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The ZENEX Implant System_Short is indicated for use in partially or fully edentulous mandibles and maxillae, in support of single or multiple-unit restorations including: cemented retained, screw retained, or overdenture restorations, and final or temporary abutment support for fixed bridgework. It is intended for delayed loading. ZENEX Implant System Short are intended to be used in the molar region.

ZENEX Implant System_Short is a thread type implant made of pure titanium according to ASTM F 67 and supplied sterile, which will be placed in the alveolar bone in order to support or maintain the prosthetic tooth or denture when a patient's teeth are partially or totally lost. The fixture's surface is treated with SLA (Sandblasted with Large-grit and Acid-etching). The entire length of 6.25mm of implant bodies are implanted into the bone to connect prosthetic devices of a dental implant set with the human body (mandibular or maxillary bone).

This is a premarket notification (510(k)) for the ZENEX Implant System Short, a dental implant device. The provided text describes the device, its intended use, and comparative information against predicate devices to demonstrate substantial equivalence. However, it does not contain acceptance criteria for device performance nor a study that directly proves it meets those criteria in the way you've outlined for an AI/software device.

Instead, the document focuses on demonstrating substantial equivalence to a legally marketed predicate device (TS Implant System, K121585) and leveraging testing from a reference predicate (Zenex Implant System, K211090) through a series of non-clinical bench tests and analyses. These tests are designed to show that the new device is as safe and effective as the predicate, not to report on clinical performance or AI algorithm metrics.

Therefore, many of the requested points in your template are not applicable or cannot be extracted from this document, as it's not a study evaluating an AI algorithm's performance against specific acceptance criteria with ground truth.

Here's an attempt to answer your questions based on the provided text, while also noting what information is not present given the nature of this 510(k) submission:

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

The document does not present a table of specific acceptance criteria for clinical performance metrics (like sensitivity, specificity, or F1 score) that would be relevant for an AI device, nor does it report device performance in that manner. Instead, the "performance" discussed relates to meeting engineering and biocompatibility standards to demonstrate substantial equivalence to a predicate device.

The "acceptance criteria" are implicitly meeting the standards of the referenced ISO and ASTM guidelines for non-clinical testing. The "reported device performance" is that the device met these standards and demonstrated substantial equivalence.

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

• Test Set Sample Size: Not applicable in the context of an AI study. The "test set" here refers to the physical samples of the device used in bench testing. The specific number of physical implants or components tested for each non-clinical test (e.g., fatigue, shelf-life) is not detailed, beyond stating "worst-case scenario" constructs were tested.
• Data Provenance: Not applicable for an AI study. The testing is non-clinical/bench testing performed on physical devices.

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 physical dental implant, not an AI algorithm requiring expert ground truth for image interpretation or diagnosis.

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

Not applicable. This is a physical dental implant, not an AI algorithm study requiring adjudication of expert opinions.

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 physical dental implant, not an AI algorithm. The text mentions "MR Environment Condition" but this refers to Magnetic Resonance (MR) safety, not Multi-Reader Multi-Case (MRMC) studies.

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

Not applicable. This is a physical dental implant, not an AI algorithm.

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

Not applicable. For this device, "ground truth" would be established by physical measurements, material properties, and biological responses according to established standards (e.g., ISO, ASTM, biocompatibility guidelines), rather than expert consensus on diagnostic images or pathology.

8. The sample size for the training set

Not applicable. This is a physical dental implant, not an AI algorithm that undergoes training.

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

Not applicable. This is a physical dental implant, not an AI algorithm.

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