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510(k) Data Aggregation
(67 days)
Dental casting alloy for making dental restorations and appliances.
High gold casting alloy
The provided document is a 510(k) premarket notification for a dental casting alloy, Aurecast Bio 59PF. It demonstrates substantial equivalence to a predicate device, Jelenko Sturdicast, based on material composition and physical/mechanical properties. However, it does not describe a study involving a medical device with an AI/ML component or a study that typically involves acceptance criteria as would be found for diagnostic or screening devices.
Therefore, most of the information requested in your prompt (e.g., sample size, data provenance, number of experts, adjudication method, MRMC studies, standalone performance, training set) is not applicable to this type of submission. The document focuses on demonstrating chemical and physical property similarities, which is a different type of evaluation than performance metrics for an AI system.
Here's a breakdown of what can be extracted based on the provided document:
1. A table of acceptance criteria and the reported device performance:
The acceptance criteria are implicitly defined by the "Comparison of physical and mechanical properties" table, where the new device's properties are compared to the legally marketed predicate device (Jelenko Sturdicast). The aim is to show "little difference" or similar characteristics.
| Property | Predicate Device (Sturdicast) Performance | New Device (Aurecast Bio59PF) Performance | Acceptance Criteria (Implicit) |
|---|---|---|---|
| Composition (weight%) | "The noble metal content of the two alloys differs very little (2%). The (Ag+Cu) content is also very close. Aurecast Bio59PF uses Zn as deoxidizing agent." (The specific acceptance range is not quantified but implies close matching). | ||
| Noble Metal (Au + Pt + Pd) | 60 + 0 + 3.8 = 63.8% | 58.9 + 4.1 + 0 = 63% | Within 2% difference |
| Ag + Cu | 22 + 14 = 36% | 23 + 12.3 = 35.3% | "very close" |
| Melting Point Range (°C) | "Physical and mechanical properties shoe only little difference." (Specific numeric ranges for acceptance are not provided, but the values are observed to be close). | ||
| Solidus | 860 | 858 | Close to predicate |
| Liquidus | 905 | 884 | Close to predicate |
| Hardness (Vickers 5/30) | "Physical and mechanical properties shoe only little difference." | ||
| Soft | 175 | 205 | Close to predicate |
| Hard | 270 | 270 | Close to predicate |
| Yield Strength (MPa) | "Physical and mechanical properties shoe only little difference." | ||
| Soft | 352 | 345 | Close to predicate |
| Hard | 703 | 520 | This shows a larger difference for 'hard' (703 vs 520), but the conclusion states "physical and mechanical properties show only little difference" and addresses it by stating "With the exception of a very small amount of Zn and In the two alloys have similar constitution and mechanical characteristics." The acceptance is therefore that these differences are not considered substantial enough to warrant a different regulatory conclusion. |
| Elongation (%) | "Physical and mechanical properties shoe only little difference." | ||
| Soft | 40 | 19 | Close to predicate |
| Hard | 8 | 6 | Close to predicate |
| Density (g/cm3) | 14.1 | 14.2 | Close to predicate |
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. Standard material testing typically involves multiple samples for reproducibility, but the exact number isn't mentioned in this summary.
- Data Provenance: The tests were performed as per ANSI/ADA 5 and ISO 8891 standards (international standards). The manufacturer is Aurex Precious Metal Industries (PTY) LTD, Republic of South Africa. The testing would have been conducted to support this submission. It is generally considered prospective for the specific purpose of the 510(k).
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. This is a material science characterization, not a diagnostic or AI-driven medical device evaluation. Ground truth, in this context, refers to the measured physical and chemical properties of the alloys, which are objectively determined through standardized laboratory tests, not through expert interpretation of images or clinical data.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not Applicable. See point 3. Measurement of material properties doesn't involve adjudication as understood in clinical studies.
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. This is not an AI/ML or diagnostic imaging device.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
- Not Applicable. This is not an AI/ML device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- The "ground truth" (or reference standard) is the measured chemical composition and physical/mechanical properties of the alloys, determined through established and standardized laboratory test methods (ANSI/ADA 5 and ISO 8891).
8. The sample size for the training set
- Not Applicable. There is no AI/ML component, thus no "training set."
9. How the ground truth for the training set was established
- Not Applicable. See point 8.
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