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1. Non-inflammatory degenerative joint disease including osteoarthritis and avascular necrosis, 2) Rheumatoid arthritis, 3) Correction of functional deformity 4) Treatment of nonunion, femoral neck and trochanteric fractures of the proximal femur with head involvement, unmanageable using other techniques, 5) Revision of previously failed total hip arthroplasty. Intended for cemented and uncemented applications

The ArComXLTM polyethylene liners are manufactured from highly cross-linked polyethylene conforming to ASTM F648 that was previously cleared in K042051. ArComXLTM is available in three designs: MaxRom, Hi-Wall, and 10o. Biolox® delta Ceramic Heads (K042091) are composed of Transition-Toughened-Platelet-Alumina (TTPA). The highly polished spherical surface articulates with the ArComXLTM polyethylene liner acetabular component. The modular head attaches to a metallic femoral stem with a Biomet Type I taper.

This document describes the 510(k) premarket notification for the ArComXL™ Acetabular Liners and Biolox® delta Ceramic Heads. However, it does not contain information about acceptance criteria or a study proving the device meets specific acceptance criteria in the context of an AI/ML medical device.

Instead, this document is a regulatory submission for a traditional medical device (hip joint prostheses) that relies on demonstrating substantial equivalence to previously cleared predicate devices. The "study" mentioned, "Volumetric wear testing," is a non-clinical test performed to support this substantial equivalence.

Therefore, many of the requested fields related to AI/ML device studies, ground truth, and expert evaluation cannot be filled from the provided text.

Here is an attempt to answer the questions based only on the provided text, with many fields noted as "Not applicable" or "Not provided" due to the nature of the document:

1. Table of acceptance criteria and the reported device performance

Explanation: For traditional medical devices like this, acceptance criteria typically involve demonstrating that the new device is as safe and effective as a legally marketed predicate device. This is primarily done through non-clinical testing and comparison of design and materials rather than explicit quantitative clinical performance metrics against pre-defined acceptance thresholds in the way an AI/ML study would. The key acceptance is the FDA's finding of "substantial equivalence."

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 applicable in the context of an AI/ML study. For the volumetric wear testing, the sample size of liners/heads tested is not specified.
• Data Provenance: Not applicable for an AI/ML study. The wear testing is a laboratory-based non-clinical study. Country of origin of the data is not specified (though Biomet is based in the US). Retrospective or prospective does not apply to a pre-clinical bench test.

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. This device is a physical implant, not an AI/ML diagnostic or prognostic tool requiring expert-established ground truth from patient data. The "ground truth" for wear testing is the measured volumetric wear.

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

• Not applicable. This is not a study requiring adjudication of expert interpretations.

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

• No. An MRMC study was not done as this is not an AI/ML device impacting human reader performance.
• Effect size: Not applicable.

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

• Not applicable, as this is not an AI/ML algorithm.

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

• For the non-clinical volumetric wear testing, the "ground truth" is derived from physical measurements of material loss post-wear simulation. This is a physical measurement-based ground truth.

8. The sample size for the training set

• Not applicable. This device does not involve a training set as it's not an AI/ML algorithm.

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

• Not applicable. This device does not involve a training set.

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