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Reparative cement for endodontic complications.

1. Furcation or root perforation treatment via canal;
2. Furcation or root perforation treatment via surgical;
3. Internal reabsorption treatment via canal or surgical;
4. External reabsorption treatment;
5. Retrofilling in parendodontic surgery;
6. Direct and indirect pulp capping;
7. Apexification;
8. Apexogenesis and Pulpotomy.

BIO-C REPAIR is a ready-to-use bioceramic MTA-based paste developed for permanent root canal repair and surgical applications. The product is a single paste provided in a syringe with disposable tips to be applied to the affected area of the root canal system. BIO-C REPAIR is an insoluble and radiopaque material which requires the presence of water to set and harden.

The provided document is a 510(k) summary for the dental device BIO-C REPAIR. This document primarily focuses on establishing substantial equivalence to predicate devices based on comparisons of indications for use, technological characteristics, and performance data from bench testing. It does not describe a clinical study directly proving the device meets specific acceptance criteria in a clinical setting in the way an AI/ML device would.

However, based on the provided text, we can infer the acceptance criteria for various physical-chemical properties and present the reported device performance. No information is available regarding AI/ML specific criteria such as sensitivity, specificity, or accuracy, as this is a dental material, not an AI/ML diagnostic tool.

Here's the information extracted and formatted as requested:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly derived from the ISO 6876:2012 standard for dental root canal sealing materials and the properties of the predicate devices. The "reported device performance" refers to BIO-C REPAIR's measured characteristics.

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

The document does not specify a "test set" in the context of human data or AI/ML model evaluation. The performance data is derived from bench testing of the material itself. Therefore, sample sizes for the bench tests would refer to the number of material samples tested for properties like setting time, pH, radiopacity, and solubility. This information is not provided in the document.

Data provenance: The testing was performed by the manufacturer, Angelus Indústria de Produtos Odontológicos S/A, based in Londrina, Brazil. The data is from laboratory (bench) testing, not clinical. It is retrospective in the sense that the tests were completed before the 510(k) submission.

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

This is not applicable as the device is a dental material, not an AI/ML diagnostic device requiring expert interpretation for ground truth establishment. The "ground truth" for the material's properties is established through adherence to international standards (ISO 6876:2012) and comparison to predicate devices, not expert consensus on medical images or clinical outcomes.

4. Adjudication Method for the Test Set

This is not applicable as there is no "test set" requiring adjudication in the context of human expert review for a dental material. The performance measurements are objective 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 is not applicable. The device is a dental filling material, not an AI-assisted diagnostic tool.

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

This is not applicable. The device does not involve an algorithm or AI.

7. The Type of Ground Truth Used

The "ground truth" for the properties of BIO-C REPAIR is established by objective laboratory measurements according to an international standard (ISO 6876:2012) and comparison to the characteristics reported for legally marketed predicate devices. This is analogous to "physical and chemical properties" ground truth.

8. The Sample Size for the Training Set

This is not applicable as the device is not an AI/ML model and therefore does not have a "training set."

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

This is not applicable. There is no training set for this type of device.

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