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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 Braces on Demand Bracket is intended for use as a clear, plastic bracket system to provide orthodontic movement of natural teeth.

The proposed device is a 3D-printed bracket system that directly bonds to either primary teeth, permanent teeth, or mixed dentition to provide for orthodontic treatment for patients with malocclusions. Each bracket is 3D printed using a photopolymer denture resin. The Braces on Demand Bracket System has an integral hook design, which allows for attachment of accessories such as elastics or springs to assist the clinician in producing the desired tooth movement. The hook position on the Braces on Demand brackets can be on the mesial occlusal tiewing or the distal occlusal tiewing, similar to traditional orthodontic brackets. The application and removal of the Braces on Demand brackets are similar to other orthodontic brackets in that it requires orthodontic adhesive for bonding and standard orthodontic tools and techniques for de-bonding. The bonding surface of the bracket is a mechanical dovetail undercut design, allowing the bracket to mechanically retain the adhesive and bond to the facial surface of the tooth.

The provided document is a 510(k) Summary for the "Braces on Demand Bracket." It primarily focuses on demonstrating substantial equivalence to predicate devices based on various characteristics, manufacturing processes, and material properties. However, it does not contain information about acceptance criteria for device performance (such as accuracy, sensitivity, specificity, or other performance metrics typically associated with AI/ML devices), nor does it describe a study specifically designed to prove the device meets such criteria.

The information provided relates to testing for physical properties and biocompatibility, which are different from the performance metrics typically found in studies for AI/ML-driven devices.

Therefore, I cannot provide the requested information about acceptance criteria and a study that proves the device meets them from the given text.

Here's an breakdown of the requested information, indicating why it cannot be extracted:

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

   • Not found. The document discusses "Bond Strength and Hook Strength testing" and "Dimensional Analysis and Dimensional Stability Tests," stating that the device was found "substantially equivalent" to the predicate. However, it does not provide specific acceptance criteria values (e.g., "bond strength > X MPa") or specific reported performance values. It also doesn't mention any performance metrics related to orthodontic movement efficacy that would typically be assessed in a clinical study.

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

   • Not found. No information is given about sample sizes for any performance testing, nor about data provenance.

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 found. This section is relevant for studies involving human experts for ground truth assessment (e.g., image interpretation). This document does not describe such a study.

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

   • Not found. This is typically associated with ground truth establishment by multiple experts. Not applicable here.

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 found. The document explicitly states: "No animal or human testing are required for this product because it is composed of the same materials, is designed similarly, and is manufactured by method similar to the predicate device." Therefore, no MRMC study or study involving human readers with/without AI assistance was conducted or reported.

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

   • Not found. While the device involves software for design and manufacturing, the document does not describe a standalone performance study of an algorithm in the context of clinical decision-making or diagnosis. The software verification and validation are for the manufacturing process, not for clinical performance metrics.

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

   • Not found. Since performance studies with clinical outcomes are not described, there is no mention of ground truth types.

8. The sample size for the training set

   • Not found. The document does not describe a machine learning model that would require a training set.

9. How the ground truth for the training set was established

   • Not found. Not applicable.

In summary, the provided 510(k) Summary focuses on demonstrating substantial equivalence based on technical specifications, materials, manufacturing processes, and static physical property tests, rather than detailing clinical performance studies with specific acceptance criteria and outcome metrics that would be typical for an AI/ML powered device.

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Blue Sky Bio Computerized Orthodontic Bracket System is a software system intended for use as an aid in orthodontic treatment planning to correct malocclusions in orthodontic patients. For use by dental professionals trained in orthodontic treatment, including radiographic analyses and treatment planning. Blue Sky Bio Computerized Orthodontic Bracket System is intended for use with commercially available brackets currently used in standard orthodontic treatment. The end product is an indirect bonding tray for use by the dental professional to place multiple brackets at the same time.

The device consists of proprietary software that calculates the ideal position of the dental brackets based on the dental impressions and or 3D models supplied by the patient's orthodontist. Commercially available brackets are used as part of the system.

The Blue Sky Bio Computerized Orthodontic Bracket System is a software system intended to aid in orthodontic treatment planning. The information provided outlines the device's substantial equivalence to a predicate device, but does not provide specific acceptance criteria or a dedicated study proving performance against those criteria. Instead, it describes general testing for accuracy and software verification.

Here's a breakdown of the available information based on your questions:

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

Note: The document does not explicitly state numerical acceptance criteria (e.g., specific thresholds for deviation in bracket placement). The performance is reported as meeting general criteria or being confirmed.

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

The document does not specify the sample size used for the performance testing or software verification and validation. It only mentions "All samples met the performance criteria." The data provenance (country of origin, retrospective/prospective) is also not mentioned.

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)

This information is not provided. The method for establishing ground truth for the "accurate bracket placement" or "accuracy of data transfer" testing is not detailed in terms of expert involvement or qualifications.

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

This information is not provided. The document describes internal testing and software verification, but no external expert adjudication process is detailed.

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

There is no mention of a multi-reader multi-case (MRMC) comparative effectiveness study being performed. The device is a software system for treatment planning, not an AI for diagnostic interpretation by human readers.

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

The performance testing described ("Testing was conducted verifying that the treatment plan performed in the software resulted in accurate placement of the brackets") appears to be a standalone assessment of the software's ability to generate an accurate treatment plan. However, the system is always intended for use by dental professionals "as an aid in orthodontic treatment planning," implying that human-in-the-loop is part of its intended use. The "accuracy of data transfer" testing also seems to be a standalone evaluation of the software's data handling.

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

The document implies the ground truth for the "accuracy of data transfer" was established by comparison with scanned physical models and 3D models generated by the software, likely based on predetermined, ideal bracket positions. For the "accurate bracket placement," the ground truth was also based on the "treatment plan in Blue Sky Bio software," suggesting an internal consistency check against the planned outcome, which is initially informed by the clinician's detailed treatment plan. There's no mention of external validation against pathology or patient outcomes data.

8. The sample size for the training set

This information is not provided. The document focuses on performance testing and software verification, not on the details of algorithm training. Given it's a "Computerized Orthodontic Bracket System" and not explicitly termed an "AI" or "machine learning" system, it might be a rules-based or CAD-like system, rather than one requiring a large training dataset for a learning algorithm.

9. How the ground truth for the training set was established

This information is not provided, as details about a training set are absent.

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ORTHODONTIC PLASTIC BRACKETS AND ACCESSORIES are indicated for orthodontic movement of natural teeth.

The ORTHODONTIC PLASTIC BRACKETS are designed to move teeth to improve their alignment. The ORTHODONTIC PLASTIC BRACKETS are bonded to natural teeth by dental professionals to connect with orthodontic wires to cause tooth movement to a more preferred positions can be used with bracket caps. The ORTHODONTIC PLASTIC BRACKETS AND ACCESSORIES consist of plastic orthodontic brackets, bracket caps, and buttons. The bracket caps are designed as an accessory of the orthodontic brackets for holding the archwire in the bracket's slot. Bracket caps are placed on the labial/buccal side of the brackets. The plastic buttons are designed to move teeth to improve their alignment. The plastic buttons are bonded to natural teeth by dental professionals to connect with orthodontic wires to cause tooth movement to a more preferred position. The button design includes a round slot for attaching wires or other appliances.

This device, "ORTHODONTIC PLASTIC BRACKETS AND ACCESSORIES", is not an AI/ML device. Therefore, the requested information regarding acceptance criteria and study details for an AI/ML device is not applicable here.

The document describes an orthodontic product (brackets, bracket caps, and buttons) and its substantial equivalence to previously marketed predicate devices, focusing on material composition, mechanical properties, and intended use. The performance data section refers to standard material testing and conformity to ISO standards, not AI/ML algorithm performance.

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The Carriere Motion Clear Class II orthodontic appliance is intended to provide orthodontic movement and alignment of teeth during orthodontic treatment for Class II cases with symmetrical malocclusions and Class I cases with mesially positioned maxillary molars.

The Carriere Motion Clear Class II is a direct bond, esthetic, orthodontic appliance that attaches the maxillary canine or premolar to molar to provide a treatment solution for patients with malocclusions of primary, permanent or mixed dentition. The orthodontic appliance is a two-piece design comprised of an integrated polyethersulfone, a clear thermoplastic, anterior pad and rigid arm that connects to a 17-4 stainless steel posterior pad in a "ball and socket" relationship. The orthodontic appliance is intended to be used at the beginning of orthodontic treatment when there are no competing forces in the mouth. The device allows the distalization of the posterior segments.

The Carriere Motion Clear Class II corrects the posterior occlusion to a Class I platform first by rotating and uprighting the maxillary molars while distalizing the posterior segment, from canine or premolar to molars. The orthodontic appliance independently moves each posterior segment, from canine or premolar to molar, as a unit. The anterior pad includes an integrated hook which allows for the attachment of elastics to the lower molars. The posterior pad bonds to the facial surface of the teeth and is made of 17-4 stainless steel. The pad serves as the socket in the ball and socket relationship with the plastic arm. The ball and socket has built-in stops that allow the molars to move directly to their desired position and are intended to prevent any unwanted over rotation or tipping.

The Carriere Motion Clear Class II's application and removal is similar to that of a plastic orthodontic bracket. It requires orthodontic adhesive for bonding and standard orthodontic tools and techniques for debonding.

This document is a 510(k) premarket notification for a medical device, specifically an orthodontic appliance. It primarily focuses on demonstrating substantial equivalence to existing devices rather than detailing a study proving the device meets specific acceptance criteria through performance.

Therefore, the requested information regarding acceptance criteria and a study proving the device meets them, particularly in the context of an AI/human-in-the-loop diagnostic device, cannot be fully extracted from this document. This document describes a physical orthodontic appliance, not a diagnostic algorithm.

However, I can extract information related to performance testing that was conducted:

Here's an attempt to answer your questions based only on the provided text, acknowledging that many fields will be "Not Applicable" or "Not Provided" due to the nature of the document.

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

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

• Sample Size for Test Set: Not explicitly provided for biocompatibility or bond strength testing.
• Data Provenance: Not provided. The tests are described as conducted in accordance with FDA and ISO standards, but the location or whether the data was retrospective/prospective is not mentioned.

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. This document does not describe a study involving expert assessment or ground truth establishment for a diagnostic algorithm. The "ground truth" for the bond strength appears to be the measured force required for bonding/debonding, and for biocompatibility, it's compliance with standard biological evaluation tests.

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

• Not Applicable. No adjudication method is mentioned as this is not a diagnostic study requiring human expert review for establishing ground truth.

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. A MRMC comparative effectiveness study was not done. This document is for a physical orthodontic appliance, not an AI-assisted diagnostic device.

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

• No. A standalone performance study of an algorithm was not done. This document is for a physical orthodontic appliance.

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

• For Biocompatibility: Compliance with established biological evaluation standards (ISO 10993). The "ground truth" is that the material does not elicit adverse biological responses.
• For Bond Strength: Measured force in lbf/MPa. The "ground truth" refers to the quantified mechanical adhesion strength.

8. The sample size for the training set

• Not Applicable. This document describes a physical medical device, not an AI algorithm requiring a training set.

9. How the ground truth for the training set was established

• Not Applicable. No training set or associated ground truth establishment is relevant to this device submission.

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CompleClear appliances are intended for use as a clear, plastic bracket and archwire system to provide orthodontic movement of natural teeth.

CompleClear Plastic Orthodontic Bracket and Wire Appliance is an orthodontic appliance consisting of a polysulfone bracket with two separate components (tooth component and wire component) and an orthodontic wire pre-attached to the wire component of the bracket. The tooth and the wire components are capable of mechanically interlocking to form a detachable and reattachable bracket assembly. The tooth component of the bracket is cemented to the tooth, like regular orthodontic brackets. The wire components are pre-attached at specific positions along the orthodontic wire. The orthodontic wire is customized for each patient by creating various bends and rotations along the wire. This configuration of the customized wire, results in a specific position and orientation of the wire components of the bracket system along the customized wire. This customized orthodontic wire along with the series of pre-attached wire components constitutes the 'aligner'. When the wire components of the 'aligner' are engaged on to the corresponding tooth component cemented on the tooth, the orthodontic wire is activated like a spring. The tooth is gently moved to its desired position due to the elastic recoil of the wire.

The two component bracket assembly of the present device allows moment arms for mesiodistal rotation, labio-lingual inclination and mesio-distal angulations (tip) similar to conventional bracket-wire used in orthodontics.

The treatment uses a series of aligners, each incorporating a predefined amount to tooth movement toward the final desired end goal. The amount of tooth movement incorporated, the type of tooth movement incorporated and the final desired end goal are all determined and approved by the provider.

This document, a 510(k) summary for the CompleClear Plastic Orthodontic Bracket and Wire Appliance (K150830), does not contain information about acceptance criteria or a study proving the device meets specific performance metrics in the format requested.

Instead, the document focuses on demonstrating substantial equivalence to predicate devices (K110796 and K140807) based on indications for use, materials, aesthetic features, mode of use, physical properties, application, and manufacturing methods.

Here's what can be extracted from the document regarding testing, though it doesn't align with the detailed "acceptance criteria and study" structure you've requested for AI/software devices:

1. Acceptance Criteria and Reported Device Performance (as interpreted from the mechanical testing)

2. Sample size used for the test set and the data provenance:

• The document does not specify general sample sizes for the mechanical tests. For the shear bond strength testing, it refers to "both CompleClear and Ortho Specialties' brackets" implying a comparison was made but no specific number of samples is given.
• Data provenance is not mentioned (e.g., country of origin, retrospective/prospective).

3. Number of experts used to establish the ground truth for the test set and qualifications of those experts:

• Not applicable as this is a physical device and the testing described is mechanical, not involving human expert assessment for ground truth.

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

• Not applicable. This type of testing does not involve adjudication by experts.

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/software device and no MRMC study was performed or described.

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

• Not applicable. This is not an AI/software device.

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

• For mechanical tests, the "ground truth" would be established by the physical properties of the materials and the design of the device, measured through standard engineering and materials science testing methodologies. For shear bond strength, it was a direct measurement comparison.

8. The sample size for the training set:

• Not applicable. This is not an AI/software device.

9. How the ground truth for the training set was established:

• Not applicable. This is not an AI/software device.

In summary, this document is a 510(k) premarket notification for a physical orthodontic device. The "proof" of meeting acceptance criteria is primarily demonstrated through mechanical testing to show equivalency to legally marketed predicate devices, not through studies involving AI performance or human reader analysis as typically required for AI/ML-based medical devices.

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eXceed Computerized Precision Bracket Placement Solution is a software system intended for use as an aid in orthodontic treatment planning to correct Malocclusions in Orthodontic Patients. For use by dental professionals trained in orthodontic treatment, including radiographic analyses and treatment planning. eXceed Computerized Precision Bracket Placement Solution is intended for use with commercially available brackets currently used in standard orthodontic treatment. The end product is an indirect bonding tray for use by the Dental professional to place multiple brackets at the same time.

The device consists of proprietary software that calculates the ideal position of the dental brackets based on the dental impressions and or 3D models supplied by the patients Orthodontist. Commercially available brackets are used as part of the system. Using the images provided by the Dental Professional, the software creates a 3D model and identifies the ideal placement of the brackets. The file is sent to the Dental Professional for review and approval. The Dental Professional may adjust the final position of the bracket if desired. A 3D model is printed, and the brackets are placed on the model in the prescribed location, approved by the Orthodontist. An indirect bonding tray is fabricated with the brackets in place. The tray and brackets are sent to the Dental professional. The Dental Professional places the indirect tray using their chosen commercially available bracket adhesive.

The provided text describes the "eXceed Computerized Precision Bracket Placement Solution" and its substantial equivalence to a predicate device, Ortho CADiQ. However, the document does not contain details about specific acceptance criteria, a detailed study that proves the device meets specific performance metrics, or the other requested information such as sample sizes, expert qualifications, or adjudication methods for performance studies.

The text focuses on demonstrating substantial equivalence based on intended use, technological characteristics, and principles of operation, rather than providing granular performance data from a specific study against predefined acceptance criteria.

The only mention of "Performance Data" is:
"The software is verified and validated by the digital model generated, matching the 3D model and bracket placement locations prescribed and approved by the Orthodontist."

This statement is very general and does not provide quantifiable acceptance criteria or detailed study results. The document notes: "As confirmed in comparative testing, the visual guidance system used by the subject device is accurate, in the sense that it corresponds exactly with the virtual coordinates dictated by the approved placement plan, thus enabling the technician to place the brackets on the working model precisely according to that plan." Again, this is a general statement without specific metrics or details of the comparative testing.

Therefore, many of the requested details cannot be extracted from the provided text.

Here's an attempt to answer the questions based only on the available information:

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

   • Acceptance Criteria: Not explicitly stated in measurable terms in the provided document. The general criteria seem to be that the visual guidance system is "accurate" and "corresponds exactly with the virtual coordinates dictated by the approved placement plan."
   • Reported Device Performance: "the visual guidance system used by the subject device is accurate, in the sense that it corresponds exactly with the virtual coordinates dictated by the approved placement plan, thus enabling the technician to place the brackets on the working model precisely according to that plan."

   Acceptance Criteria (inferred)	Reported Device Performance
   Visual guidance system for bracket placement is accurate and corresponds exactly with approved virtual placement plan coordinates.	"the visual guidance system used by the subject device is accurate, in the sense that it corresponds exactly with the virtual coordinates dictated by the approved placement plan, thus enabling the technician to place the brackets on the working model precisely according to that plan."

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

   • Sample Size: Not specified.
   • Data Provenance: Not specified.

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 specified. The ground truth seems to be "the approved placement plan" from the orthodontist.

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

   • Not specified.

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 MRMC study is mentioned. The document describes "comparative testing" of the visual guidance system's accuracy, but not a study of human readers’ improvement with AI assistance.

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

   • The "performance data" describes the software generating a digital model and bracket placement, which is then verified against the orthodontist's prescription. This implies a standalone assessment of the software's output matching the desired plan. However, the exact methodology and metrics of this "verification and validation" are not detailed.

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

   • The ground truth for the device's accuracy appears to be the "approved placement plan" or "virtual coordinates dictated by the approved placement plan" supplied and approved by the "Dental Professional" or "Orthodontist."

8. The sample size for the training set

   • Not specified. (This device is described as software that calculates ideal positions based on dental impressions/3D models and an orthodontist's plan, rather than a deep learning AI model that would typically have a specific training set size).

9. How the ground truth for the training set was established

   • Not applicable/Not specified. The document does not describe a machine learning model that would require a ground-truthed training set in the conventional sense. The "ground truth" (the approved placement plan) is established by the dental professional for each case being processed by the system.

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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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Insignia Digicast is a computer aided system intended for use as an aid in orthodontic diagnostics for use by dental professionals trained in orthodontic treatment including radiographic analyses and diagnostics.

Insignia Digicast is a software product and service that creates digital models of patients' teeth, which are used primarily to record the status of a patients' dentition prior to treatment. Clinicians may also use the digital model to support their diagnosis. The Insignia Digicast system scans a traditional impression, processes the scan, and electronically delivers a digital study model to the dental professional. The dental professional may view, measure, and analyze the Insignin Digicast three dimensional viewer software. The main analysis tools include TJ Moyers, Bolton analyses, ABO scoring, and Arch and Overbite/Overjet measurements. There are no accessories or patient contacting components of Insignia Digicast.

The provided document describes the Insignia Digicast, a software product and service that creates digital models of patients' teeth for orthodontic diagnostics.

Here's an analysis of the acceptance criteria and study data:

1. Table of Acceptance Criteria and Reported Device Performance:

   The document does not explicitly state numerical acceptance criteria (e.g., specific accuracy thresholds for measurements). Instead, it relies on demonstrating substantial equivalence to predicate devices (OrthoCAD iQ and Lava Digital Models) through qualitative comparisons of features and mode of use, and quantitative comparisons of measurement accuracy.

   Feature/Measurement	Acceptance Criteria (Implied by Substantial Equivalence)	Insignia Digicast Performance (Reported)
   Teeth Width	Functionally equivalent to predicates	Bench tested, successfully validated
   Space	Functionally equivalent to predicates	Bench tested, successfully validated
   T-J Moyers Analysis	Functionally equivalent to predicates	Bench tested, successfully validated
   Bolton Analysis	Functionally equivalent to predicates	Bench tested, successfully validated
   Arch Measurements	Functionally equivalent to predicates	Bench tested, successfully validated
   Overbite/Overjet	Functionally equivalent to predicates	Bench tested, successfully validated
   Overall Performance	Substantially equivalent to predicate devices	Deemed substantially equivalent

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

   • Sample Size: Not specified in the provided document. The document states "data from bench testing" was used, but does not quantify the number of cases or models tested.
   • Data Provenance: Not explicitly stated. Given it's bench testing, it's likely synthetic data, cadaver models, or a collection of patient impressions, but the origin (e.g., country) is not mentioned. It is a retrospective evaluation against existing (presumably traditional) measurements.

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

   • Not specified. The document indicates that bench testing was used to "evaluate the performance characteristics... compared to the predicate device." It doesn't mention expert involvement in establishing a separate ground truth for the test set beyond the comparisons made with the predicate device's established performance.

4. Adjudication Method for the Test Set:

   • Not specified. This information is typically relevant for human-reader evaluations, which did not occur for this device.

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 MRMC comparative effectiveness study was done. The document explicitly states: "Clinical testing has not been conducted on this product."

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

   • Yes, a standalone evaluation was performed. The "Non-Clinical Performance Data" section describes "bench testing" to evaluate the "performance characteristics of Insignia Digicast," which is an algorithm-only assessment. The software was "successfully validated to confirm the performance of the device."

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

   • The "ground truth" for the non-clinical performance evaluation was based on comparisons to the predicate device, OrthoCAD iQ, for characteristics such as teeth width, space, and various analyses (T-J Moyers, Bolton, Arch, Overbite/Overjet). This implies the predicate device's measurements served as the reference or accepted standard.

8. The sample size for the training set:

   • Not specified. The document does not provide any details regarding the training data or its size.

9. How the ground truth for the training set was established:

   • Not specified. Since no information on the training set is provided, the method for establishing its ground truth is also unknown.

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Insignia with iTero is a treatment planning software and orthodontic appliance system used to correct malocclusions in orthodontic patients, using appliances individualized for the orthodontic patient. The Insignia Orthodontic System is compatible with the iTero scanner.

The Insignia software creates a computer model of the patient's dentition based on a stone model, iTero scan file or impression of the patient's dentition. The iTero scanner produces a digital scan of a patient's tooth data as an alternative to the physical dental impressions. Insignia operators and the orthodontist use this computer model to determine the placement and/or modification of dental brackets to achieve the intended repositioning of the teeth. Ormco then manufactures foam bracket placement jigs to position the brackets on the patient's teeth in specific positions prescribed by the orthodontist. The orthodontist uses the foam jigs to place and secure the brackets with a commercially-available dental adhesive. Insignia with iTero consists of the following components and accessories: 1) Proprietary software that calculates the position of dental brackets based on the dental impressions and treatment plan supplied by the patient's orthodontist. 2) Commercially-available metal, plastic, or ceramic brackets and/or individually modified metal brackets. 3) Patient-specific foam bracket placement jigs to affix the brackets in position. 4) Either commercially-available or patient-specific shaped traditional archwires. The device does not include the adhesive that affixes the brackets to the teeth.

The provided text describes the "Insignia with iTero" device, an orthodontic treatment planning software and appliance system. It claims substantial equivalence to two predicate devices: "Insignia (K121524)" and "Biomet 3i Using Cadent iTero Scanner (K102209)".

Here's an analysis of the acceptance criteria and study information provided:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state quantitative acceptance criteria in a typical pass/fail format with specific thresholds. Instead, it relies on the concept of "substantial equivalence" to predicate devices. The primary performance aspect highlighted is the accuracy of the digital impression file generated from the iTero scanner.

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

• Sample Size: Not specified. The document only mentions "Accuracy testing of the digital impression file..." without providing the number of scans or measurements included in this testing.
• Data Provenance: Not specified. It's unclear if the testing was retrospective or prospective, or the country of origin of the data.

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

• Not specified. The document simply mentions "Accuracy testing" without detailing how the ground truth for this testing was established or if experts were involved in its determination.

4. Adjudication Method for the Test Set:

• Not specified. There's no mention of any adjudication method (e.g., 2+1, 3+1, none) for the accuracy testing.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance:

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly mentioned or performed. The device is not presented as an AI-assisted diagnostic tool for human readers but rather as a treatment planning software and appliance system. The evaluation focused on the accuracy of the digital impression and substantial equivalence to existing devices, not on human reader improvement with AI.

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

• Yes, implicitly. The "Accuracy testing of the digital impression file generated from the iTero scanner" appears to be a standalone performance evaluation of the scanner component, which produces a digital output (algorithm only) as an alternative to physical impressions. The software then uses this digital model for treatment planning. The "Insignia software" itself also operates in a standalone manner to calculate bracket positions.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.):

• Not explicitly defined. For the "accuracy testing of the digital impression file," the ground truth likely involved a comparison against a highly accurate reference measurement of the dentition. This could be a physical impression measured with high-precision instruments or a different, highly accurate 3D scanning method considered the gold standard. However, the document does not specify the exact nature of this ground truth.

8. The Sample Size for the Training Set:

• Not applicable/not specified. The document describes a "proprietary software that calculates the position of dental brackets" and the "iTero scanner" which produces digital scans. While these systems likely have internal algorithms that were developed and potentially "trained," the document does not discuss a training set in the context of machine learning or AI models in the modern sense. The focus is on the output accuracy of the system's components.

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

• Not applicable/not specified. As with the training set itself, the document does not provide details on how ground truth would have been established for any internal training or development of the software or scanner's algorithms.

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