(161 days)
Ziocera & Convertible Systems are intended for use with a dental implant to provide support for prosthetic restorations such as crowns, bridges, or overdentures.
The Ziocera & Convertible Systems are device made of Zirconia and Titanium intended for use with a dental implant to provide support for prosthetic restorations such as crowns, bridges, or overdentures. It consists of Abutment, Cylinder and Abutment Screw.
The provided text is a 510(k) summary for a dental device (Ziocera & Convertible System). This document is focused on demonstrating substantial equivalence to predicate devices and does not contain information about acceptance criteria or a specific study proving the device meets those criteria in the context of a diagnostic or AI-driven medical device.
The "study" described in this document is a review of material, indication for use, design, and technological characteristics comparing the proposed device to predicate devices, along with safety tests (including biocompatibility). This is typical for a 510(k) submission for a non-AI or non-diagnostic device, where the goal is to show that the new device is as safe and effective as a legally marketed predicate device.
Therefore, I cannot fulfill your request for the specific details outlined (acceptance criteria, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, ground truth types) because the provided text does not contain this type of information. It's a regulatory submission for a physical dental implant component, not a software or AI-driven diagnostic.
To answer your request, here's a breakdown of what can be extracted or inferred from the document, and where the requested information is absent:
Acceptance Criteria and Study Details for the Ziocera & Convertible System (Based on 510(k) Summary)
This document describes a regulatory submission for a physical dental device (abutments, cylinders, screws), not an AI-driven or diagnostic device. Therefore, many of the requested criteria related to AI performance, reader studies, and ground truth are not applicable or not present in this type of submission.
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Substantial Equivalence to Predicate Devices: |
- Similar intended use
- Similar technology used
- Similar claims
- Similar material composition
- Similar performance characteristics | The Ziocera & Convertible Systems are stated to be "substantially equivalent in design, function and intended use" to the listed predicate devices.
They have "similar material, indication for use, design and technological characteristics" as the predicate devices. |
| Safety: - Biocompatibility
- Compliance with applicable International and US regulations | Safety tests including biocompatibility have been performed to ensure the devices comply with applicable regulations. (Specific results not detailed in this summary) |
| Performance: - (Implied: Mechanical strength, durability, fit as per predicate devices) | Product validations were performed prior to release. (Specific performance metrics not detailed in this summary, but generally inferred to be comparable to predicate devices in mechanical properties). |
Note: For a physical medical device like this, "acceptance criteria" are typically met by demonstrating that the device meets recognized standards (e.g., ISO for biocompatibility, ASTM for mechanical properties) and performs comparably to legally marketed predicate devices, rather than through sensitivity/specificity metrics.
2. Sample size used for the test set and the data provenance
- Sample Size for Test Set: Not applicable in the context of a diagnostic test or AI performance evaluation. This submission refers to physical device testing. The specific number of physical units tested for safety and performance (e.g., for mechanical testing or biocompatibility) is not detailed in this 510(k) summary.
- Data Provenance: Not applicable in the context of diagnostic data. The "data" refers to test results from physical device evaluations and comparisons to predicate devices. The country of origin for manufacturing and testing would likely be South Korea (Republic of Korea), where the submitting company is based. The nature of the studies would be prospective in the sense that they were conducted specifically for this submission, but not in the clinical trial sense for AI evaluation.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Not applicable. This submission does not involve establishing ground truth for a diagnostic test using expert review. The "truth" for the device's performance relies on engineering specifications, material standards, and comparison to predicate devices, not clinical interpretation of data by experts.
4. Adjudication method for the test set
- Not applicable. There is no "adjudication" in the sense of reconciling expert opinions on diagnostic interpretations. Device testing involves objective measurements against established standards.
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, not done. This is a physical device, not an AI or diagnostic tool. MRMC studies are irrelevant for this type of submission.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- No, not done. This is a physical device, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- Not applicable in the diagnostic sense. The "ground truth" for this device's performance would be derived from:
- Material specifications: Chemical composition, mechanical properties (e.g., tensile strength, fatigue resistance) as measured in a lab.
- Biocompatibility standards: Compliance with ISO or ASTM standards for biological safety.
- Design specifications: Dimensional accuracy, fit with implants.
- Comparative analysis: Direct comparison of these attributes against the predicate devices.
8. The sample size for the training set
- Not applicable. There is no "training set" as this is not a machine learning or AI device.
9. How the ground truth for the training set was established
- Not applicable. No training set exists.
§ 872.3630 Endosseous dental implant abutment.
(a)
Identification. An endosseous dental implant abutment is a premanufactured prosthetic component directly connected to the endosseous dental implant and is intended for use as an aid in prosthetic rehabilitation.(b)
Classification. Class II (special controls). The guidance document entitled “Class II Special Controls Guidance Document: Root-Form Endosseous Dental Implants and Endosseous Dental Implant Abutments” will serve as the special control. (See § 872.1(e) for the availability of this guidance document.)