Search Results

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.

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.

Ask a specific question about this device