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510(k) Data Aggregation
(471 days)
Krystal Klear Aligners
The Krystal Klear Aligners System is intended to correct minor discrepancies in the alignment of maloccluded anterior teeth on patients with permanent dentition (second molars) by moving the teeth with a progressive series of clear thin, thermoformed plastic aligners, fabricated in stages to gradually align teeth over a period of several months. The aligners are completely removeable by the patient and may be discontinued at any time.
The Krystal Klear device is fabricated of clear, thin, thermoformed copolyester plastic in a sequential series to progressively reposition teeth. Corrective force to straighten the teeth is delivered via minor changes into a position in each subsequent aligner.
The Krystal Klear Aligners System's acceptance criteria and the study proving it meets these criteria are detailed below.
1. Table of Acceptance Criteria and Reported Device Performance:
| Attribute | Acceptance Criteria | Reported Device Performance |
|---|---|---|
| Fit of the aligner against the treatment plan | As determined by a dental health professional | Acceptable results observed during verification and validation testing, showing capability of performing to stated intended use and specification requirements. |
| Process consistency | From the treatment plan file to 3D printed mold to final aligner, measured against internal acceptance criteria derived by considering all sources of variation. | Acceptable results observed during verification and validation testing, showing capability of performing to stated intended use and specification requirements. |
| Density | Met ASTM Method D1505 | Met acceptance criteria. |
| Flexural Modulus | Met ASTM Method D790 | Met acceptance criteria. |
| Flexural Strength | Met ASTM Method D790 | Met acceptance criteria. |
| Tensile Strength | Met ASTM Method D882 | Met acceptance criteria. |
| Tensile Modulus of Elasticity | Met ASTM Method D882 | Met acceptance criteria. |
| Cytotoxicity | Compliant with US FDA Docket Number FDA-2013-D-0350 and ISO 10993-1, non-cytotoxic | Met the requirements of the study protocols and is considered non-cytotoxic. |
| Sensitization | Compliant with US FDA Docket Number FDA-2013-D-0350 and ISO 10993-1, non-sensitizing | Met the requirements of the study protocols and is considered non-sensitizing. |
| Irritation | Compliant with US FDA Docket Number FDA-2013-D-0350 and ISO 10993-1, not an intracutaneous irritant | Met the requirements of the study protocols and is not an intracutaneous irritant. |
| Software Safety and Effectiveness | Software testing performed to verify safety and effectiveness for areas of moderate concern (ordering and treatment planning). | Software testing has been performed to verify the safety and effectiveness of the Krystal Klear Aligner System, which supports a substantial equivalence decision. |
2. Sample size used for the test set and the data provenance:
The document does not explicitly state a specific sample size for a "test set" in the context of a clinical trial or a machine learning evaluation. The performance testing section describes "bench testing" which was performed to ensure accuracy and consistency. This likely refers to in-house engineering and quality control tests on manufactured aligners and processes, rather than a clinical dataset for performance evaluation against a diagnostic algorithm.
The data provenance for these bench tests is internal to the manufacturer ("internal acceptance criteria derived by considering all sources of variation"). There is no mention of country of origin for the data or whether it was retrospective or prospective.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
The document mentions that the "Fit of the aligner against the treatment plan" was "as determined by dental health professional". It does not specify the number of experts, their specific qualifications (e.g., years of experience, specialization), or how ground truth was established for the "test set."
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
No adjudication method is mentioned for the test set.
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:
The document does not describe an MRMC comparative effectiveness study or any study involving human readers or AI assistance. The Krystal Klear Aligner System is a physical medical device (aligners) for orthodontic treatment, not an AI-powered diagnostic or assistive tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
This question is not applicable as the device is not an algorithm for standalone performance. The "Software Consideration" section refers to software used in the ordering and treatment planning process, implying human oversight and input, rather than a standalone algorithm with diagnostic capabilities.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
For the physical attributes (Density, Flexural Modulus, etc.), the ground truth was based on ASTM standards and achieving "acceptance criteria" defined by these standardized methods.
For the "Fit of the aligner against the treatment plan" and "Process consistency," the ground truth was based on "pre-established specifications and acceptance criteria" and likely involves expert assessment by dental health professionals in the context of verification and validation testing.
For biocompatibility, the ground truth was based on standardized biological evaluation tests (cytotoxicity, sensitization, irritation) according to ISO 10993-1 guidance, with results being "non-cytotoxic, non-sensitizing, and is not an intracutaneous irritant."
8. The sample size for the training set:
The document does not mention a "training set" or a machine learning model that would require one. The product is a physical orthodontic device manufactured through a process that includes software for treatment planning but does not describe the use of a machine learning model that would be "trained."
9. How the ground truth for the training set was established:
As no training set is mentioned or implied for a machine learning model, this question is not applicable.
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