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degenerative, post-traumatic or rheumatoid arthritis;
avascular necrosis of the femoral condyle;
post-traumatic loss of joint configuration, particularly when there is patellofemoral erosion, dysfunction or prior patellectomy;
moderate valgus, varus or flexion deformities;
treatment of fractures that are unmanageable using other techniques.
This device may also be indicated in the salvage of previously failed surgical attempts.
This system is to be used for cemented applications.

Device Description

This submission is to request clearance for a line extension to the current patella product line to include a highly cross linked polyethylene patella infused with pharmaceutical grade alphatocopheral.

AI/ML Overview

Here's a breakdown of the acceptance criteria and the study information based on the provided text, recognizing that this document describes a medical device (a knee implant patella), not an AI algorithm. Therefore, many of the requested fields pertinent to AI algorithm evaluation (like MRMC, ground truth establishment for training data, expert consensus, etc.) will not be applicable.

Device Name: Highly Cross Linked Patella with Vitamin E

Device Type: Knee joint patellofemorotibial polymer/metal/polymer semi-constrained cemented prosthesis.

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria (Implied by Predicate Device Comparison & Non-Clinical Testing)	Reported Device Performance
Mechanical Performance: Device must perform under expected conditions, demonstrating adequate strength, durability, and resistance to wear, push-out, lever-out, torsion, and impact.	Demonstrated through non-clinical mechanical characterization testing, push-out, lever-out, torsion, Izod impact, small punch, tensile testing, and wear testing.
Material Characterization: Material properties (highly cross-linked polyethylene with Vitamin E) must be comparable to previously cleared materials and suitable for implantation.	Material characterization testing was not repeated as identical material was cleared in K091956. This implies the material met prior acceptance criteria.
Biocompatibility/Safety: No toxicological response or cytotoxicity.	Demonstrated through animal implant for toxicological response and cytotoxicity testing.
Design Equivalence (absence of certain tests): Absence of need for subluxation and contact stress testing due to design equivalence to predicate devices.	Found not to be required due to design equivalence.
Substantial Equivalence: Features (design, materials, indications, sterilization, packaging, intended use) must be comparable to legally marketed predicate devices.	Stated as meeting the criteria for substantial equivalence to predicate devices (K932246, K905613, K100900, K091956). FDA confirmed substantial equivalence.

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

Test Set Sample Size: Not applicable. This submission relies on non-clinical (bench) testing and comparison to predicate devices, not on a clinical test set with patient data or an algorithm's performance on a dataset.
Data Provenance: Not applicable. The "data" comes from engineering and laboratory tests, not patient data sets.

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

Not applicable. Ground truth, in the context of an AI algorithm, usually refers to labels established by human experts on a dataset. For this medical device, performance is established through physical and material testing, not expert-labeled data.

4. Adjudication Method for the Test Set

Not applicable. There was no "test set" in the context of human interpretation or algorithm output requiring adjudication.

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 medical device (implant), not an AI-powered diagnostic or assistive tool. No MRMC study was performed.

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

Not applicable. This is a physical medical device, not an algorithm.

7. The Type of Ground Truth Used

Engineering/Material Science Ground Truth: Performance was judged against established engineering standards, material specifications, and the performance characteristics of previously cleared predicate devices. Examples include:
- Quantifiable mechanical properties (e.g., strength, wear rates, impact resistance).
- Biocompatibility standards (e.g., absence of cytotoxicity).
- Comparability to existing devices as defined by design, materials, and intended use.

8. The Sample Size for the Training Set

Not applicable. This is a medical device, not an AI algorithm. There is no concept of a "training set" for physical bench testing.

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

Not applicable. As above, no training set for an AI algorithm was involved. The "ground truth" for the development of the device itself would stem from engineering specifications, industry standards, and clinical needs for knee joint replacement, guiding the design and material selection.

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