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Smart Moves Complete is indicated for the treatment of tooth malocclusion in patients with permanent dentition (i.e. all second molars). Smart Moves Complete positions teeth by way of continuous gentle force.

Smart Moves Complete consists of a series of doctor-prescribed, thin, clear plastic removable orthodontic appliances (aligners). The aligners gently move the patient's teeth in small increments from their original state to a more optimal, treated state. Smart Moves Complete is intended as an alternative to conventional bracket technology and fixed appliances for the treatment of patients with malocclusion.

The provided text describes a 510(k) premarket notification for "Smart Moves Complete," an orthodontic aligner system. It details the device's indications for use, design, manufacturing, and comparison to a legally marketed predicate device. The submission explicitly states that no clinical studies were performed to support the device as the indications for use are equivalent to the predicate device, and thus, no comparative effectiveness study (such as MRMC) was done, nor was there a standalone algorithm performance evaluation.

Therefore, the requested information regarding acceptance criteria and a study proving the device meets them, specifically within the context of AI/algorithm performance evaluation, cannot be extracted from this document as it pertains to a medical device that does not incorporate AI and relies on equivalence to a predicate device through non-clinical performance data.

The relevant sections of the document state:

• "No clinical studies are included in the submission" (page 4)
• "Clinical Performance Data: There was no clinical testing performed to support the medical device as the indications for use is equivalent to the predicate device. The substantial equivalence is supported by non-clinical testing and the comparative table, so this is not required." (page 9)

Given this, I cannot provide the detailed information requested about acceptance criteria and a study proving the device meets them, as it relates to AI/algorithm performance, because such a study was not conducted or presented in this 510(k) submission.

The document focuses on demonstrating substantial equivalence based on:

• Same intended use as the predicate device.
• Similar technological characteristics, with a detailed comparison table (pages 5-6) highlighting similarities in product code, regulation number, regulation name, indications for use, device description, mode of action, anatomy location, size, manufacturing method, biocompatibility, hardness, and dental tooth alignment software description.
• Non-clinical performance testing (page 8-9) for materials and manufacturing process, including biocompatibility, software verification and validation (though this refers to the design software for aligners, not an AI algorithm for diagnostic or treatment planning), tensile strength, elongation, tensile stress, modulus, load, water absorption, durometer, and process flow validation. These tests are about the physical properties and manufacturing consistency of the aligners, not AI performance.

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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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Biocryl X is intended for the laboratory fabrication of radiographic templates to be worn by a patient during x-ray imaging.
Biocryl X is indicated for the fabrication of dental radiographic templates worn during x-ray imaging.

Biocryl X is a radiopaque, auto-polymerizing powder/liquid dental acrylic system.

The provided text describes a 510(k) submission for a dental acrylic system named "Biocryl X." This submission focuses on establishing substantial equivalence to a predicate device, not on demonstrating clinical performance against specific acceptance criteria in a study involving human or image-based diagnostics.

Therefore, most of the information requested in your prompt regarding acceptance criteria, sample sizes, expert ground truth, adjudication methods, and AI-related studies is not applicable to this document.

However, I can extract the relevant information regarding the tests performed to establish equivalence:

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

2. Sample sized 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 sample sizes for any of the tests.
• The data provenance is not explicitly stated. These are laboratory/material tests, not clinical studies.

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. The "ground truth" here refers to the results of standardized material and biocompatibility tests, not expert interpretation of clinical data.

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

• Not applicable. These are objective laboratory tests, not subjective assessments requiring adjudication.

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 material science 510(k) submission, not a study of AI-assisted diagnostic effectiveness.

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

• Not applicable. This is not an algorithm or AI device.

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

• The "ground truth" for the tests performed is the objective outcome of standardized material property and biocompatibility assays (e.g., whether a material is cytotoxic, its hardness value).

8. The sample size for the training set

• Not applicable. This is not an AI/machine learning device.

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

• Not applicable. This is not an AI/machine learning device.

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The Keles protraction face mask is used in the treatment of patients with Class III The Keles profitaction facc mask is used in the neationed maxilla. The facemask is especially useful in patients with an anterior bite tendency or condition.

The Keles Facemask is an orthodontic headgear device. All components have been used in legally marketed devices or have been found to be safe for dental use.

This submission is a 510(k) premarket notification for a Class II medical device, the Keles Facemask, an orthodontic headgear. The purpose of a 510(k) is to demonstrate that the new device is substantially equivalent to a legally marketed predicate device, meaning it is as safe and effective. Therefore, there are no specific "acceptance criteria" in the sense of performance metrics (like sensitivity, specificity, accuracy) for an AI model or a new diagnostic technology.

Instead, the "acceptance criteria" are related to demonstrating substantial equivalence in design, materials, manufacturing, and intended use to a predicate device. The "study" that proves the device meets these criteria is the submission itself, which provides a detailed comparison to the predicate device.

Here's an analysis based on the provided document:

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

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

• Not applicable. This submission is for a physical medical device (orthodontic headgear), not a data-driven device like an AI algorithm. Therefore, there is no "test set" of patient data in the context of an AI study. The determination of substantial equivalence relies on a comparison of device characteristics, materials, and intended use.

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

• Not applicable. See point 2. The "ground truth" here is established by regulatory standards and expert opinion within Great Lakes Orthodontics regarding the safety and effectiveness of their design compared to a known safe and effective predicate device.

4. Adjudication method for the test set

• Not applicable. See point 2. The regulatory review process itself involves expert review by the FDA, who adjudicates the submitted evidence for substantial equivalence.

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 device is a physical orthodontic device, not an AI diagnostic tool.

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

• Not applicable. This device is a physical orthodontic device, not an AI algorithm.

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

• The "ground truth" for this type of submission is the established safety and effectiveness of the legally marketed predicate device. The manufacturer asserts, and the FDA concurs, that the Keles Facemask is substantially equivalent to this predicate, implying it meets the same safety and effectiveness standards.

8. The sample size for the training set

• Not applicable. This is a physical device, not an AI algorithm. There is no concept of a "training set" in this context.

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

• Not applicable. See point 8.

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Metacryl___ is intended for the chairside fabrication of soft relines for dentures.

Metacryl is a chemically cured soft denture reline. All components have been used in legally marketed devices or have been found to be safe for dental use.

The provided text describes the "Metacryl" soft denture reline device. However, it does not contain specific acceptance criteria, a detailed study proving device performance against such criteria, or the requested details about statistical methods, expert involvement, or training data.

The document primarily focuses on establishing substantial equivalence to a predicate device (Flexacryl Soft) for 510(k) clearance.

Here's an analysis based on the information available:

Acceptance Criteria and Device Performance

The document does not explicitly state numerical acceptance criteria in a dedicated table format. Instead, it lists the properties evaluated and concludes that the device's performance, along with its similarity to the predicate and biocompatibility results, supports its safety and effectiveness.

Note: The document states that Metacryl was "evaluated as follows" for mechanical properties, hardness, water absorption, discoloration, and peel strength. It does not provide the specific quantitative results for these evaluations, nor does it define what specific values would constitute "acceptance." The conclusion is a general statement of similarity and support for safety and effectiveness.

Additional Information Not Available in the Provided Text:

1. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): This information is not provided. The document states "Metacryl was evaluated," but does not detail the size or nature of the test set for the performance parameters.
2. 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 as this device is a material, not an AI or diagnostic device requiring expert interpretation of ground truth in the context of imaging or clinical outcomes. The "ground truth" here would be the physical and chemical properties measured in a lab setting.
3. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable for this type of material testing.
4. 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-assisted diagnostic or imaging device.
5. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. This is a material, not an algorithm.
6. The type of ground truth used (expert concensus, pathology, outcomes data, etc): For the performance properties (mechanical, hardness, water absorption, discoloration, peel strength), the ground truth would be the measured values obtained through established laboratory testing protocols for dental materials. For biocompatibility, the ground truth was the result of the ISO Agar Overlay Cytotoxicity Test.
7. The sample size for the training set: Not applicable. This is not an AI or machine learning device requiring a training set.
8. How the ground truth for the training set was established: Not applicable.

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Variflex™ is intended for the laboratory fabrication of dental appliances such as interocclusal splints and night guards.

Variflex 100 is a chemically cured soft dental acrylic. All components have been used in legally marketed devices or have been found to be safe for dental use.

This is a 510(k) premarket notification for a dental material (Variflex™ heat-softening acrylic), not a medical device software or AI algorithm. Therefore, many of the requested criteria such as "effect size of how much human readers improve with AI vs without AI assistance," "standalone performance," "training set size," and "ground truth establishment for training set," are not applicable.

Here's the information gleaned from the document regarding the acceptance criteria and the study that proves the device meets them:

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

Note: The document states that "We conclude that the similarity in composition between Variflex™ and the predicate device, as well as the performance data and biocompatibility results, supports the safety and effectiveness of Variflex™ for the indicated uses." This implies that the acceptance criteria for the mechanical and physical properties were met if they were comparable or equivalent in performance to the predicate device, as the 510(k) process is about demonstrating substantial equivalence. Exact numerical acceptance criteria are not provided in this summary.

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

• Sample Size: Not specified in the provided text for any of the tests (mechanical, physical, or biocompatibility).
• Data Provenance: Not specified. It's standard for such tests to be laboratory-based.

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

Not applicable. This is a material testing for a physical device, not an AI or diagnostic imaging device requiring expert ground truth for interpretation.

4. Adjudication method for the test set

Not applicable. No "adjudication" in the sense of expert consensus on interpretations is relevant here. The tests are objective laboratory 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

Not applicable. This is a material test, not a diagnostic imaging device with human readers.

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

Not applicable. This is a material test.

7. The type of ground truth used

For the biocompatibility tests (MEM Elution Test, Mucous membrane irritation, Kligman Maximization Test), the "ground truth" is established by standard biological assays and their predefined thresholds for cytotoxicity, irritation, and sensitization. For the mechanical and physical properties, the "ground truth" would be the standard measurement techniques and reference values for similar dental materials, with the predicate device serving as a comparative benchmark.

8. The sample size for the training set

Not applicable. This device is not an AI algorithm requiring a training set.

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

Not applicable. This device is not an AI algorithm.

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