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510(k) Data Aggregation
(55 days)
ClearTemp is a provisional cement used for luting of thin translucent veneer restorations.
ClearTemp is a light curable, temporary cement used specifically for luting thin translucent veneers on teeth.
The provided document describes a 510(k) submission for a dental cement called ClearTemp. The submission focuses on establishing substantial equivalence to a predicate device (TempBond Clear by Sybron Dental Specialties) through various bench tests and a literature review. However, it does not contain information about a study proving the device meets specific numerical acceptance criteria in a clinical setting, nor does it detail studies typically associated with AI/ML-driven medical devices (e.g., test set sample sizes, ground truth establishment, expert adjudication, MRMC studies, or standalone algorithm performance).
Therefore, the requested information, particularly regarding studies that prove the device meets acceptance criteria in a way that involves human perception, expert adjudication, or AI performance metrics, is not present in the provided text. The document focuses on demonstrating comparable physical and chemical properties to a predicate device.
1. A table of acceptance criteria and the reported device performance
The document lists various tests used to compare ClearTemp to its predicate device (TempBond Clear), but it does not specify numerical acceptance criteria. Instead, it states that ClearTemp should perform "as well or better than" or be "comparable to" the predicate device and competitors. The table below summarizes the functions tested and the general performance goal stated.
| Function | Acceptance Criteria (Stated Goal) | Reported Device Performance |
|---|---|---|
| Flexural Strength | Higher than competitors (for strength), comparable to most competitors (for modulus) | Performs as well or better than the predicate device. |
| Hardness | Within competitors' range | Performs as well or better than the predicate device. |
| Compressive Strength | High numbers according to competitors are acceptable | Performs as well or better than the predicate device. |
| Depth of Cure | At the high end of competitors | Performs as well or better than the predicate device. |
| Ambient Light Sensitivity | Low times in this category | Performs as well or better than the predicate device. |
| Sorption | Low readings | Performs as well or better than the predicate device. |
| Film Thickness | (Implied to be comparable/acceptable) | Performs as well or better than the predicate device. |
| Radiopacity | Clear product shows up during an X-ray (implied to be comparable) | Performs as well or better than the predicate device. |
| Sorption Solubility | No degradation in solutions or saliva (implied to be comparable) | Performs as well or better than the predicate device. |
2. Sample size used for the test set and the data provenance
The document refers to "in-house testing" and "bench tests" but does not specify sample sizes for these tests or the data provenance (e.g., country of origin, retrospective/prospective). These are laboratory tests, not clinical studies with patient data.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This information is not applicable as the study described involves bench testing (physical and chemical properties of a dental cement), not expert-based image interpretation or clinical diagnosis that would require ground truth established by experts.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
This information is not applicable for the same reasons as point 3.
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 was not done. This type of study is relevant for AI-powered diagnostic tools assisting human readers, which is not the subject of this 510(k) submission.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
A standalone performance study of an algorithm was not done. This device is a dental cement, not an AI algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The document describes "bench tests" which assess physical and chemical properties of the material. The "ground truth" for these tests would be established through laboratory measurements and established test methodologies (e.g., ISO standards for material properties), not expert consensus, pathology, or outcomes data.
8. The sample size for the training set
This information is not applicable as there is no training set mentioned or implied for this non-AI medical device.
9. How the ground truth for the training set was established
This information is not applicable for the same reasons as point 8.
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