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The Invisalign® System is intended for the orthodontic treatment of malocclusion in patients with primary, mixed (primary and permanent), or permanent dentition. The optional mandibular advancement feature(s) are indicated for the treatment of skeletal malocclusion in patients with mixed or permanent dentition.

The subject device Invisalign® System is a proposed modification to add integrated button, an optional feature into the predicate device, Invisalign System (K241412). The Invisalign® System consists of removable orthodontic appliances (aligners) and proprietary 3D treatment planning software. This submission adds an optional integrated button to aligners which is similar to the predicate device's precision cut feature that allows doctors to add orthodontic accessories such as elastics during treatment. The 3D treatment planning software allows the visualization and button placement on the aligners. The doctor still approves the treatment plan prior manufacturing, which is the same as that in the predicate.

Like the predicate device, the Invisalign® System consists of a series of doctor prescribed, customized, thin, clear plastic aligners that gently move the patient's teeth in small increments from their original state to a more optimal, treated state to address malocclusion. The optional MAF positions patients jaw forward to address skeletal malocclusion. The system is used in patients with primary, mixed, and permanent dentition. There are no changes introduced to the user workflow other than the addition of optional integrated button feature.

This FDA 510(k) clearance letter describes a modification to an existing medical device, the Invisalign System. It does not contain the detailed information typically found in a study report for proving device performance against acceptance criteria, especially for AI/software devices. The provided text primarily focuses on regulatory approval based on "substantial equivalence" to a predicate device for an additional physical feature (integrated button) rather than a software-driven performance claim that would necessitate a rigorous clinical or performance study with acceptance criteria and specific test methodologies for AI.

Therefore, many of the requested elements for describing a study proving the device meets acceptance criteria cannot be extracted from this document because such a study, in the context of an AI/software device, does not appear to be the primary focus of this specific 510(k) submission as presented. The submission is for a physical device modification, not a new AI algorithm.

However, based on the information provided, here's what can be inferred or stated that such an approval did not involve:

Summary of Device Performance Study Based on Provided Text:

This 510(k) clearance letter for the Invisalign System (K252380) primarily concerns a modification to an existing device, specifically the addition of an "integrated button" feature to the aligners. The regulatory pathway is based on substantial equivalence to a predicate device (Invisalign System, K241412). The "study" described is a set of non-clinical tests to demonstrate that this physical modification does not negatively impact the device's safety and effectiveness. It does not present a study proving the performance of an AI/software component against acceptance criteria in the typical sense of a diagnostic or therapeutic AI device.

Therefore, most of the requested information regarding AI algorithm performance (e.g., sample sizes for test sets, data provenance, expert ground truth establishment, MRMC studies, standalone performance, training set details) is not applicable or not provided in this document.

1. Table of Acceptance Criteria and Reported Device Performance:

The document states: "The subject device, Invisalign® System underwent a complete set of functional and performance testing, including durability, shear bond, retention, and biocompatibility testing. All testing passed acceptance criteria and demonstrated the device modification does not affect the safety and effectiveness of Invisalign® System and does not raise any new questions of safety and effectiveness."

However, the specific quantitative acceptance criteria and the corresponding reported performance values for these tests (durability, shear bond, retention, biocompatibility) are not detailed in this 510(k) summary. These are typically listed in an internal test report, not the public-facing FDA clearance letter.

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

• Sample Size: Not specified.
• Data Provenance: Not specified (since the tests are physical and chemical, not clinical data for an AI algorithm).
• Retrospective/Prospective: Not specified.

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

• Not Applicable. The described tests (durability, shear bond, retention, biocompatibility) are laboratory-based engineering and materials tests, not clinical evaluations requiring expert consensus on a test set of patient data as would be the case for an AI diagnostic device.

4. Adjudication Method for the Test Set:

• Not Applicable. See point 3.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

• No. This document does not mention an MRMC study. The device modification is a physical feature (integrated button) and its impact on human readers or clinical interpretation in an AI-assisted workflow is not discussed.

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

• No, not in the context of AI algorithm performance. The "Invisalign System" does include "proprietary 3D treatment planning software," and this submission notes the software allows "visualization and button placement on the aligners." However, the 510(k) focuses on the physical button's safety and effectiveness, not a new or modified AI algorithm's standalone performance. The software's role is described as "the doctor still approves the treatment plan prior manufacturing," indicating a human-in-the-loop scenario. No standalone algorithm performance evaluation is detailed.

7. The Type of Ground Truth Used:

• For the physical tests (durability, shear bond, retention, biocompatibility): The ground truth would be established through scientific measurement standards and validated laboratory methodologies (e.g., ISO standards for materials testing).
• For any software component related to the new feature: The ground truth for software functionality (e.g., correct button placement visualization, accurate manufacturing instructions) would internally be established through testing against design specifications and requirements. This is not detailed in the document.

8. The Sample Size for the Training Set:

• Not Applicable/Not Specified. This document does not describe the development or training of a new AI algorithm. If the "proprietary 3D treatment planning software" utilizes machine learning, its training set details are not provided as part of this specific 510(k) for a physical modification.

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

• Not Applicable/Not Specified. See point 8.

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This product is suitable for making invisible orthodontic appliances by additive manufacturing (light curing 3D printing) process. The orthodontic appliance is designed for orthodontic treatment. It uses continuous gentle force to adjust tooth position, correct malocclusion, and maintain the results of completed orthodontic treatment.

It can also be used for printing splints and night guards.

Additively Manufactured Aligner Resin is custom plastic aligner system which are a series of doctor prescribed clear removable aligners that are used as alternative treatment for the alignment of maloccluded or misaligned teeth. This series of aligners gently move the patient's teeth in small increments from their original state to a treated state.

Additively Manufactured Aligner Resin is a light-curing resin used to print orthodontic appliances. The resin is a light yellow transparent liquid. The appliance printed by a 3D printer is de-supported, cleaned and post-cured to obtain an orthodontic appliance that can correct the patient's malocclusion. This product is a light-curing 3D printing resin composed of acrylate resin oligomers and acrylate monomers as well as initiators and additives.

Additive manufacturing (light cured) orthodontic resin is a light cured acrylic resin commonly used in the manufacture of orthodontic appliances. The resin is stored in a black HDPE bottle according to the weight of the resin liquid. The color of the resin is colorless or yellowish liquid, polymerized by UV light at 385 nm or 405 nm.

The provided FDA 510(k) clearance letter details the clearance of an "Additively Manufactured Aligner Resin." This document is for a material, not a diagnostic AI device. Therefore, the information typically requested in a description of an AI device's acceptance criteria and study proving its performance (e.g., sample sizes for test and training sets, number of experts establish ground truth, MRMC studies, standalone performance) is not applicable to this submission.

The acceptance criteria and supporting studies for this material device primarily focus on bench testing (physical and mechanical properties), biocompatibility, sterility, and shelf-life. The purpose of these tests is to demonstrate that the new aligner resin is safe and effective for its intended use, comparable to already marketed predicate devices.

Here's an interpretation of the relevant information provided:

Acceptance Criteria and Performance of "Additively Manufactured Aligner Resin"

As this is a material device, the "acceptance criteria" are based on meeting established international standards for dental materials and demonstrating comparable or superior performance to existing predicate devices. The "study that proves the device meets the acceptance criteria" refers to the non-clinical bench testing, biocompatibility testing, and shelf-life testing performed.

1. Table of Acceptance Criteria and Reported Device Performance

The primary standard referenced for mechanical characteristics is ISO 20795-2:2013 Dentistry – Base polymers – Part 2: Orthodontic base polymers. The acceptance criteria for each property are implicitly defined by the requirements of this standard, and the device's performance is reported as meeting these requirements or being comparable to predicate devices.

*Note: For Flexural Modulus and Ultimate Flexural Strength, the subject device's performance was statistically significantly higher than the predicate, which is considered an improvement and not an adverse difference in terms of safety or effectiveness for the material properties. For Water Solubility and Sorption, slight differences were observed but all conformed to the ISO standard.

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

The document does not specify the exact sample sizes for each mechanical property test (e.g., number of specimens tested for flexural strength). This level of detail is typically found in the full testing report, not the 510(k) summary. However, tests were conducted as "bench testing" meaning in a laboratory setting. The data provenance is implied to be from the manufacturer's internal testing facilities, Aidite (Qinhuangdao) Technology Co., Ltd., which is based in China. The testing is retrospective in the sense that it's pre-market validation performed on manufactured material samples.

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

This question is not applicable as this is a material device and not an AI or diagnostic device that requires expert-established ground truth for a test set. Ground truth for material properties is established by objective physical and chemical testing methods adhering to international standards (e.g., ISO, ASTM).

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

This question is not applicable as there is no human interpretation or subjective assessment being performed that would require an adjudication method. The testing results are 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

This question is not applicable. An MRMC study is relevant for diagnostic AI devices where human readers (e.g., radiologists) interpret images with and without AI assistance. This submission is for a dental material.

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

This question is not applicable. There is no algorithm or software for standalone performance evaluation in this material device submission.

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

The "ground truth" for this material device is established by objective, standardized laboratory testing methods against pre-defined specifications and international material standards (e.g., ISO 20795-2:2013). This is analogous to a "gold standard" for material properties.

8. The sample size for the training set

This question is not applicable. This is a material device, not an AI/machine learning model, and therefore does not have a "training set" in the computational sense.

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

This question is not applicable for the same reason as point 8.

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Clear Miracle is a clear orthodontic appliance designed to treat malocclusions in patients with permanent dentition (i.e., all second molars). It uses a series of gradual tooth movements to position teeth sequentially with continuous gentle force. Clear Miracle is intended for professional use only.

Clear Miracle is a methacrylate-based resin designed for creating clear, light-cured aligners. It is supplied in 250-gram bottles made of high-density polyethylene (HDPE) and is a light yellow in color. Exposure to ultraviolet (UV) light within the 405–412-nanometer (nm) wavelength range causes the liquid resin to solidify into a three-dimensional structure. The resin contains a photoinitiator that begins the curing process at wavelengths between 405 and 412 nm. During additive manufacturing, Clear Miracle forms 50-μm-thick layers, achieving a resolution of 0.022 mm in the X and Y axes. This ensures the creation of high-precision orthodontic aligners through a layer-by-layer curing process.

This document is a 510(k) Clearance Letter from the FDA for a medical device called "Clear Miracle," an orthodontic clear aligner. According to the document, clinical testing was not required for this device due to its substantial equivalence to a predicate device. Therefore, the provided text does not contain information about explicit acceptance criteria for device performance based on a study, a test set, expert involvement, or any human-in-the-loop (MRMC) or standalone algorithm performance studies.

The document primarily focuses on demonstrating substantial equivalence to a predicate device (TERA HARZ CLEAR, K223355) through non-clinical testing and comparison of technological characteristics.

Here's a breakdown of the information that can be extracted or inferred, and what cannot:

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

The document doesn't explicitly state "acceptance criteria" in the sense of predefined thresholds for a clinical study that the device must meet to prove its efficacy/safety in real-world scenarios. Instead, it reports performance values obtained from non-clinical mechanical property tests and compares them to the predicate device's values and relevant ISO standards. The implicit "acceptance criteria" here are that the 'Clear Miracle' device performs at least as well as the predicate device or meets the relevant ISO standard requirements.

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

• Test Set (for performance validation): The document does not specify a "test set" in the context of patient data or clinical cases. The "testing" referred to is laboratory-based non-clinical testing of materials and manufacturing processes. Therefore, information about patient sample sizes or their provenance (country, retrospective/prospective) is not applicable/provided.
• The mechanical properties tests were conducted on "specimen plates" as per ISO 20795-2:2013. The exact number of specimens tested for each characteristic is not provided in this summary.

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

• Not applicable/provided. As there was no clinical study testing the device's performance against human ground truth (e.g., diagnostic accuracy), there were no experts establishing ground truth in that sense. The "ground truth" for the non-clinical tests is based on the methods and measurements defined by the ISO standards.

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

• Not applicable/provided. No adjudication method was mentioned as there was no clinical reading or expert review process involved.

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. The device "Clear Miracle" is described as a "clear orthodontic appliance" made of resin, a physical device, and not an AI/software. Therefore, no MRMC study or AI assistance evaluation would be relevant or conducted for this type of product.

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

• Not applicable. See point 5. This is a physical medical device, not an algorithm.

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

• For the non-clinical mechanical property tests, the "ground truth" is established by the measurement standards and methodologies prescribed by ISO 20795-2:2013. This involves precise laboratory measurements of physical properties.

8. The sample size for the training set:

• Not applicable/provided. There is no "training set" in the context of machine learning for this physical device. The manufacturing process does involve "optimization" and "validation" of print parameters, but this is not a machine learning training process.

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

• Not applicable/provided. As there's no training set for an AI model, this question is not relevant.

In summary:

This FDA clearance for "Clear Miracle" is for a physical medical device (orthodontic aligner resin), not an AI/software product. The substantial equivalence determination was primarily based on non-clinical laboratory testing against well-established international standards (ISO 20795-2:2013, ISO 10993-1) and direct comparison of its material properties and manufacturing process with a previously cleared predicate device. Therefore, many of the questions related to clinical trials, AI performance, expert review, and ground truth establishment in a diagnostic context are not relevant to this specific device clearance.

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MEM Clear Aligner System is indicated for the treatment of tooth malocclusion in patients with permanent dentition (i.e. all second molars). The MEM Clear Aligner System repositions teeth by way of continuous gentle force.

The MEM Clear Aligner System is a customized plastic orthodontic system, consisting of a series of transparent, removable aligners prescribed by a doctor to correct misaligned or crooked teeth. These customized, removable transparent plastic aligners gradually reposition teeth with continuous gentle pressure.

The product is a series of transparent, removable orthodontic aligners, custom-made according to the dentist's prescription and designed using the "3Shape A/S (K171634)" software. They are manufactured using thermoforming technology. These aligners are designed to provide a comfortable teeth straightening experience and achieve optimal correction through precise design using advanced technology.

The provided FDA 510(k) clearance letter for the MEM Clear Aligner System does not contain any information regarding a study that proves the device meets specific acceptance criteria based on diagnostic performance, reader studies, or AI algorithm performance. This document primarily focuses on establishing substantial equivalence to a predicate device (ULab Systems Dental Aligner Kit, K192596) by comparing intended use, technological characteristics, and material properties.

The "Non-Clinical Performance Data" section lists various ISO standard tests related to biocompatibility and material properties, along with transportation, packaging, and shelf-life testing. These are primarily for demonstrating the safety of the material and the product's integrity, not its diagnostic efficacy or performance in a clinical setting related to treatment outcomes or accuracy of tooth movement prediction.

Therefore, based solely on the provided text, I cannot produce a table of acceptance criteria and reported device performance related to a diagnostic or AI-driven study, nor can I answer questions about sample sizes, data provenance, expert panels, MRMC studies, or ground truth types for such a study.

The document implicitly suggests the "acceptance criteria" for clearance are met by demonstrating:

• Same Intended Use: Treatment of tooth malocclusion in patients with permanent dentition.
• Similar Technological Characteristics: Mode of action, principles of operation, method of use, OTC/Rx status, duration of use, method of manufacturing, design, application (removable).
• Comparable Material Biocompatibility and Mechanical Properties: Demonstrated through ISO and ASTM standards.

Here's what can be extracted and what cannot:

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

Since this is a substantial equivalence submission for a physical medical device (aligners), not an AI/diagnostic device, the "acceptance criteria" are related to equivalence to the predicate, and material/biocompatibility performance rather than diagnostic accuracy.

Note: There are no "acceptance criteria" in the sense of diagnostic performance metrics (e.g., sensitivity, specificity, AUC) because this is not an AI/diagnostic device.

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

• Not Applicable. The document describes tests on the device materials and physical properties, not on a "test set" of patient data for an algorithm. The biocompatibility tests are likely performed on a limited number of animal subjects or cell cultures, and the physical property tests on samples of the material.
• Data Provenance: Not specified for biocompatibility or material tests beyond the standards referenced. The company is based in Taiwan.

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

• Not Applicable. There is no "test set" requiring expert ground truth in the context of this 510(k) submission. The ground truth for material properties is the physical measurement itself according to standard protocols.

4. Adjudication method for the test set

• Not Applicable. No human adjudication panel for a test set of data.

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 a physical aligner device, not an AI or imaging diagnostic device. No MRMC study would be performed for this product type.

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

• Not Applicable. This is a physical aligner device. There is no AI algorithm being evaluated for standalone performance. The design of the aligners uses "3Shape A/S (K171634) software," but the 510(k) is for the physical aligner product, not the software itself or its AI capabilities for treatment planning.

7. The type of ground truth used

• For Biocompatibility: In vitro (cytotoxicity, gene mutation), in vivo (animal studies for irritation, toxicity, pyrogenicity, sensitization, implantation).
• For Mechanical Properties: Measurements derived from standardized laboratory tests (e.g., ISO 20795-2:2013, ASTM D570).

8. The sample size for the training set

• Not Applicable. There is no training set for an AI algorithm described in this 510(k). Fabrication is custom for each patient based on a doctor's prescription.

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

• Not Applicable. No training set, thus no ground truth establishment for it.

In conclusion: The provided document is a 510(k) clearance for a physical medical device (clear aligners), not a software-as-a-medical-device (SaMD) or an AI/diagnostic imaging device. Therefore, the questions related to AI performance metrics, test sets, training sets, human readers, and expert ground truth are not applicable to the information contained within this specific FDA clearance letter. The study described in the document primarily involves materials testing and biocompatibility assessments to demonstrate the safety and equivalence of the aligner product itself.

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The Laon Ortho is intended for use as a medical front-end device providing tools for management of orthodontic models, systematic inspection, detailed analysis, treatment simulation and virtual appliance design options based on 3D models of the patient's dentition before the start of an orthodontic treatment.

The use of the Laon Ortho requires the user to have the necessary training and domain knowledge in the practice of orthodontics, as well as to have received a dedicated training in the use of the software.

Laon Ortho is a PC-based software that sets up virtual orthodontics via digital impressions. It automatically segments the crown and the gum in a simple manner and provides basic model analysis to assist digital orthodontic procedures.

The provided FDA 510(k) clearance letter and summary for Laon Ortho primarily focus on demonstrating substantial equivalence to predicate devices, particularly concerning its design, functionality, and intended use. While it mentions "verification and validation (V&V) testing" and "performance test," it does not provide granular details about the specific acceptance criteria for AI performance, the study design, sample sizes, ground truth establishment methods, or expert qualifications that would typically be associated with rigorous clinical or non-clinical performance studies for AI/ML devices.

The key takeaway is that the clearance appears to be based on the equivalence of the "Automatic Simulation Mode" to the "Manual Mode" in achieving the same treatment planning, rather than a standalone AI performance study against a clinical ground truth.

Therefore, I will extract what is available and highlight what is not present given the prompt's request.

Here's the breakdown based on the provided document:

Acceptance Criteria and Device Performance for Laon Ortho

The document states: "The results of the verification and validation (V&V) testing showed that the Automatic Mode achieves the same treatment planning as the existing workflow." This implies the "acceptance criteria" for the Automatic Simulation Mode (the new feature) was equivalence to the existing manual workflow for treatment planning. However, the specific metrics for "same treatment planning" are not detailed.

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document does not specify quantitative metrics (e.g., accuracy, precision, F1-score, or specific measurement deviations) for "same treatment planning" or "meets all performance test criteria."

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

• Test Set Sample Size: Not explicitly stated. The document mentions "verification and validation (V&V) testing" and "performance test" but does not provide the number of cases or scans used for these tests.
• Data Provenance: Not explicitly stated. The company is based in South Korea, but the origin (e.g., country, specific clinics) of the data used for V&V testing is not mentioned. It also doesn't explicitly state if the data was retrospective or prospective, though performance testing often uses existing (retrospective) data.

3. Number of Experts and Their Qualifications for Ground Truth

• Number of Experts: Not explicitly stated. The document states, "The use of the Laon Ortho requires the user to have the necessary training and domain knowledge in the practice of orthodontics, as well as to have received a dedicated training in the use of the software." This refers to the user of the software, not the experts who established the ground truth for V&V.
• Qualifications of Experts: Not explicitly stated. It's highly probable that orthodontic experts were involved in evaluating if the Automatic Mode achieved "the same treatment planning," but their specific number, roles, and qualifications (e.g., years of experience, board certification) are not detailed in this summary.

4. Adjudication Method for the Test Set

• Adjudication Method: Not explicitly stated. Given the lack of detail on the "same treatment planning" assessment, the method for resolving discrepancies among evaluators (if multiple were used) is unknown from this document.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• Was an MRMC study done? No, not explicitly stated or implied. The summary explicitly notes "Clinical Test Summary: Not Applicable." This indicates that a rigorous human-in-the-loop study, such as an MRMC study comparing human readers with and without AI assistance, was not performed or submitted as part of this 510(k). The focus was on the internal equivalence of the AI-driven "Automatic Mode" to the device's own "Manual Mode."
• Effect Size: N/A, as no MRMC study was conducted.

6. Standalone (Algorithm Only) Performance Study

• Was a standalone study done? Yes, in an indirect sense, but against an internal benchmark. The "Automatic Simulation Mode" is an algorithm that performs treatment planning. The V&V testing confirmed that this algorithm's output ("Automatic Mode") aligns with the output of the "existing workflow" (presumably the manual or previously cleared aspects of the device). However, this is not a standalone study against an independent, external clinical ground truth (e.g., pathology, clinical outcomes). It's more of a functional validation against an established internal process. The document does not provide standalone quantitative performance metrics (e.g., sensitivity, specificity, accuracy) for the algorithm itself.

7. Type of Ground Truth Used

• Type of Ground Truth: The "ground truth" used for evaluating the "Automatic Simulation Mode" was its ability to achieve "the same treatment planning as the existing workflow." This implies that the accepted output or method of the "existing workflow" served as the reference. It is an internal ground truth based on the device's established manual capabilities, rather than an independent clinical ground truth like pathology, surgical findings, or long-term patient outcomes.

8. Sample Size for the Training Set

• Training Set Sample Size: Not stated. The document refers to "Software Validation" and "Performance Testing" but provides no information about the size or characteristics of the data used to train the "Automatic Simulation Mode" algorithm.

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

• Ground Truth Establishment for Training: Not stated. Since the training set details are omitted, the method for establishing its ground truth is also not provided.

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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 LuxCreo Clear Aligner System is indicated for the treatment of tooth malocclusion in patients with permanent dentition (i.e. all second molars). The LuxCreo Clear Aligner System repositions teeth by way of continuous gentle force.

Dental health professionals achieve orthodontic tooth movement through prescription of aligners which apply force to the patient's teeth so that each tooth follows a prescribed, predetermined displacement. LuxCreo Clear Aligner System is custom plastic aligner system which are a series of doctor prescribed clear removable aligners that are used as alternative treatment for the alignment of maloccluded or misaligned teeth. This series of aligners gently move the patient's teeth in small increments from their original state to a treated state.

A 3D printer, based on a 3D stereolithographic drawing, prints the predetermined shape of each aligner. Final polymerization is achieved by placing the printed aligner in a UV-light curing box. 3D printing uses specialty liquid resins, which help the aligners achieve mechanical properties similar to thermoplastics, and increased processability.

The aligners are packaged and labeled according to the sequence in which they are intended for use, determined by the prescribing dental health professional. The finished set of aligners is shipped with twelve-month-shelf-life to the prescribing physician, who is accountable for ensuring the patient uses the device properly and safely.

The LuxCreo Clear Aligner System mechanism of operation, and software usage, are identical to the predicate devices, and support a determination of substantial equality. Both the LuxCreo Clear Aligner System and the predicate devices are manufactured from a biocompatible, non-sterile polyurethane materials that supports a determination of substantial equality.

This FDA 510(k) clearance letter and supporting Special 510(k) Summary for the LuxCreo Clear Aligner System (K250343) does not describe an AI medical device or a study involving AI.

The document primarily focuses on demonstrating substantial equivalence to a predicate device (K212680) by comparing:

• Intended Use/Indications for Use: Identical for both devices.
• Mode of Action: Identical (application of continuous gentle force for teeth alignment).
• Method of Use: Identical (sequential use of preformed plastic trays).
• Manufacturing Process: Identical (light-cured 3D printing).
• Material: Different, but the new material's mechanical and chemical properties were tested against pre-determined acceptance criteria and found to be equivalent or better.
• Biocompatibility: Extensive ISO 10993 testing was performed to demonstrate biocompatibility of the new material, with all results meeting requirements.
• Shelf Life: Increased from 6 months to 12 months, supported by stability and packaging integrity testing.

The document does not mention any software that performs medical functions requiring AI/ML performance evaluation, nor does it refer to terms like "algorithm performance," "diagnostic accuracy," "human-in-the-loop," "ground truth," or "expert readers" in the context of an AI study. The "software usage" mentioned (Section H, page 7) refers to ordering workflow, not a medical function.

Therefore, I cannot extract the requested information (acceptance criteria, study details for AI performance, sample sizes, expert qualifications, etc.) because the provided text describes a medical device clearance based on material and shelf-life changes, not an AI/ML component.

If the LuxCreo Clear Aligner System had an AI component (e.g., AI-powered treatment planning, AI for predicting tooth movement, or AI for assessing aligner fit from scans), that information would typically be detailed in a separate section addressing the software's performance, validation, and clinical results. This document does not contain such information.

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The Spark™ Clear Aligner System is indicated for the alignment of teeth during orthodontic treatment of malocclusion.

The Spark™ Clear Aligner System consists of a series of doctor-prescribed, custom manufactured, thin, clear plastic removable orthodontic appliances (aligners) that gently move the participant's teeth in small increments from their original state to a more optimal, treated state. Treatment planning, aligner manufacture are supported by a proprietary software system. The clinician receives the aligners and provides them in sequential "stages" to the patient, confirming fit and monitoring treatment from the placement of the first aligner to the removal of the final aligners are held in place by presure and can be removed by the patient at any time. Several treatment options may be integrated into the Spark Clear Aligners, such as cutouts, hooks, and/or other attachment shapes, bite ramps, etc. to aid the aligners with teeth movement. The integrated occlusion guides on the upper and lower aligners allow the option of incrementally repositioning the mandible (lower jaw) forward to address in patients who have not reached full skeletal maturity.

This document is a 510(k) clearance letter for the Spark™ Clear Aligner System. It describes the device, its intended indications for use, and confirms its substantial equivalence to previously cleared devices. However, it does NOT contain the detailed information necessary to answer your questions about acceptance criteria and the study proving the device meets those criteria.

Typically, such information, especially related to the performance of a device against specific acceptance criteria and the methodologies of studies (like sample sizes, expert qualifications, ground truth establishment, etc.), would be found in detailed performance study reports or summaries submitted as part of the 510(k) application, but this clearance letter does not include that level of detail.

Therefore, I cannot provide the requested information from the provided text. The document focuses on regulatory clearance and substantial equivalence, not the specifics of performance testing or clinical study design.

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ZeTTA PACS is intended for use in hospitals and diagnostic centers as a PACS to receive, store, retrieve, and display medical images from DICOM-compliant modalities, including CT, MRI, ultrasound, and radiographic devices. The system enables healthcare professionals to securely access and analyze diagnostic images over hospital networks.

Typical users of ZeTTA PACS include trained professionals such as physicians, radiologists, and medical technicians.

For mammography, only preprocessed DICOM for-presentation images can be interpreted for primary image diagnosis in mammography. Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations. Mammographic images may only be interpreted using a monitor that meets technical specifications identified by FDA.

ZeTTA PACS is a Windows-based Picture Archiving and Communication System (PACS) used in hospitals and diagnostic centers to receive, store, retrieve, distribute, and display medical images from various DICOMcompliant modalities, such as CT, MRI, ultrasound, and radiographic devices. This system supports the DICOM 3.0 standard and is designed to allow healthcare professionals to securely access and manage medical images over hospital networks.

ZeTTA PACS supports more than two high-resolution monitors to facilitate efficient image interpretation. It provides advanced layout options, multi-worklist functionality, and DICOM GSPS (Grayscale Presentation State), enhancing diagnostic and analytical efficiency. Additionally, it offers image analysis tools such as ruler and angle, along with image manipulation features like windowing and zoom, enabling healthcare professionals to perform more accurate analyses.

ZeTTA PACS integrates multiple medical imaging sources into a centralized solution, ensuring secure storage and management. It is useful across various medical fields such as radiology, and neurology. However, it does not provide diagnostic decision-making functions, and all diagnoses, treatments, and prescriptions must be made by qualified medical professionals.

Furthermore, ZeTTA PACS does not support mobile devices and is designed for use in network-based desktop and workstation environments, ensuring stable and secure management of medical images.

The provided document describes the ZeTTA PACS, a medical image management and processing system, and its substantial equivalence to a predicate device. However, the document does not contain an acceptance criteria table or a detailed study proving the device meets specific acceptance criteria in the manner requested.

The "Determination of Substantial Equivalence" section in the K241694 submission (page 6-7) compares the proposed device (ZeTTA PACS) to the predicate device (Infinitt PACS 7.0) based on various features and functionalities. This comparison is used to argue for substantial equivalence, not to demonstrate performance against pre-defined quantitative acceptance criteria for things like diagnostic accuracy or sensitivity/specificity.

Here's an analysis based on the information provided, highlighting what is present and what is missing:

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

• Not present in the requested format. The document provides a detailed comparison table between the proposed device and its predicate, outlining functionalities like worklist modes, study list features, image display options, and output capabilities. It consistently concludes "Same" for these features, indicating functional equivalence, but it does not present quantitative performance metrics against specific acceptance criteria.

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

• Not present. The document mentions "Performance Testing" was conducted, confirming that "ZeTTA PACS meets all performance test criteria and that all functions work without errors." However, it does not specify the sample size of images or cases used for this testing, nor does it provide details about the data provenance (e.g., country of origin, retrospective/prospective nature).

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/Not present. Since a clinical performance study with an explicit ground truth assessment by experts is not described for the ZeTTA PACS itself, this information is not provided. The device is a PACS system for managing and viewing images, not an AI-powered diagnostic tool that produces interpretations.

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

• Not applicable/Not present. For the same reasons as point 3, an adjudication method for a test set's ground truth is not relevant or provided in this context.

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 present. The device described (ZeTTA PACS) is a Picture Archiving and Communication System; it does not explicitly feature AI-assisted diagnostic capabilities. Therefore, an MRMC study comparing human readers with and without AI assistance is not described.

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

• Not applicable/Not present. ZeTTA PACS is a software system for image management and display, not a standalone diagnostic algorithm. Its function is to facilitate human interpretation, not to provide independent diagnostic outputs.

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

• Not applicable/Not present. As this is a PACS system and not an AI diagnostic device, the concept of "ground truth" for diagnostic accuracy is not directly applicable to its stated function in this submission. The tests performed were likely functional and performance tests to ensure the system handles images correctly, displays them accurately, and supports its specified features.

8. The sample size for the training set

• Not applicable/Not present. ZeTTA PACS is not described as an AI/ML-driven device requiring a training set in the way a diagnostic algorithm would. It is a traditional software system for image management.

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

• Not applicable/Not present. For the same reason as point 8, this information is not relevant or provided.

Summary of what is available regarding "acceptance criteria" and "study":

The document focuses on demonstrating substantial equivalence to an existing predicate device (Infinitt PACS 7.0) based on functional and technical characteristics.

• "Acceptance Criteria" (Implicit): The implicit acceptance criteria appear to be the functionalities and performance of the predicate device, or general industry standards for PACS systems. The comparison table (pages 6-7) outlines the features of both the proposed and predicate devices, and the consistent "Same" in the "SE Decision" column indicates that the proposed device meets these functional requirements.
• "Study" (Performance Testing): "Performance Testing" was conducted to confirm that "ZeTTA PACS meets all performance test criteria and that all functions work without errors." (Page 9, "Non-Clinical Test Summary"). This implies internal testing was performed to ensure the software's functionality, stability, and adherence to design specifications. However, specific test methodologies, quantitative results, or external validation studies are not detailed.
• No Clinical Studies: The document explicitly states, "No clinical studies were considered necessary and performed." (Page 9, "Clinical Test Summary"). This further confirms that no studies involving human subjects for diagnostic accuracy or effectiveness were part of this submission.

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The Pearl Clear Aligner is indicated for the alignment of teeth during orthodontic treatment of malocclusions by continuous gentle forces.

Pearl Clear Aligner is comprised of a series of clear, thin, thermoformed removable aligner trays that are designed to align teeth during the orthodontic treatment of malocclusions. They are made of biocompatible thermoplastic polyurethane. They are provided non-sterile and are customized for each patient according to the dental clinician's prescription. The dental health professional (dentist/orthodontist) provides a digital file (scan) of the patient's teeth to Pearl Digital. Based on the dental health professional's treatment plan, Pearl Digital develops a digital plan using commercially available treatment planning software. Upon approval by the dental health professional, molds are created with 3D-printing technology and the clear aligners are vacuum formed on the molds. The finished, customized aligners are provided to the dental health care professional who delivers the aligners to the patients in sequential stages checking for fit and function.

The provided document is a 510(k) premarket notification for the Pearl Clear Aligner. It primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting a standalone study with detailed performance metrics and acceptance criteria for the new device.

Therefore, much of the requested information regarding acceptance criteria, specific study design, sample sizes, expert involvement, and ground truth for a performance study is not available within this document. The document mainly discusses the technical characteristics and biocompatibility testing of the Pearl Clear Aligner and compares them to the predicate device.

However, I can extract the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

Based on the document, specific quantitative acceptance criteria for the device's performance (e.g., accuracy of tooth movement, treatment success rates) are not detailed. The performance aspects highlighted are related to the manufacturing process validation and the general concept of applying forces for tooth alignment.

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

• The document mentions "Bench testing was performed to validate the manufacturing process to ensure the accuracy of the final aligners compared to the initial digital scans." However, the sample size for this test set is not specified.
• Data provenance is not specified (e.g., country of origin, retrospective or prospective).

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

• This information is not provided in the document. The manufacturing process validation likely involved internal technical experts, but their number and specific qualifications are not detailed.

4. Adjudication method for the test set:

• This information is not provided in the document.

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:

• An MRMC comparative effectiveness study is not mentioned for this device. The device itself (Pearl Clear Aligner) is an orthodontic appliance, not a diagnostic AI system with human-in-the-loop interaction for interpretation. The "treatment planning software" is mentioned as a reference device, but no MRMC study involving it is described here.

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

• This information is not applicable in the context of an orthodontic aligner device. While an algorithm is used for treatment planning (referencing PlaniMax Orthodontic Software, K201036), this document is for the aligner itself, and no standalone algorithm performance study for the aligner's effectiveness is detailed. The closest would be the "bench testing" to ensure manufacturing accuracy, which is a validation of the physical product, not a standalone algorithm performance.

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

• For the "bench testing" of manufacturing accuracy, the "initial digital scans" (likely of the patient's teeth or desired final positions) served as the reference or ground truth against which the final aligners were compared.

8. The sample size for the training set:

• The document implies that "commercially available treatment planning software is used" (referencing PlaniMax Orthodontic Software, K201036). If this software utilized a training set (as AI/ML software often does), its sample size is not specified in this document, as the document focuses on the aligner device.

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

• As the document references an already cleared "commercially available treatment planning software," how its training set's ground truth was established is not detailed in this 510(k) submission for the Pearl Clear Aligner. That information would typically be part of the 510(k) for the software itself (K201036).

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