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The Align Radial Head System and accessories are designed specifically for:

• Replacement of the radial head for degenerative or post-traumatic disabilities presenting pain, crepitation, and decreased motion at the radio-humeral and/or proximal radio-ulnar joint with:
  • o Joint destruction and/or subluxation.
  • o Resistance to conservative treatment.
• Primary replacement after fracture of the radial head.
• Symptomatic sequelae after radial head resection.
• Revision following failed radial head arthroplasty.

The system is intended for press fit use.

The subject Align Radial Head System and the predicate Align Radial Head System (K172688) are a radial head prosthesis and instrumentation platform that is designed to orient the radial head perpendicular to the axis of forearm rotation. It consists of cobalt chrome modular heads in different sizes with cobalt chrome locking screws, titanium alloy stems, necks, and specialized instrumentation.

The provided text is a 510(k) summary for the ALIGN Radial Head System, which is a medical device for radial head replacement. This document primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed study proving the device meets specific acceptance criteria in the context of AI/ML performance.

Therefore, many of the requested sections related to AI/ML study components (such as sample sizes for test and training sets, expert qualifications, ground truth establishment, MRMC studies, or standalone performance) are not applicable to this type of regulatory submission and are not present in the provided text.

The "acceptance criteria" discussed in this document refer to the criteria for demonstrating substantial equivalence to a predicate device, primarily through mechanical testing to ensure safety and effectiveness.

Here’s the information based on the provided text, with "N/A" for sections not covered by this type of submission:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

N/A. This document describes mechanical testing of a physical medical device, not a study involving a "test set" of data or patient provenance in the context of an AI/ML device. The testing would involve physical samples of the device components. The document does not specify the number of samples used for static and fatigue compression testing.

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)

N/A. Not applicable to mechanical testing of a physical implant.

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

N/A. Not applicable to mechanical testing of a physical implant.

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

N/A. Not applicable as this is not an AI/ML device.

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

N/A. Not applicable as this is not an AI/ML device.

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

For the mechanical testing, the "ground truth" would be established engineering standards and specifications for material strength, fatigue life, and structural integrity under simulated physiological loads, which are used to determine if the device performs equivalently to the predicate. This document does not elaborate on specific standards or the methodology of establishing "ground truth" beyond stating "mechanical testing" was performed.

8. The sample size for the training set

N/A. Not applicable as this is not an AI/ML device.

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

N/A. Not applicable as this is not an AI/ML device.

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