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The intended use of composite brackets and buttons is to be bonded to the teeth to provide orthodontic movement of natural teeth.

The main indication for use of orthodontic brackets and buttons is a malocclusion, such as misaligned teeth, overcrowding, spacing issues, and bite irregularities.

Composite orthodontic brackets and buttons present a clear and aesthetically pleasing choice for orthodontic patients undergoing orthodontic treatment. The Composite Bracket and Button is engineered to offer simple and aesthetic devices that address both minor and complex misalignments in patients.

Composite orthodontic brackets and buttons are classified as Class II medical devices. In accordance with ISO 10993-1:2018, based on the nature of body contact, orthodontic brackets and buttons are categorized as having mucosal contact, as they are affixed to the teeth and maintain prolonged contact with the oral mucosa. Furthermore, the contact duration is categorized as "permanent exposure" (=more than thirty days), as brackets and buttons are expected to remain in place for extended periods during orthodontic treatment.

Utilized by orthodontic professionals, these brackets and buttons serve as integral components - together with adhesives, wires, bands, elastics and other attachments in the alignment and correction of dental malocclusions and misalignments. The duration of the treatment depends on the degree of misalignment and is between 6 months and a maximum of 2,5 years.

Brackets and buttons are strategically placed and affixed to the surface of the teeth using dental adhesive. This bonding process ensures that the brackets and buttons remain securely attached to the teeth throughout the orthodontic treatment. Then Orthodontic arch wires are pushed into the slot of the bracket. The slot acts as an aid to hold and guide the orthodontic wires that - in conjunction with bands and other orthodontic accessories - exert gentle forces to the teeth, gradually moving them into their desired position. These direct and indirect orthodontic bonding techniques with orthodontic adhesives is thoroughly documented in orthodontic literature. These additional products required for orthodontic treatment are chosen by the orthodontist as required and are hence not part of this 510(k) application. The removal of the brackets/buttons follow standard procedures that do not require additional training.

Composite Orthodontic Products are only to be used by Orthodontists/Dentists. As educated specialists they know exactly how to use brackets and buttons. They have received training in order to analyse and decide with which other products they are best compatible (wires, adhesives, elastics and instruments). This 510(k) application is only for composite orthodontic brackets and buttons.

It's important to note that the provided document is an FDA 510(k) clearance letter for "Composite Orthodontic Brackets and Buttons" (ECC Premium Line). While it confirms substantial equivalence to a predicate device, it does not include detailed study results in the format requested, particularly for acceptance criteria and specific performance metrics for AI/ML devices. This document describes a physical medical device, not an AI/ML software device.

Therefore, many of the requested fields, especially those related to AI/ML specific studies (like MRMC, standalone performance, training set details, and ground truth for AI), cannot be extracted from this document, as they are not applicable to the device described.

However, I can provide information based on the presented text for the relevant sections:

1. Table of Acceptance Criteria and Reported Device Performance

The document states that a series of bench tests were completed to show that the medical devices function as intended and meet specified performance characteristics. It also states they withstand stresses and do not pose a risk. However, precise numerical acceptance criteria and their corresponding reported performance values are not detailed in this 510(k) summary. The document generally asserts that the device "meets the specified performance characteristics" and "functions as intended."

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

The document is for a physical medical device (orthodontic brackets and buttons), not a software/AI device that typically uses "test sets" of data. The "tests" performed are bench tests on the physical product. The sample sizes for these bench tests are not specified in the provided text. The concept of "data provenance" (country of origin, retrospective/prospective) is not applicable here as these are laboratory bench tests, not data-driven studies.

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

This question is not applicable as the device is a physical medical device. Ground truth, in the context of expert consensus, refers to the labeling of medical images or data by experts, typically for AI/ML model training or evaluation. The performance evaluation here is based on physical material properties and mechanical function through bench testing.

4. Adjudication Method for the Test Set

This question is not applicable as the device is a physical medical device. Adjudication methods (like 2+1, 3+1) are used for resolving disagreements among human readers/experts when establishing ground truth for AI/ML datasets.

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 question is not applicable. An MRMC study is relevant for evaluating the clinical effectiveness of AI/ML-assisted diagnostic or decision-support systems by comparing human performance with and without AI assistance. This document describes a physical orthodontic device; therefore, no such study was conducted or reported.

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

This question is not applicable. Standalone performance refers to the evaluation of an AI/ML algorithm's performance independent of human intervention. Since this is a physical medical device, there is no algorithm or AI component to evaluate in a standalone manner.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

For the bench tests conducted, the "ground truth" implicitly refers to the engineering specifications and standards (e.g., ISO 27020:2019 for dimensional tests) against which the physical device's performance is measured. There is no biological "ground truth" like pathology or outcomes data generated for these non-clinical tests.

8. The Sample Size for the Training Set

This question is not applicable. A "training set" is used for developing AI/ML models. This device is a physical product, not an AI/ML software.

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

This question is not applicable. As there is no AI/ML model, there is no training set and thus no ground truth for a training set.

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The Composite Brackets are intended for use as a clear, plastic bracket system to provide orthodontic movement of natural teeth.

Composite brackets provide a clear, aesthetic option for patients undergoing orthodontic treatment. The Composite Bracket system is designed to provide simple, aesthetic bonded brackets to correct minor to complicated mal-alignments in patients with permanent dentition (second molars) or mixed dentition using current orthodontic diagnosing techniques with orthodontic arch wires. The system consists of a series of clear, plastic brackets that conform to each tooth and its anatomy and adheres with a bracket base bearing a mechanical retention surface. They are provided with or without a metal archwire slot. Additional accessories to the brackets, depending on the dental professionals' technique, mav include small hooks for the use of elastics and auxiliary arch wire tubes. Each bracket applies incremental, progressive force to reposition teeth to achieve ideal alignment, as prescribed by the treating dental practitioner. The composite brackets are bonded to the patient's teeth by traditional orthodontic direct and indirect bonding techniques using Orthodontic adhesives.

The provided text describes a 510(k) premarket notification for "Composite Brackets" by Ortho Specialties, Incorporated. This document focuses on demonstrating substantial equivalence to predicate devices, rather than an AI/ML-driven device with acceptance criteria and a study proving performance against those criteria in the typical sense of AI model evaluation.

Therefore, many of the requested sections about AI study specifics cannot be answered from the provided text. I will extract the information that is present.

This document is a 510(k) premarket notification for a medical device called "Composite Brackets." It is a regulatory filing to demonstrate that the new device is substantially equivalent to legally marketed predicate devices, not a study evaluating the performance of an AI/ML algorithm. As such, the typical acceptance criteria and study design for AI models (e.g., sensitivity, specificity, ROC curves, human reader improvement) are not applicable here.

However, I can extract information related to the device's characteristics and the biological evaluation studies performed for regulatory clearance.

1. A table of acceptance criteria and the reported device performance

Since this is not an AI/ML algorithm evaluation, there are no "acceptance criteria" in the traditional sense of performance metrics like sensitivity or specificity. Instead, the "acceptance criteria" are implied by the biological safety tests and the claim of substantial equivalence to predicate devices based on technological characteristics.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Cytotoxicity Test: The ISO 10993-5 Elution Method involves in vitro mammalian cell culture. The sample size refers to the number of cell cultures or replicates tested, which is not specified but follows ISO guidelines. Data provenance is implied by adherence to ISO standards.
• Oral Mucosal Irritation Test: Performed in hamsters. The number of hamsters (sample size) is not specified but follows ISO 10993-10 guidelines. Data provenance is implied by adherence to ISO standards.
• Technological Equivalence Comparison: This is a comparison of device characteristics against predicate devices, not a test with a "test set" of patient data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable to this type of device and study. The "ground truth" for the biological evaluations is determined by the standardized test methods outlined in the ISO standards. The evaluation of technological equivalence is a comparison of product specifications by regulatory professionals and engineers.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

Not applicable. The biological tests follow standardized laboratory protocols. The comparison to predicate devices is a regulatory assessment.

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 document is for an orthodontic bracket, not an AI-assisted diagnostic tool.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done

Not applicable. This is not an algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

• Cytotoxicity: The "ground truth" is defined by the cellular response to the eluted materials as per ISO 10993-5 (e.g., cell viability, morphological changes indicating toxicity).
• Oral Mucosal Irritation: The "ground truth" is based on observed inflammatory responses in the hamster oral mucosa as per ISO 10993-10 (e.g., erythema, edema).
• Technological Equivalence: The "ground truth" for comparison is the documented characteristics and performance of the legally marketed predicate devices.

8. The sample size for the training set

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

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