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The MDS Injection Screw is intended for the fixation of bone fractures and bone reconstructions of the humerus. The MDS Injection Screws can be used to deliver injectable bone void fillers to a surgical site and are compatible with applicable MDS plating systems.

Miami Device Solutions (MDS) Injection Screws enable fixation of simple and complex fractures of the humerus. The MDS Injection Screws are only to be used in combination with compatible MDS 3.5T plating systems in the humerus (Proximal Humerus Plating System, K141493/K161058; MDS Plating System, K172786). When inserted through a 3.5T plate screw hole, injection screw placement is possible at any angle within a 40° cone. MDS Injection Screws can be used with or without bone void fillers. Fenestrations along the screw length allow bone void filler delivery directly into the surgical site.

This document (K173556) is a 510(k) premarket notification for a medical device called the "Injection Screw." It does not contain information about acceptance criteria or a study proving the device meets them in the context of an AI/ML software. Instead, it demonstrates substantial equivalence to predicate devices through non-clinical performance testing.

Therefore, I cannot answer the questions as they relate to AI/ML device acceptance criteria and studies. The device in this document is a physical medical implant (a bone screw), and the "performance data" refers to mechanical testing.

However, I can provide the information available in the document regarding the device's technical validation:

1. Table of Acceptance Criteria and Reported Device Performance
This document does not specify "acceptance criteria" in the typical sense of a target metric for an AI/ML system (e.g., accuracy, sensitivity, specificity).
Instead, it references industry standards and internal testing to demonstrate the physical device's mechanical properties and functionality.

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/provided for an AI/ML context. The document refers to "non-clinical (laboratory/performance) testing" and "Cadaver Lab" for functional testing of the physical screw. Specific sample sizes for mechanical tests would relate to the number of screws tested, and "cadaver lab" would refer to the number of cadaveric specimens used. These details are not elaborated in the 510(k) summary.

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. This is a physical device, and its ground truth is established through engineering and materials science principles and testing, not expert consensus on interpretations.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. This concept is relevant for expert review in diagnostic studies, not for the mechanical testing of a bone screw.

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 physical device, not an AI/ML diagnostic system.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a physical device, not an algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
The "ground truth" for this device's performance is based on established engineering principles, material science data, and mechanical testing results compliant with industry standards like ASTM F543. For the BVF delivery aspect, it refers to "cadaver lab" testing, which implies direct observation and measurement of the physical phenomenon.

8. The sample size for the training set
Not applicable. This is a physical device, and the concept of "training set" is for AI/ML models.

9. How the ground truth for the training set was established
Not applicable.

In summary: The provided document is for a traditional physical medical device (bone screw) and addresses its substantial equivalence through non-clinical performance and engineering analysis, not through the evaluation of an AI/ML algorithm. Therefore, many of the requested details pertaining to AI/ML device validation are not present or applicable.

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