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The Multi-unit Abutment, Multi-unit Angled Abutment is intended to the maxillary or mandbular arches for the purpose providing prosthetic support for dental restorations (Crown, bridges, and overdentures) in partially or fully edentulous individuals.

The Multi-unit Abutment, Multi-unit Angled Abutment of a dental implant system to provide support for prosthetic restorations. It is attached to the implants and intended to be used in the upper or lower jaw and used for supporting tooth replacements to restore patient's chewing function. The Multi-unit Abutment, Multi-unit Angled Abutment consists of straight & angled abutments and prosthetic components in varying sizes for single & multiple unit screw retained restorations.

Here's an analysis of the provided text regarding the acceptance criteria and study for the dental device:

Acceptance Criteria and Device Performance for MegaGen Implant Co. Ltd.'s Multi-unit Abutment, Multi-unit Angled Abutment (K203808)

This submission is a 510(k) premarket notification for dental implant abutments. The primary method of demonstrating acceptance and substantial equivalence is through comparison to predicate devices and performance testing according to established international standards (ISO 14801) and FDA guidance documents. There is no AI component or related acceptance criteria described in this document.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are not explicitly stated in numerical thresholds within the document, as the submission focuses on demonstrating substantial equivalence to existing predicate devices. The performance is assessed by confirming that the subject device meets the requirements of relevant standards, implying that its performance is comparable to or better than the predicate devices.

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

The document does not explicitly state the sample sizes used for the non-clinical performance (bench) testing. Similarly, the data provenance (e.g., country of origin, retrospective/prospective) for these tests is not specified beyond indicating they were performed in accordance with international standards. Given it's a Korean manufacturer, the testing likely occurred in Korea or at facilities that adhere to these international standards.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This section is not applicable as the device is a dental implant abutment, and the document describes a 510(k) submission based on substantial equivalence and non-clinical bench testing. There is no mention of a "ground truth" derived from expert consensus on patient cases for evaluation in the context of diagnostic or interpretive performance.

4. Adjudication Method (e.g., 2+1, 3+1, none) for the Test Set

This section is not applicable. Adjudication methods like 2+1 or 3+1 are typically used in clinical studies where expert readers independently assess cases and discrepancies are resolved. The submission relies on bench testing and comparison to predicates, not clinical interpretation studies.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done

No, an MRMC comparative effectiveness study was not done. This type of study involves human readers interpreting cases, often with and without AI assistance, to measure diagnostic performance. The submission pertains to a physical dental device (abutments) and does not involve AI or human-in-the-loop performance evaluation.

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

No, a standalone (algorithm only) performance study was not done. This concept is specific to AI/CADe (Computer-Assisted Detection/Diagnosis) devices. The submitted device is a mechanical component, not an algorithm.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

The concept of "ground truth" as typically defined for diagnostic or AI studies (expert consensus, pathology, outcomes data) does not apply here. For this device, the "ground truth" for demonstrating acceptance is adherence to engineering specifications, material standards, and performance benchmarks established by international standards (ISO 14801) and FDA guidance documents. The acceptable performance of the predicate devices acts as the benchmark.

8. The Sample Size for the Training Set

Not applicable. The device is a physical product (dental implant abutment). There is no "training set" in the context of machine learning or AI algorithms for this type of submission.

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

Not applicable. As there is no training set for an AI algorithm, there is no ground truth to be established for it.

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The Magicore System is intended to replace missing teeth to restore chewing function. The Magicore System can be placed in support of single or multiple-unit restorations including; cement retained, screw retained, or overdenture restorations, and terminal or immediate abutment support for fixed bridgework. This system is for one or two stage surgical procedures. This system is intended for delayed loading.

This submission is to add new fixtures and abutments to the previously cleared device, Magicore System (K201981), Magicore II System (K201621), Magicore II System (K192197), and Magic UCLA Abutment System (K202418).
The fixtures and abutments in this system are below:

1. Fixture

• Magicore
• Magicore (Cutting Edge)

2. Abutment

• Magic Multiunit Abutment (Screw type - Hex, Non-Hex & Cemented type - Hex, Non-Hex)
• Magic Multiunit UCLA Cylinder
• Magic Multiunit Cap
• Magic Abutment (Screw type Hex, Non-Hex & Cemented type Hex, Non-Hex)
• Magic UCLA Cement Retained Type (Hex, Non-Hex)
• Magic Cylinder (Hex, Non-Hex, Post)
• Magic Multiunit Cylinder (Hex, Non-Hex, Post)
• Magicore Healing Cap
• Magicore Healing Cap Screw
• Cylinder Screw
  An endosseous dental implant is a device made of a material such as Ti 6AL 4V Eli (Conforming to ASTM Standard F-136). The Magicore System consists of dental implants, Abutments, cylinders, caps and screws for use in one or two-stage dental implant placement and restorations.
  The implant-Abutment connection is tight and precise fitting with internal hex and Morse taper bevel. The surface of the Magicore implant is treated with RBM (Resorbable Blasted media).

The provided text describes the regulatory submission for the Magicore System, an endosseous dental implant system, and its determination of substantial equivalence (SE) to previously cleared predicate devices. It does not contain information about acceptance criteria or a study proving the device meets those criteria in the context of an AI/ML-driven medical device performance study (e.g., accuracy, sensitivity, specificity, or clinical outcomes).

The document is a 510(k) summary for a dental implant system. The "acceptance criteria" here refers to demonstrating substantial equivalence to a predicate device, as required for FDA 510(k) clearance, rather than performance metrics of an AI model. The studies mentioned are primarily non-clinical (material, mechanical, sterilization, biocompatibility testing) and are leveraged from predicate devices or performed to show equivalence in basic structural and material properties. There is no mention of an AI/ML component in the Magicore System.

Therefore, I cannot provide the requested information about acceptance criteria for AI performance, sample sizes for AI test sets, expert ground truth establishment, MRMC studies, or standalone algorithm performance, as these concepts are not applicable to the provided document.

The document discusses physical and material properties of a dental implant system, comparing them to legally marketed predicate devices to establish substantial equivalence.

However, if we were to interpret "acceptance criteria" in the context of this device's type (dental implants), it would refer to regulatory requirements and engineering performance specifications needed to demonstrate safety and effectiveness. Based on the provided text, here's what can be inferred about the "study" for this traditional medical device type regarding its acceptance for market clearance:

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

Since this is a 510(k) submission for a non-AI/ML dental implant device, the "acceptance criteria" are primarily related to substantial equivalence to predicate devices, material safety, mechanical performance, and sterility. The document outlines comparisons to predicate devices for various characteristics, implying these characteristics meeting equivalent or acceptable standards are the acceptance criteria.

2. Sample sized used for the test set and the data provenance:

• Sample Size: Not applicable in the context of an AI/ML test set. The document refers to non-clinical testing (e.g., sterilization, biocompatibility, fatigue, shelf-life). These tests typically involve a defined number of device units or material samples per standard requirements, not "patient data samples." Specific numbers of units tested are not detailed in this summary, but the tests themselves rely on established sample size methodologies for their respective standards.
• Data Provenance: Not applicable for patient data. The "data" provenance in this context refers to the source of non-clinical test reports, which are largely leveraged from previous 510(k) submissions for predicate devices by the same manufacturer (e.g., K201981, K201621, K192197, K202418, K152520, K173120). These are lab-based tests, not human study data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable. This pertains to establishing ground truth for AI model training/testing which is not relevant here. For dental implants, the "ground truth" for material, mechanical, and biological properties is established through adherence to recognized international standards (e.g., ASTM, ISO) and laboratory testing protocols.

4. Adjudication method for the test set:

• Not applicable. This refers to consensus methods for AI/ML ground truth, which is not relevant to this device's clearances.

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 type of study is relevant for diagnostic imaging AI. The document describes a physical dental implant.

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

• Not applicable. No AI algorithm is involved.

7. The type of ground truth used:

• For physical and material properties: The ground truth is based on established engineering principles, material science definitions, recognized industry standards (e.g., ASTM, ISO), and performance specifications determined through laboratory testing (e.g., mechanical strength, biocompatibility, sterility assurance levels).
• For substantial equivalence: The "ground truth" for the FDA's decision is the demonstration that the device's characteristics (intended use, design, materials, etc.) are as safe and effective as a legally marketed predicate device.

8. The sample size for the training set:

• Not applicable. There is no AI model to train.

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

• Not applicable. There is no AI model to train.

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