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The OPTETRAK Comprehensive Knee Systems 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. In the USA, the OPTETRAK Comprehensive Knee Systems are indicated for cemented use only, except for the OPTETRAK Logic PS and CR Porous Femoral Components, which are indicated for cemented or cementless use.

Optetrak Advanced Patella implants represent dimensional modifications to "classic" Optetrak patella components. Like the predicate devices, Optetrak Advanced Patella implants are intended for resurfacing the patella during tri-compartmental total knee arthroplasty with other Optetrak and Optetrak Logic components. Optetrak Advanced Patella implants are designed to provide expanded options to help surgeons optimize bone coverage while keeping the same basic features and device compatibility as predicate "classic" Optetrak patella implants.

This document is a 510(k) Pre-Market Notification from the FDA regarding the Exactech Optetrak Advanced Patella device. It is a notification for a medical device, not an AI/ML device, therefore the information requested about acceptance criteria and studies (sample size, data provenance, expert numbers, adjudication, MRMC, standalone, ground truth, training set) is not applicable to this document.

The document discusses the substantial equivalence of the new device to a legally marketed predicate device, primarily based on design and material similarities, and mechanical testing.

Here's what information is available that partially relates to "acceptance criteria" and "study":

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

The document doesn't provide a formal table of quantitative acceptance criteria as would be expected for an AI/ML model's performance metrics (e.g., sensitivity, specificity, AUC). Instead, the "acceptance criteria" can be inferred as demonstrating that the new device does not introduce a new worst-case scenario compared to the predicate device in terms of mechanical performance.

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 is a mechanical device, and the "test set" refers to mechanical testing, not a dataset of patient images or information. The testing conducted is described as "engineering studies."

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. Ground truth, in this context, would involve objective measurements from mechanical testing performed by engineers/technicians, not expert consensus as in AI/ML validation.

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

Not applicable. Adjudication methods like 2+1 or 3+1 are used for resolving disagreements among human readers or annotators in AI/ML studies. This is not relevant to mechanical 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:

Not applicable. This device is an orthopedic implant, not an AI system. Therefore, an MRMC study related to AI assistance is not relevant.

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

Not applicable. This refers to AI algorithm performance.

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

For the mechanical testing, the "ground truth" would be the direct measurements and physical properties observed during the engineering studies (e.g., contact pressure values). There is no "expert consensus" or "pathology" in this context.

8. The sample size for the training set:

Not applicable. There is no AI model or training set for this medical device submission.

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

Not applicable, as there is no training set.

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The OPTETRAK Comprehensive Knee Systems 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 OPTETRAK Comprehensive Knee Systems are contraindicated in patients with active infection, patients without sufficient bone stock to allow appropriate insertion and fixation of the prosthesis, patients without sufficient soft tissue integrity to provide adequate stability, patients with either mental or neuromuscular disorders that do not allow control of the knee joint, and patients whose weight, age, or activity level might cause extreme loads and early failure of the system.

The proposed Exactech Optetrak® Proximal Tibial Spacer (PTS) is a titanium alloy spacer that assembles with the Optetrak® Tibial Tray and the Optetrak® Tibial Insert prostheses to replace the correct amount of joint space. This allows a combined tibial insert/tibial tray thickness comparable to the thickness provided by larger tibial inserts, while maintaining the function and performance of the predicate Optetrak Knee tibial insert/tibial tray assembly. The proposed Optetrak PTS is intended to take the place of inserts larger than 15mm by mating with the thinner inserts (ranging from 9mm to 15mm) to achieve the same total thickness.

Here's a breakdown of the acceptance criteria and the study information for the Exactech Optetrak® Proximal Tibial Spacer, based on the provided 510(k) summary:

This device is a Class II medical device, and the submission is a 510(k) premarket notification. 510(k) submissions typically do not involve clinical trials with human readers or standalone algorithm performance studies in the way AI/ML devices do. Instead, they focus on demonstrating substantial equivalence to a legally marketed predicate device. Therefore, many of the requested categories (like MRMC studies, number of experts, training set size, etc.) are not applicable in this context.

The "study" that proves the device meets the acceptance criteria is primarily non-clinical performance data demonstrating substantial equivalence.

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

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 clinical images or patient data. The "test set" here refers to the specific components of the device that underwent mechanical testing. The document does not specify the exact number of spacers tested, but rather refers to "mechanical tests and engineering analyses."
• Data Provenance: Not applicable. The data is from in-vitro mechanical testing and engineering analyses, not human patient data or images.

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. Ground truth for mechanical performance is established through recognized engineering standards and test methodologies, not expert interpretation of clinical data. This would be determined by qualified engineers and material scientists.
• Qualifications of Experts: Not specified, but implied to be qualified engineers/scientists conducting and interpreting the mechanical tests.

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

• Adjudication Method: Not applicable. This concept applies to human interpretations of clinical data, not mechanical 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, an MRMC comparative effectiveness study was not done. This type of study is not relevant for a prosthetic device demonstrating substantial equivalence via mechanical testing. This device is not an AI/ML imaging device where "human readers" would be involved in interpreting outputs.

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

• Standalone Performance Study: No, a standalone performance study in the context of an algorithm or AI was not done. The performance demonstrated is the standalone mechanical integrity of the device itself.

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

• Type of Ground Truth: The ground truth for this device's performance is based on recognized industry standards and engineering principles for permanent implants. This includes material property specifications, dimensional tolerances, biomechanical load testing parameters, and adherence to established sterilization protocols. The "predicate devices" serve as the benchmark for this ground truth performance.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable. This device is a physical implant, not an AI/ML algorithm that requires a "training set" of data.

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

• How Ground Truth for Training Set was Established: Not applicable, as there is no training set for a physical implant.

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