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The ET Abutment System are indicated for use with ET Dental Implants to provide support to prosthetic restoration such as crowns, bridges and overdentures in partially or fully edentulous patients.

The ET Abutment System are indicated for use with ET dental implants to provide support to prosthetic restoration such as crowns, bridges and overdentures in partially or fully edentulous patients. Manufactured from medical grade titanium alloy and delivered non-sterilized. The ET Abutments are available in various lengths and diameters; configurations are listed in the table below.

This document describes a 510(k) premarket notification for a medical device called the "ET Abutment System," which is an endosseous dental implant abutment. The primary purpose of a 510(k) submission is to demonstrate substantial equivalence to a legally marketed predicate device, rather than proving safety and effectiveness through de novo clinical trials.

Therefore, the submission does not contain information about specific "acceptance criteria" for an AI algorithm's performance, nor does it detail a study proving such a device meets these criteria in the typical sense of AI/ML performance evaluation. The "studies" referenced are non-clinical bench tests demonstrating the physical and material properties of the dental abutments are comparable to existing, legally marketed devices.

Based on the provided text, here's an analysis of the "acceptance criteria" and "proof" in the context of this 510(k) submission:

The acceptance criteria and proof fundamentally revolve around demonstrating substantial equivalence to predicate devices, not performance against a specific clinical metric for an AI algorithm.

Missing Information:

The document concerns a physical dental device (abutment system), not an AI/ML powered device. As such, the concept of "acceptance criteria" for AI performance, clinical study design for AI (sample size for test/training sets, data provenance, expert ground truth, adjudication, MRMC studies, standalone performance, etc.) are not applicable to this submission. The FDA letter confirms the device type: "Endosseous Dental Implant Abutment."

However, to address the prompt's implied need for "acceptance criteria" and "studies" as they relate to this specific device (dental abutment), I will interpret the request within the context of a 510(k) submission for a non-AI medical device.

1. Table of Acceptance Criteria and Reported Device Performance (as interpreted for a Dental Abutment System)

In a 510(k) submission for a dental abutment, "acceptance criteria" are typically defined by demonstrating that the proposed device has the same technological characteristics and similar performance to legally marketed predicate devices, or that differences do not raise new questions of safety and effectiveness. The "reported device performance" comes from non-clinical bench testing.

2. Sample Size Used for the Test Set and Data Provenance

Since this is a physical medical device submission and not an AI/ML algorithm:

• Sample Size for Test Set: Not applicable in the context of an AI test set. For physical device testing, the sample sizes would be determined by the relevant ISO standards (e.g., ISO 14801 for fatigue testing). These specific numbers are not detailed in the summary but are typically part of detailed test reports that support the conclusion of substantial equivalence.
• Data Provenance: The data comes from non-clinical testing (bench tests) performed to standard specifications (e.g., ISO 14801). The "ET Abutment System are contract manufactured by the predicate device manufacturer," implying the manufacturing process and potentially some historical performance data are shared or directly comparable.
  • Country of Origin: Not specified for the non-clinical test data itself, but the applicant (Hiossen Inc.) is in Fairless Hills, Pennsylvania, USA. The predicate manufacturer (Osstem Implant Co., Ltd.) is generally based in South Korea, suggesting potential international collaboration or shared manufacturing data.
  • Retrospective or Prospective: Not applicable in the context of patient data. The non-clinical tests would be conducted prospectively on newly manufactured devices.

3. Number of Experts Used to Establish Ground Truth and Qualifications of Experts

• This concept is not applicable as this is not an AI/ML diagnostic or image analysis device that requires expert labeling or interpretation for "ground truth." The "ground truth" here is the adherence to material specifications, dimensional tolerances, and performance under specific mechanical and biological test conditions as defined by international standards.

4. Adjudication Method for the Test Set

• This concept is not applicable as there is no "test set" in the sense of clinical cases requiring interpretation or adjudication by multiple readers/experts. Performance is based on mechanical, material, and sterilization testing against predefined standards.

5. Multi Reader Multi Case (MRMC) Comparative Effectiveness Study

• Not applicable. This type of study is for evaluating human performance with or without AI assistance, typically in image interpretation or diagnosis. This submission is for a physical dental implant component. The document explicitly states: "No clinical performance report(s) is being submitted."

6. Standalone (i.e., algorithm only without human-in-the-loop performance) Study

• Not applicable. This pertains to AI algorithm performance.

7. Type of Ground Truth Used

• The "ground truth" for this device's acceptance is based on engineering standards, material specifications, and performance data from validated non-clinical bench tests. This includes:
  • ASTM (American Society for Testing and Materials) standards for materials (e.g., ASTM F136 for titanium alloy).
  • ISO (International Organization for Standardization) standards for testing medical devices (e.g., ISO 14801 for fatigue testing of dental implants, ISO 17665-1 for moist heat sterilization).
  • FDA guidance documents (e.g., "Class II Special Controls Guidance Document: Root-form Endosseous Dental Implants and Abutments," "Testing and Labeling Medical Devices for Safety in the Magnetic Resonance (MR) Environment").
  • Direct comparison to the established characteristics and performance of the legally marketed predicate devices.

8. Sample Size for the Training Set

• Not applicable. This concept relates to AI/ML model development. There is no "training set" for a physical dental abutment. The device's design and manufacturing rely on established engineering principles and prior knowledge from the predicate device.

9. How the Ground Truth for the Training Set was Established

• Not applicable. Again, this refers to AI/ML model training. The "ground truth" for developing a physical device is derived from engineering design principles, material science, and the performance history of similar devices.

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