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TheRay Collared and Collarless Total Hip System is indicated for use in skeletally mature individuals undergoing surgery for total hip replacement due to:
• A severely painful and/or disabled joint from osteoarthritis, theumatoid arthritis, avascular necrosis, or congenital hip dysplasia;
· Acute traumatic fracture of the femoral head or neck;
· Failed previous hip surgery including joint reconstruction, arthrodesis, hemiarthroplasty, surface replacement arthroplasty or total hip replacement.

TheRay Collared and Collarless Total Hip System femoral stems are intended for cementless fixation. The acetabular cup is intended for cementless fixation. The porous structured surfaces on the acetabular cup provide biological fixation in a cementless application.

The iNSitu Bipolar Hip System is intended for use in combination with the iNSitu Total Hip System Femoral Stem or TheRay Collared or Collarless Femoral Stem for uncemented primary or revision hemiarthroplasty of the hip. This prosthesis may be used for the following conditions, as appropriate:
· Femoral neck and trochanteric fractures of the proximal femur;
· Osteonecrosis of the femoral head;
· Revision procedures where other devices or treatments for these indications have failed.

TheRay Collared and Collarless Hip System includes the new subject femoral stems, along with previously cleared femoral heads (K161184, K220336), acetabular cups (additively manufactured – K161184 and K191936), acetabular liners (vitamin E polyethylene – K161184), acetabular bone screws (K161184), screw hole covers for the screw holes in the acetabular cups (K161184), and apical hole covers for the acetabular cups (K161184). The subject femoral stem implant features a forged triplaner Ti-6Al-4V ELI substrate and an applied dual coating comprised of plasma-sprayed commercially pure titanium (CPTi) and hydroxyapatite (HA). The collared version of the subject TheRay Femoral Stem features a collar on the medial aspect of the stem above the coating that is designed to seat on the native resected calcar. The collarless version of the subject TheRay Femoral Stem is identical to the collared version, less the medial collar.

The iNSitu Bipolar Hip System has been previously cleared for use in K191297 and consists of a factory assembled UHMWPE (ASTM F648) liner in a cobalt chrome (ASTM F75) outer shell, and UHMWPE (ASTM F648) retention ring with a Ti-6Al-4V ELI (ASTM F136) spring. These Bipolar Heads include outer diameters ranging from 38 to 60 mm, in 1 mm increments, to properly fit the patient anatomy. The smaller Bipolar Heads (38 to 43 mm) have an inner diameter that mates with a 22mm diameter Femoral Head; the larger Bipolar Heads (44 to 60 mm) have an inner diameter that mates with a 28 mm diameter Femoral Head. The iNSitu Bipolar Hip System may be used in conjunction with the subject TheRay Collared and Collarless Hip System Femoral Stems.

The provided text describes a medical device, "TheRay Collared and Collarless Femoral Stem," and its submission for FDA clearance. However, it does not include information about acceptance criteria or a study proving the device meets them in the context of an AI/ML enabled device.

The document is a 510(k) summary for a hip implant (a physical medical device), not a software device or an AI/ML product. The performance testing mentioned (Range of Motion, Distal stem fatigue, Neck fatigue, Femoral head disassembly, Biocompatibility) are standard tests for orthopedic implants, ensuring their mechanical integrity and safety for human implantation.

Therefore, I cannot provide the requested information regarding acceptance criteria and a study proving an AI device meets them because the document describes a traditional medical device, not an AI/ML-enabled one.

To directly answer your request based on the absence of the information in the provided text:

1. A table of acceptance criteria and the reported device performance: Not applicable. The document describes a physical hip implant, not an AI/ML device, and therefore does not have performance metrics like sensitivity, specificity, or F1-score with corresponding acceptance criteria typically associated with AI.
2. Sample size used for the test set and the data provenance: Not applicable. This information is relevant for AI/ML validation datasets. The document mentions "Extensive preclinical performance testing" but does not detail sample sizes in the context of data for an AI model.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. "Ground truth" in this context usually refers to expert-labeled data for AI model training/validation. The document does not describe such a process.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable. This refers to methods for resolving discrepancies in expert labeling for AI ground truth. The document does not describe such a process.
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 specific to AI-assisted diagnostic or decision-making tools to evaluate human performance with and without AI. The device described is a physical hip implant.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable. This refers to the performance of an AI algorithm on its own. The device described is a physical hip implant.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable. "Ground truth" here refers to data labeling for AI. For a hip implant, "ground truth" would relate to real-world clinical outcomes and mechanical performance, which are evaluated through different types of studies (e.g., clinical trials, bench testing per ISO standards).
8. The sample size for the training set: Not applicable. This refers to the dataset used to train an AI model.
9. How the ground truth for the training set was established: Not applicable. This refers to the process of creating labeled data for AI model training.

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