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510(k) Data Aggregation
(90 days)
The INBONE Total Ankle System and INFINITY Total Ankle System are indicated for patients with ankle joints damaged by severe rheumatoid, post-traumatic, or degenerative arthritis.
The INBONE Total Ankle System and INFINITY Total Ankle System are additionally indicated for patients with a failed previous ankle surgery.
CAUTION: In the United States, the ankle prosthesis is intended for cement use only.
The subject INBONE™ and INFINITY™ Total Ankle Systems are fixed-bearing, bone-sparing ankle replacement prostheses that restore mobility to a failing ankle joint. Both the INFINITY and INBONE systems include three components (tibial trays with or without stems, poly inserts, and talar domes) that are assembled together to create the two-piece prosthesis.
This is a 510(k) premarket notification for a medical device (INFINITY and INBONE Total Ankle Systems) and does not contain the detailed information typically found in a study proving a device meets specific acceptance criteria in the context of AI/ML or diagnostic performance. Instead, it demonstrates substantial equivalence to predicate devices, focusing on design, materials, and non-clinical performance.
Therefore, many of the requested points cannot be answered from the provided text. I will address the points that can be inferred or directly stated.
1. A table of acceptance criteria and the reported device performance
The document does not present acceptance criteria or reported device performance in the form of a table with numerical values for metrics like sensitivity, specificity, or image quality, as would be expected for a diagnostic or AI-driven device. Instead, it lists non-clinical tests performed to demonstrate substantial equivalence to predicate devices.
| Acceptance Criteria (Non-Clinical Tests) | Reported Device Performance (as demonstrated by testing) |
|---|---|
| Chemical Analysis | Demonstrated equivalence to predicate devices |
| Compressive Strength | Demonstrated equivalence to predicate devices |
| Shear and Tensile Strength | Demonstrated equivalence to predicate devices |
| MRI Safety Analysis | Minimal risk to patients in an MR environment (MR Conditional) |
| Direct Metal Laser Sintering (DMLS) Process Validation | Demonstrated equivalence to predicate devices (Performance Qualification, Mechanical validation, Microstructure, Powder Bed Position Validation) |
| Endotoxin (<20EU/device) | Demonstrated equivalence to predicate devices |
2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)
Not applicable. This submission relies on non-clinical bench testing and comparison to predicate devices, not clinical or image-based test sets.
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. No expert review for ground truth was conducted as no clinical efficacy/diagnostic study was performed.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
Not applicable. No clinical efficacy/diagnostic study was performed, thus no adjudication method was used.
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. No MRMC study was done, as this is not an AI-assisted diagnostic device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a medical implant, not a standalone algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
Not applicable. The "ground truth" equivalent for this type of submission is the established performance and safety profile of the predicate devices based on their historical use and regulatory clearances, and the results of the non-clinical bench tests demonstrating similar physical and mechanical properties.
8. The sample size for the training set
Not applicable. There is no AI/ML component, so no training set was used.
9. How the ground truth for the training set was established
Not applicable. There is no AI/ML component, so no training set or associated ground truth establishment process was used.
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