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510(k) Data Aggregation
(125 days)
Total-Etch Dualbond is indicated for:
- Bonding resin-based materials (especially dual-cure composite / compomer . materials) to tooth structure (dentin and enamel)
- Treatment of hypersensitive teeth .
Total-Etch Bond is indicated for:
- Bonding resin-based materials (especially light-cure composite / compomer . materials) to tooth structure (dentin and enamel)
- Treatment of hypersensitive teeth .
The Total Etch Bonding Agent consists of two dental bonding agent formulations for use in dual- and light-cured bonding procedures:
Total-Etch Bonding Agent for Dual-Cured Resin-Based Materials (Total-Etch Dualbond) Total-Etch Bonding Agent for Light-Cured Resin-Based Materials (Total-Etch Bond)
This document is a 510(k) summary for a dental bonding agent, not a study report. Therefore, it does not contain the detailed information requested regarding acceptance criteria and a study proving device performance in the context of AI/device performance metrics.
Here's why and what information can be extracted:
The document is a submission to the FDA for market clearance, asserting "substantial equivalence" to existing predicate devices. It focuses on chemical composition and physical performance data to establish this equivalence, rather than a clinical trial demonstrating specific performance metrics against pre-defined acceptance criteria in the way a diagnostic algorithm or device might.
However, I can provide a structure based on what you would expect to see in such a study, and indicate what is missing from this document.
Acceptance Criteria and Study for Total Etch Bonding Agent
Missing Information: The provided 510(k) summary does not contain the detailed acceptance criteria or a comprehensive study plan/results in the format requested for evaluating device performance against such criteria. The document states "This submission contains safety and performance information (chemical composition and physical performance data) sufficient to establish substantial equivalence in comparison to the devices listed above," but it does not elaborate on specific performance metrics, and certainly not in the context of AI or human reader improvement.
Therefore, the following tables and sections will indicate where the requested information would typically be if this were a performance study report, and highlight that this specific document does not provide it.
1. Table of Acceptance Criteria and Reported Device Performance
As this document is a 510(k) submission focused on "substantial equivalence" rather than a clinical or performance study report with explicit acceptance criteria for this specific device's novel performance, it does not provide a table like the one requested below. Performance is implied through comparison to predicates regarding chemical composition and physical properties.
| Performance Metric (Hypothetical, for a dental bonding agent) | Acceptance Criteria (Hypothetical) | Reported Device Performance (Not provided in this document) |
|---|---|---|
| Bond Strength (e.g., Shear Bond Strength to Enamel) | ≥ X MPa (e.g., comparable to predicate devices) | (Not reported) |
| Bond Strength (e.g., Shear Bond Strength to Dentin) | ≥ Y MPa (e.g., comparable to predicate devices) | (Not reported) |
| Microleakage (e.g., Dye penetration score) | ≤ Z (e.g., comparable to predicate devices) | (Not reported) |
| Working Time | A ± B seconds | (Not reported) |
| Curing Time | C ± D seconds | (Not reported) |
| Cytotoxicity (e.g., ISO 10993) | Non-cytotoxic | (Implied to be non-cytotoxic based on substantial equivalence) |
2. Sample Size Used for the Test Set and the Data Provenance
- Sample Size for Test Set: Not specified. The document refers to "physical performance data" but does not detail the size of any test cohorts for specific performance metrics.
- Data Provenance: Not specified. Given it's a dental product, any physical performance data would likely involve in-vitro studies conducted in a lab setting, possibly with extracted human teeth or artificial substrates. The country of origin for such data is not mentioned.
- Retrospective or Prospective: Not applicable in the context of this 510(k) document, as it doesn't describe a clinical trial or a dataset analysis in the way these terms are typically used for AI or diagnostic device studies. Any "performance data" would likely be from lab testing (in-vitro), not human subject trials.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
- Not Applicable. This document describes a dental bonding agent, not a diagnostic device that requires expert interpretation for ground truth establishment. "Ground truth" in this context would refer to objective physical or chemical measurements (e.g., bond strength measured by a machine, microleakage visualized by microscopy).
4. Adjudication Method for the Test Set
- Not Applicable. As there are no human experts establishing a "ground truth" through interpretation, no adjudication method would be required.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size of AI vs. Without AI Assistance
- Not Applicable. This device is a dental bonding agent, not an AI-powered diagnostic tool. Therefore, an MRMC study and analysis of AI assistance is completely irrelevant to this submission.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
- Not Applicable. This device is a dental bonding agent, not an algorithm.
7. The Type of Ground Truth Used
- For physical and chemical properties: The "ground truth" would be established through objective, standardized laboratory measurements (e.g., spectrophotometry for chemical composition, tensile/shear testing machines for bond strength, microscopy for microleakage).
- For biocompatibility: "Ground truth" would be established through in-vitro cytotoxicity assays and potentially in-vivo animal studies if full biocompatibility testing was required beyond similarity to predicate devices.
- The document implies that these types of tests were conducted to demonstrate substantial equivalence, but specific reports are not provided.
8. The Sample Size for the Training Set
- Not Applicable. This device is not an AI algorithm, so there is no "training set."
9. How the Ground Truth for the Training Set Was Established
- Not Applicable. There is no training set for an AI algorithm in this context.
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