics of the predicate device.
8. The sample size for the training set:
- Not applicable. This device is not an AI/ML algorithm that requires a training set.
9. How the ground truth for the training set was established:
- Not applicable.
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(157 days)
Denture Base Polymers is used for fabrication and repair of partial and full denture base for patients with missing teeth.
Denture Base Polymers contains powder and liquid, wherein the power is mainly composed of polymethyl methacrylate, and the main composition of the liquid is methyl methacrylate.
This document is a 510(k) premarket notification for a medical device called "Denture Base Polymers." It's a submission to the FDA (U.S. Food & Drug Administration) to demonstrate that the device is "substantially equivalent" to legally marketed predicate devices, meaning it's as safe and effective as a device already on the market.
However, the provided text does not describe a study involving "acceptance criteria" and "device performance" in the context of an AI/algorithm-based diagnostic or prognostic device. It's for a dental material (denture base polymers), which is a physical product, not a software or AI device.
Therefore, I cannot extract the information required for your request, such as a table of acceptance criteria for AI performance, sample sizes for test sets in an AI study, expert ground truth establishment, MRMC studies, or standalone algorithm performance.
The document primarily focuses on:
- Chemical composition of the denture material.
- Technological characteristics (e.g., heat curing, self-curing).
- Physical and chemical properties that meet ISO standards (ISO 20795-1 for Dental base material).
- Biocompatibility testing (following ISO 10993 standards) to ensure it's safe for use in the human body.
- Comparison to predicate devices to demonstrate substantial equivalence for its intended use (fabrication and repair of partial and full denture base).
It explicitly states: "10. Clinical Performance Data: Not applicable. Clinical performance testing has not been performed on the subject device." This further confirms that no clinical studies in the sense of a performance study for an AI device were conducted or are being reported here.
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(94 days)
Smiletone® (denture base resin) is a thermoplastic resin that is intended to be used in fabrication of removable full and partial dental prosthesis, as well as occlusal splints and night guards. The product is based on a compounded mixture of polyamide and pigments.
Smiletone® is a thermoplastic material to be used for removable full or partial dental prosthesis. The product is based on a compounded mixture of Polyamide and pigments. Smiletone® is classified as 'Type 3-thermoplastic blank or powder' by EN ISO 20795-1[2013].
The provided document describes the 510(k) premarket notification for the Smiletone® denture base resin, not a device with AI or machine learning components. Therefore, many of the requested categories related to AI/ML device studies (such as multi-reader multi-case studies, effect size of AI assistance, expert qualifications for ground truth, adjudication methods, and training/test set sample sizes for algorithms) are not applicable.
However, the document does contain information about performance testing and acceptance criteria for the material.
Here's a summary of the available information based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The document doesn't explicitly list "acceptance criteria" with numerical thresholds against which the device performance is reported. Instead, it states that "All test results were satisfactory" and indicates "Pass" for each test against various standards. The acceptance criteria are implied to be meeting the requirements of the specified standards (e.g., EN ISO 20795-1, ISO 10993 series).
| Test Title | Test Standard | Reported Device Performance (Acceptance Criteria Implicitly Met) |
|---|---|---|
| Dentistry - Medical devices for dentistry - Materials testing | EN 1641 (2010) | Pass |
| Accelerate aging test | ASTM F1980 (2002) | Pass |
| Visual Inspection | Performance test Guidance of dental materials (KFDA 2014) | Pass |
| Capacity test | Performance test Guidance of dental materials (KFDA 2014) | Pass |
| Packaging (Visual Inspection) test | Performance test Guidance of dental materials (KFDA 2014) | Pass |
| Surface characteristics test | EN ISO 20795-1 | Pass |
| Shape characteristics test | EN ISO 20795-1 | Pass |
| Color test | EN ISO 20795-1 | Pass |
| Color Stability test | EN ISO 20795-1 | Pass |
| Translucency test | EN ISO 20795-1 | Pass |
| Freedom from porosity test | EN ISO 20795-1 | Pass |
| Bonding to synthetic polymer teeth test | EN ISO 20795-1 | Pass |
| Residual Monomer test | EN ISO 20795-1 | Pass |
| Sorption test | EN ISO 20795-1 | Pass |
| Solubility test | EN ISO 20795-1 | Pass |
| Ultimate flexural strength test | EN ISO 20795-1 | Pass |
| Genotoxicity test: BACTERIAL REVERSE MUTATION STUDY (AMES) | ISO 10993-3 & OECD 471 Bacterial Reverse Mutation Test | Pass |
| Cytotoxicity Test (Agar diffusion test) | ISO7405:2008 | Pass |
| Acute Systemic Toxicity Test | ISO 10993-11 | Pass |
| Maximization Sensitization Test (LLNA-BrdU) | ISO 10993-10 & OECD 442B:2010 | Pass |
| Oral mucosa irritation test | ISO10993-10:2010 Annex B.3 | Pass |
Note on Physical Properties (Specific Values from Predicate Comparison):
While not explicitly stated as "acceptance criteria" for Smiletone, the comparison table ([6]) provides specific physical property values for Smiletone and its predicates. For Smiletone:
- Flexural strength: 68 ± 2 MPa
- Flexural modulus: 1389 ± 35 MPa
- Water absorption: 30.7 ± 0.2 µg/mm²
- Water solubility: 0.33 ± 0.1 µg/mm²
These values would implicitly need to meet certain ranges or be comparable to the predicates as part of the overall demonstration of substantial equivalence.
2. Sample size used for the test set and the data provenance
The document does not specify the sample sizes used for each of the physical, chemical, and biological tests. It states that tests were performed according to standards (e.g., ISO, ASTM, OECD, KFDA guidance), which typically include requirements for sample size and testing methodology.
The data provenance is not explicitly stated in terms of country of origin of the data, but the testing appears to have been conducted based on international standards (ISO, ASTM, OECD) and a Korean FDA (KFDA) guidance, suggesting either international or Korean testing laboratories. The KFDA guidance implies the reporting entity and potentially the data origin is from Korea. The tests are prospective in the sense that they were conducted specifically for this submission.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. This is a material testing study, not an AI/ML device requiring clinical expert ground truth for interpretation.
4. Adjudication method for the test set
Not applicable. This is a material testing study.
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 testing study.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a material testing study.
7. The type of ground truth used
The "ground truth" for the material testing is based on objective measurements and compliance with established international and national standards for denture base resins (e.g., EN ISO 20795-1 for physical properties, ISO 10993 series and OECD guidelines for biocompatibility). The results are quantitative measurements or qualitative observations (e.g., visual inspection) evaluated against predefined specifications within the standards.
8. The sample size for the training set
Not applicable. This is a material testing study, 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 a material testing study.
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