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The Acumed Anatomic Radial Head System, the Acumed Anatomic Radial Head Long Stems, the Acumed ARH Slide-Loc™ System, and accessories are designed specifically for:

1. Replacement of the radial head for degenerative or post-traumatic disabilities presenting pain, crepitation, and decreased motion at the radiohumeral and/or proximal radio-ulnar joint with: joint destruction and/or subluxation, resistance to conservative treatment.
2. Primary replacement after fracture of the radial head.
3. Symptomatic sequelae after radial head resection.
4. Revision following failed radial head arthroplasty.
   The device is intended to be press fit or cemented.

The Acumed Anatomic Radial Head Long Stems and the Acumed ARH Slide-Loc "" System include modular heads and stems with accessories to anatomically replace the proximal portion of the radius and restore the natural articulation of the radial head with the radial notch of the ulna and capitulum of the distal humerus.

The provided document (K131845) is a 510(k) summary for the Acumed Anatomic Radial Head Long Stems and ARH Slide-Loc™ System, which are elbow hemi-prostheses. It primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study with specific acceptance criteria and performance metrics in the way one might see for a diagnostic AI device.

Therefore, many of the requested elements regarding acceptance criteria, study design, ground truth, and expert involvement are not applicable or cannot be extracted from this type of regulatory submission. This document describes non-clinical (bench) testing to characterize the strength of the device.

Here's an attempt to answer the questions based on the provided text, indicating where information is not applicable (N/A) or not provided (NP):

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

The document does not specify quantitative acceptance criteria (e.g., minimum tensile strength, fatigue life cycles) or specific numerical performance results from the non-clinical tests. It broadly states that the devices "underwent static and cyclic load testing to characterize their strength." The comparison table focuses on material, dimensions, and design features, not performance metrics related to acceptance criteria.

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

• Sample Size for Test Set: Not specified. This refers to the number of devices or components tested in the static and cyclic load assessments.
• Data Provenance: Not applicable in the context of device mechanical testing. These tests are typically performed in a laboratory setting by the manufacturer or a contract testing facility. It's not clinical data from patients.

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)

• Number of Experts: Not applicable. For mechanical testing of an elbow prosthesis, "ground truth" is not established by medical experts interpreting images or patient outcomes. It's determined by engineering standards and measurements.
• Qualifications of Experts: Not applicable.

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

• Adjudication Method: Not applicable. Adjudication methods like 2+1 or 3+1 are used for reconciling discordant interpretations in clinical studies or for establishing ground truth from multiple human readers. This is mechanical bench testing.

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

• MRMC Study: No. This document describes a medical device (prosthesis), not an AI diagnostic tool.
• Effect size of AI improvement: Not applicable.

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

• Standalone Performance: No. This device is an implant, not an algorithm.

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

• Type of Ground Truth: For mechanical testing, the "ground truth" would be established by the physical properties of the materials and the mechanical performance of the device as measured against engineering standards (e.g., ASTM standards for implants). The document refers to "static and cyclic load testing to characterize their strength," implying that the measured mechanical properties are the "ground truth" for evaluating the physical integrity of the device.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable. This is not an AI/machine learning study requiring a training set.

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

• Ground Truth Establishment for Training Set: Not applicable.

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The Acumed Anatomic Radial Head System is indicated for use in:

1. 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: joint destruction and/or subluxation, resistance to conservative treatment.
2. Primary replacement after fracture of the radial head.
3. Symptomatic sequelae after radial head resection.
4. Revision following failed radial head arthroplasty

The Acumed Anatomic Radial Head System includes modular heads and stems with accessories to anatomically replace the proximal potion of the radius and restore the natural articulation of the radial head with the radial notch of the ulna and capitulum of the distal humerus.

This document is a 510(k) summary for the Acumed Anatomic Radial Head System, a medical device for elbow replacement. It is important to note that a 510(k) submission generally focuses on demonstrating substantial equivalence to a predicate device, rather than proving performance against specific acceptance criteria through detailed studies in the way an AI/ML device submission would.

Therefore, many of the requested elements for an AI/ML device performance study are not applicable or not explicitly detailed in this type of submission.

Here's the breakdown based on the provided text:

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

• Acceptance Criteria: Not explicitly stated in terms of quantitative performance metrics for the device itself. For a 510(k) submission like this, the primary "acceptance criterion" is demonstrating substantial equivalence to legally marketed predicate devices. This typically involves showing similar intended use, technological characteristics, and safety and effectiveness profiles.
• Reported Device Performance: No specific quantitative performance metrics are reported. The submission states, "An assessment of performance data is not applicable. A discussion of clinical and non-clinical tests is not applicable." This indicates that the substantial equivalence was primarily based on design and material similarities to the predicates, rather than new performance testing data detailed in this summary.

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

• Not Applicable. This submission does not describe a "test set" for performance evaluation in the context of an AI/ML device. It focuses on the substantial equivalence of the physical implant itself to existing devices.

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)

• Not Applicable. There is no "test set" or ground truth establishment in this context.

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

• Not Applicable. No test set for performance evaluation is described.

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 prosthetic device, not an AI/ML diagnostic or assistive tool.

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

• Not Applicable. This is a physical prosthetic device.

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

• Not Applicable. The "ground truth" for this device's approval is its substantial equivalence to predicate devices, supported by its design, materials, and intended use aligning with those already found safe and effective.

8. The sample size for the training set

• Not Applicable. There is no training set for an AI/ML model in this submission.

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

• Not Applicable. There is no training set for an AI/ML model in this submission.

Summary of the document's approach to demonstrating safety and effectiveness:

The submission for the Acumed Anatomic Radial Head System demonstrates substantial equivalence to predicate devices (Avanta Radial Head Implant K002644 and Wright Medical Inc. Modular Radial Head K991915). The key arguments for substantial equivalence are:

• Intended Use: The indications for use are similar to the predicate devices.
• Technological Characteristics: The device uses similar materials (cobalt alloy head, titanium alloy stem) that have been successfully used in numerous implant prostheses, and its elliptical shape is aligned with anatomical replacement principles. The submission explicitly states, "There are no technological characteristics that raise new issues of safety or effectiveness."
• Performance Data/Testing: The submitter explicitly states that "An assessment of performance data is not applicable. A discussion of clinical and non-clinical tests is not applicable." This is typical for a 510(k) where substantial equivalence is established through design, materials, and intended use comparison, implying that the safety and effectiveness are established by the long-standing use and prior approval of the predicate devices with similar characteristics.

In essence, for this type of medical device (a mechanical implant), the "acceptance criteria" and "proof" primarily revolve around demonstrating that it is fundamentally the same as or very similar to devices already on the market and has no new safety or effectiveness concerns.

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