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The Optetrak Logic Metaphyseal Cones are indicated for use in skeletally mature individuals undergoing primary surgery for total knee replacement due to osteoarthritis, osteonecrosis, rheumatoid arthritis and/or post-traumatic degenerative problems. They are also indicated for revision of failed previous reconstructions where sufficient bone stock and soft tissue integrity are present.

The augments are intended for press-fit fixation with the proximal tibial or distal femur. The final implant construct is completed by cementing a tibial tray or femoral component in place.

Optetrak Logic Metaphyseal Cones are designed to fill tibial and femoral bone voids during revision or complex primary surgery in the case of severe bone loss. Specifically, Optetrak Logic Metaphyseal Cones are designed to enhance fixation in primary or revision total knee arthroplasty (TKA) patients who have Anderson Orthopaedic Research Institute (AORI) type II and III tibial and femoral defects by providing stability to total knee implants via the metaphysis.

The provided text is a 510(k) premarket notification document for a medical device called "Optetrak Logic Metaphyseal Cones" by Exactech Incorporated. It details the regulatory review process and concludes that the device is substantially equivalent to existing predicate devices.

However, the document does not contain any information about acceptance criteria or a study proving the device meets specific performance criteria in the context of an AI/ML medical device. The text describes the device as knee system augments for total knee replacement and lists non-clinical testing such as fatigue testing, mating analysis, cadaveric implantation, biocompatibility assessment, compressive plastic deformation testing, abrasion resistance, static tensile strength testing, shear resistance, and porous structure characterization. These are typical engineering and material property tests for an orthopedic implant, not studies for an AI/ML-driven device's performance against clinical acceptance criteria.

Therefore, I cannot fulfill the request as the provided text does not contain the necessary information about an AI/ML device study, acceptance criteria, sample sizes for test/training sets, expert involvement, adjudication methods, MRMC studies, standalone performance, or ground truth establishment for such a device.

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