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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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1. Direct restorative for Class I, II, III, IV, and V cavities
2. Fissure sealant
3. Sealing hypersensitive areas
4. Repair of (in)direct aesthetic restorations, temporary crown & bridge, defect margins when margins are in enamel
5. Blocking out undercuts
6. Liner or base
7. Core build-up
8. Adhesive cementation of ceramic and composite veneers, inlays and onlays with a thickness (

G-ænial Universal Injectable II is a light-cured, nano-filled radiopaque composite resin filled in syringe. The device is used for the restoration of both anterior and posterior teeth, core build-up, adhesive cementation of ceramic and composite veneer, inlays and onlays, and build-up for transparent removable orthodontic retainers. The device is available in 9 shades.

This document is an FDA 510(k) clearance letter for a dental resin material, G-ænial Universal Injectable II. It is important to note that this is NOT an AI/ML medical device submission. Therefore, the information provided in the document focuses on the material's physical and chemical properties and biocompatibility, as compared to predicate dental materials.

The request asks for information typically found in submissions for AI/ML medical devices, such as acceptance criteria based on diagnostic performance metrics (e.g., sensitivity, specificity, AUC), details about test and training sets, expert consensus for ground truth, MRMC studies, and effect sizes of AI assistance. Since this is a dental material, these types of studies are not relevant and are not present in the provided document.

Therefore, the following response will adapt the requested sections to the context of this dental material, explaining what information is available and what is not, given the nature of the device.

Acceptance Criteria and Device Performance for G-ænial Universal Injectable II

The acceptance criteria for G-ænial Universal Injectable II are based on established ISO standards for dental materials and FDA guidance for composite resin devices. The "study that proves the device meets the acceptance criteria" refers to the Performance Bench Tests and Non-Clinical Performance Testing detailed in Section 7 and 8 of the 510(k) summary. These tests assess the physical, chemical, and biological properties of the material.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are generally "Complies" with specific quantitative or qualitative thresholds defined by the standards (e.g., ISO 4049, ISO 6874). The document reports that the device Complies with all listed requirements.

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

For a dental material, the "test set" refers to the samples of the material manufactured and subjected to the performance bench tests and biocompatibility assessments.

• Sample Size: The document does not specify the exact number of samples (e.g., number of specimens for flexural strength, number of animals for biocompatibility tests). It simply states that "Performance testing includes" and "A biocompatibility assessment was completed."
• Data Provenance: The data provenance is internal to the manufacturer (GC America, Inc.) and derived from laboratory testing of the material according to international ISO standards and FDA guidance documents. There is no indication of "country of origin of the data" in the sense of patient data, nor is it a retrospective or prospective study in the clinical trial sense. These are laboratory-based material characterization tests.

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

This question is not applicable to a dental material submission. The "ground truth" for material properties is established by the standardized test methods themselves (e.g., ISO 4049 defines how depth of cure is measured). There are no "experts" establishing ground truth in the sense of clinical interpretations or diagnoses. The expertise lies in adhering to the established test protocols and analyzing results accurately by qualified laboratory personnel.

4. Adjudication Method for the Test Set

This concept is not applicable for dental material performance testing. Adjudication methods (like 2+1, 3+1 consensus) are used in studies involving human interpretation of images or clinical outcomes, typically for AI/ML device validation. Here, tests are quantitative measurements of physical/chemical properties or biological responses.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done, and Effect Size of Human Readers Improving with AI vs Without AI Assistance

This question is not applicable. G-ænial Universal Injectable II is a dental restorative material, not an AI-assisted diagnostic or therapeutic device. There are no "human readers" involved in interpreting its performance, nor does it assist human readers. Therefore, no MRMC study was performed, and no effect size on human reader improvement with AI assistance can be reported.

6. If a Standalone (i.e., Algorithm Only Without Human-in-the-Loop Performance) was Done

This question is not applicable. G-ænial Universal Injectable II is a physical dental material, not an algorithm. There is no "standalone performance" of an algorithm. Its performance is measured directly through laboratory tests of its inherent material properties.

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

For dental materials, the "ground truth" is based on:

• Standardized Test Methods: Adherence to established ISO standards (e.g., ISO 4049, ISO 6874, ISO 10993) defines the "truth" for material properties like flexural strength, depth of cure, water sorption, and biocompatibility.
• Predicate Device Comparison: Performance is also evaluated in comparison to predicate devices, where "equivalence" often serves as a benchmark for acceptance.

There is no "expert consensus," "pathology," or "outcomes data" in the sense of human diagnostic performance or clinical trial results, as this is a pre-market notification for a material.

8. The Sample Size for the Training Set

This question is not applicable. There is no "training set" for a dental material in the context of machine learning. The material itself is manufactured, and specific properties are tested for quality control and regulatory submission.

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

This question is not applicable, as there is no training set.

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FG Bone Graft B is recommended for:

• Augmentation or reconstructive treatment of the alveolar ridge.
• Filling of infrabony periodontal defects.
• Filling of defects after root resection, apicoectomy, and cystectomy.
• Filling of extraction sockets to enhance preservation of the alveolar ridge.
• Elevation of the maxillary sinus floor.
• Filling of periodontal defects in conjunction with products intended for Guided Tissue Regeneration (GTR) and Guided Bone Regeneration (GBR).
• Filling of peri-implant defects in conjunction with products intended for Guided Bone Regeneration (GBR).

FG Bone Graft B is a sterile, synthetic, multi-porous biocompatible ceramic matrix in granular form for filling bone defects. The material with microporous structure supports rapid ossification with local bone. With its phase purity of >= 99%, the ceramic material complies with US standard specification ASTM F 1088-04. The validated manufacturing process guarantees batch conformity and reproducibility.

The FDA 510(k) clearance letter for FG Bone Graft B indicates that the device is substantially equivalent to a predicate device (CERASORB M DENTAL). The clearance letter references non-clinical tests performed to demonstrate this equivalence, focusing on chemical composition, physical properties, and performance in vivo.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample size for the test set: The document states that the in vivo study used a "Beagle dog" model, and the animals were "divided into groups: test group (FG Bone Graft B), positive control group (Cerasorb, a commercial β-TCP), and a negative control (empty defect)." However, the exact number of animals in each group or total animal count is not specified in the provided text.
• Data provenance: The study was a prospective in vivo animal study performed on Beagle dogs. The location/country of origin of the study is not explicitly stated in the provided text, but the submitter "Full Golden Biotech Co., Ltd." is located in Taiwan.

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

• Number of experts: Not explicitly stated. The histological and radiographic analyses were likely performed by trained professionals (e.g., veterinary pathologists, radiologists), but the number of reviewers or their specific qualifications are not detailed in the provided text.
• Qualifications of experts: Not specified beyond the implied expertise in conducting and analyzing in vivo studies (e.g., histology, micro-CT).

4. Adjudication Method for the Test Set

• Adjudication method: Not explicitly stated. For animal studies, consistency and blinding are typically employed, but a formal "adjudication method" in the sense of multiple human readers for consensus is not described for this non-AI bone graft device. The results are presented as quantitative measurements and observations (e.g., "new bone formation increased," "minimal to mild inflammatory response").

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

• MRMC study: No, an MRMC comparative effectiveness study was not done. This type of study is typically performed for AI/image analysis devices where the AI's impact on human reader performance is being assessed. This document describes a traditional preclinical performance study for a bone graft material.

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

• Standalone performance: N/A. This is a bone graft material, not an algorithm or AI device. The "performance" refers to the biological and physical properties of the material itself, not the output of a software algorithm.

7. The Type of Ground Truth Used

• Type of ground truth: The ground truth for the in vivo study (which is the primary performance study) was established through direct anatomical, histological, and radiographic assessments of the bone defects in the animal model.
  • Histological analysis: Quantified new bone formation, material degradation, and inflammatory response. This involves microscopic examination of stained tissue sections, which is considered a gold standard for assessing tissue regeneration and integration.
  • Radiographic analysis: Used micro-CT to assess bone density and bone volume, providing quantitative structural data.
  • Comparison to predicate: The "ground truth" for showing substantial equivalence was the performance of the established predicate device (Cerasorb) under the same study conditions.

8. The Sample Size for the Training Set

• Sample size for training set: N/A. This device is a bone graft material, not an AI or machine learning algorithm. Therefore, there is no "training set."

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

• Ground truth for training set: N/A. As there is no AI component, there is no training set and no ground truth establishment for such a set.

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Primescan 2 can be used as a diagnostic aid by licensed dentists for detection of caries on visible tooth surfaces, proximal caries, and tooth cracks.

The Primescan 2 is an intraoral scanner that records and generates digital images to provide caries diagnosis support using additional light sources at 405 nm and 850 nm and an optical filter to filter out the excitation light. By illuminating the tooth with these two wavelengths, two diagnosis support modes are realized, the fluorescence mode and the near-infrared mode. The acquired 2D data from the scanner can be viewed in the software in a live stream video during acquisition. The images are also stored in the cloud platform software for later patient communication.

In fluorescence mode, the tooth (or teeth) are illuminated with UV light (405 nm). This stimulates an autofluorescence of the enamel in the green wavelength range. In addition, the red fluorescence is stimulated in carious areas on the teeth. All stimulated fluorescence responses are significantly weaker in terms of their light intensity compared to the back-reflected excitation light. For this reason, the excitation light is filtered out with the aid of an optical filter. The dental professional can use the 2D image data of the fluorescence response (live stream video) as additional information for caries diagnosis.

For near-infrared mode (NIR mode), the tooth or teeth are illuminated with 850 nm. Enamel is partially transparent in this wavelength. The illumination can therefore penetrate the tooth and is reflected by structural defects such as cracks and cavities, as well as from the dentin core. The reflected light is picked up by the 2D sensor of the scanner.

When used, a sleeve is placed over the distal end of the scanner. This sleeve is the only patient contacting component and is offered as either a single-use disposable or a multi-use sleeve that is reprocessed.

Here's the breakdown of the acceptance criteria and study information for the Primescan 2 device, based on the provided FDA 510(k) clearance letter:

Acceptance Criteria and Device Performance

The provided document does not explicitly state quantitative acceptance criteria or a specific table outlining them. However, it does mention that "in vivo bench tests demonstrated that Primescan-2 is effective as a diagnostic aid for occlusal caries using the fluorescence function and tooth cracks using the NIR function." This implies that the device met an unstated level of effectiveness for these diagnostic aids.

Since specific quantitative metrics (e.g., sensitivity, specificity, accuracy) are not provided in the summary, we cannot populate a detailed table with numerical acceptance criteria and performance outcomes.

Study Details

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

• Sample Size for Test Set: Not specified in the provided document.
• Data Provenance: The study was "in vivo bench tests," implying data was collected from living subjects. The country of origin and whether it was retrospective or prospective is not explicitly stated.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

4. Adjudication method for the test set

• Adjudication Method: 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

• MRMC Study: Not mentioned in the provided document. The study described is "Performance Validation Testing of the Caries diagnostic Aid - In vivo bench tests demonstrated that Primescan-2 is effective as a diagnostic aid..." This describes standalone device performance rather than human-in-the-loop improvement.

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

• Standalone Performance Study: Yes, a standalone performance study was done. The document states: "Performance Validation Testing of the Caries diagnostic Aid - In vivo bench tests demonstrated that Primescan-2 is effective as a diagnostic aid for occlusal caries using the fluorescence function and tooth cracks using the NIR function." This indicates the device's ability to provide a diagnostic aid on its own.

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

• Type of Ground Truth: Not explicitly stated. For "in vivo bench tests" related to caries and tooth cracks, ground truth would typically be established through a combination of visual-tactile examination by experienced clinicians, potentially supplemented by radiography or even histology (though less common for a diagnostic aid). However, the document does not specify the method used here.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable or not specified. This device appears to be a direct imaging and diagnostic aid rather than an AI/ML algorithm that requires a separate training set. The "diagnostic support" refers to the illumination and optical filtering techniques, not necessarily an AI algorithm trained on a dataset.

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

• Ground Truth for Training Set: Not applicable, as there's no indication of an AI/ML algorithm with a training set. The device operates on optical principles.

Key Observations and Limitations of Information:

• The provided 510(k) summary focuses highly on technological comparisons, safety, and regulatory compliance (electrical safety, biocompatibility, reprocessing, software, cybersecurity).
• While it mentions "Performance Validation Testing," it lacks specific quantitative results (e.g., sensitivity, specificity, accuracy, AUC) that are typically associated with diagnostic device clearances.
• The clinical study details, such as sample size, expert qualifications, and ground truth establishment methods for the performance validation, are not provided in this specific document. This information would typically be in a more detailed study report submitted to the FDA, but is summarized very broadly here.
• The device is described as providing "diagnostic support" using optical modes (fluorescence and NIR), rather than an explicit AI algorithm.

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