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OptiBond SE is a two-component self-etch universal adhesive system designed to be used for all direct and indirect applications including, but not limited to, the following: Direct Applications - Light-cured composite and compomer restorations - Composite/ceramic/metal repairs - Cavity sealing for amalgam restorations - Sealing of hypersensitive and/or exposed root surfaces - Core build-ups (self-cured, light-cured or dual-cured) Indirect applications - Veneers - Porcelain, composite, and metal-based (including zirconia-based and aluminabased) inlays, onlays, crowns, bridges - Endodontic posts - Cavity sealing as a pretreatment for indirect restorations

Device Description

OptiBond SE is a two-component self-etch universal adhesive system including a self-etch PRIMER and a universal ADHESIVE. The self-etch primer provides effective etching to uncut enamel and dentin, without the need for a separate phosphoric acid etch, thus simplifying the bonding procedure. The adhesive component is 15% filled with 0.4 micron barium glass to help reinforce bond strength. The material's chemistry allows for compatibility with all self-cure or dual-cure resin cements and core build-up materials. Dentists can therefore utilize OptiBond SE for their direct and indirect procedures without the need for a secondary bonding system.

AI/ML Overview

The provided text describes OptiBond SE, a dental adhesive, and states its substantial equivalence to a predicate device based on biocompatibility and bench testing. However, it does not include information about acceptance criteria or a study that evaluates its performance against those criteria in a manner typically associated with AI/ML device evaluations. The document is a 510(k) summary for a medical device (a resin tooth bonding agent), which means the "study" referred to is about demonstrating substantial equivalence through specific performance characteristics.

Therefore, many of the requested fields regarding AI/ML study specifics (like sample size for test/training sets, experts for ground truth, adjudication methods, MRMC studies, standalone performance, and effect size of human reader improvement) are not applicable to this document.

Here's the information that can be extracted from the provided text, structured to address your request as much as possible for a non-AI/ML device:

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria (Implied by Substantial Equivalence)	Reported Device Performance
Biocompatibility	A biocompatibility study was completed, demonstrating the material is safe for its intended use. (Implied to meet safety standards for dental materials).
Direct Bonding Strength to Various Materials	Bench testing evaluated direct bonding strength to various dental materials including dentin, enamel, composite, porcelain, gold, and PFM. (Implied to be comparable or superior to the predicate device, OptiBond All-In-One, to establish substantial equivalence).
Indirect Bonding Strength to Various Materials	Bench testing evaluated indirect bonding strength to various dental materials including dentin, enamel, composite, porcelain, gold, and PFM. (Implied to be comparable or superior to the predicate device, OptiBond All-In-One, to establish substantial equivalence).
Compatibility with Curing Mechanisms	Material's chemistry allows for compatibility with all self-cure or dual-cure resin cements and core build-up materials. (Implied to perform effectively with these, no direct acceptance criteria or comparative performance data against predicate specifically on this point are detailed in the provided text, but it's a stated characteristic).
Intended Use Applications	Designed for all direct and indirect applications (listed in detail above). (Implies the device performs adequately for these stated uses, presumably comparable to the predicate).

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

The document does not specify a "test set" in the context of an AI/ML study. It refers to "bench testing" to evaluate performance characteristics.

Sample Size: Not specified for the bench tests.
Data Provenance: The nature of bench testing implies lab-generated data. No country of origin is mentioned for the data, but the submission is from a US company for FDA approval. The testing would be considered prospective in the sense that it was conducted specifically for this submission.

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

Not applicable. "Ground truth" in this context would refer to the accurate measurement and assessment of bonding strength and biocompatibility in a lab setting, not expert interpretation of diagnostic images or clinical data. No experts are mentioned in this capacity.

4. Adjudication Method for the Test Set

Not applicable. There is no "adjudication" process described for the results of the bench testing. Lab tests typically rely on standardized protocols and quantitative 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 not an AI/ML device, and no MRMC study was conducted.

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

Not applicable. This is not an AI/ML device.

7. The Type of Ground Truth Used

For the bench testing and biocompatibility study, the "ground truth" would be established by:

Quantitative measurements: Direct and indirect bonding strengths are measured values (e.g., in MPa).
Biocompatibility standards: Adherence to established biological safety standards for medical devices, which typically involve specific in vitro and in vivo tests to assess cytotoxicity, irritation, sensitization, genotoxicity, etc.

8. The Sample Size for the Training Set

Not applicable. This is not an AI/ML device.

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

Not applicable. This is not an AI/ML device.

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