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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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The Flow-Screw is intended for the fixation of bone fractures and bone reconstructions. When used for these indications, the Flow-Screw can also be used to deliver injectable bone void fillers to a surgical site.

The Flow-Screw is cannulated and available in fully and partially threaded designs in various lengths. The Flow-Screw is fenestrated along its length which allows it to be used as a delivery system for injectable bone void fillers. The Flow-Screw implants are made of titanium alloy (Ti-6Al-4V) conforming to ASTM F136 or stainless steel conforming to ASTM F138 or ASTM F2229.

The provided text describes a medical device called the "Flow-Screw" and its substantial equivalence to predicate devices, but it does not contain any information about acceptance criteria or a study that proves the device meets those criteria in the context of an AI/ML product.

The document is a 510(k) premarket notification decision letter from the FDA for a physical medical device (a bone fixation screw), not an AI/ML algorithm. Therefore, the questions related to AI/ML product evaluation (like sample sizes for test/training sets, expert ground truth, MRMC studies, standalone performance, etc.) are not applicable to this document.

The "Substantial Equivalence" section mentions "Mechanical Performance" and "BVF Delivery" as criteria, stating:

• Mechanical Performance: "Mechanical testing demonstrates the substantial equivalence of the Flow-Screw relative to the identified predicates when subjected to static compression bending loads."
• BVF Delivery System: "The qualification testing (i.e., Injectability Testing, Experimental Void Fill Imaging Studies, Static Extraction Torque, BVF Characterization) was performed with ETEX Beta-bsm and CarriGen (K062630, K072355, K090242, K101557)"

However, these are not quantitative acceptance criteria in the format requested, nor do they detail the specifics of such studies as would be done for an AI/ML device.

Therefore, I cannot provide the requested information because the document describes a physical medical device and not an AI/ML product.

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The Flow-Nail is intended to treat stable and unstable proximal fractures of the femur including pertrochanteric, intertrochanteric, and high subtrochanteric fractures and combinations of these fractures. The Flow-Nail can also be used to deliver injectable bone void fillers to a surgical site.

The Flow-Nail is a dynamic compression trochanteric nail system and includes an intramedullary nail, a sliding fenestrated lag screw, anti-rotation screws, a cap and accompanying surgical instruments. The Flow-Nail components are made of titanium alloy (Ti-6Al-4V) conforming to ASTM F136.

Acceptance Criteria and Study for Flow-Nail (K140601)

The Flow-Nail is an intramedullary fixation rod intended to treat stable and unstable proximal femur fractures and to deliver injectable bone void fillers. The device's substantial equivalence to predicate devices was established through a comparison of various attributes, including mechanical performance.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance for Test Set

The provided document (K140601 510(k) Summary) does not explicitly detail the sample size or data provenance (e.g., country of origin, retrospective/prospective) for the test set used in the mechanical performance studies. The study primarily relies on a comparative mechanical testing approach rather than clinical trial data.

3. Number of Experts and Qualifications for Ground Truth of Test Set

This type of submission (510(k) for an intramedullary fixation rod) does not typically involve human expert adjudication for a "test set" in the context of clinical outcomes or imaging classification. The evaluation is based on engineering and material science standards and physical testing. Therefore, the concept of "experts establishing ground truth" as it would apply to, for example, image interpretation, is not relevant here. The "experts" would be the engineers and scientists conducting the mechanical tests and comparing the results to established standards and predicate device performance.

4. Adjudication Method for the Test Set

Given the nature of the mechanical performance studies for a medical device like an intramedullary nail, there is no adjudication method described or typically applied in the way it would be for a clinical diagnostic study (e.g., 2+1 or 3+1). The evaluation is based on objective measurements from standardized mechanical tests.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not performed. This type of study is relevant for evaluating the impact of AI on human readers in diagnostic tasks, which is not applicable to the Flow-Nail's pre-market submission which focuses on substantial equivalence through mechanical and material testing.

6. Standalone (Algorithm Only Without Human-in-the-Loop) Performance

Not applicable. The Flow-Nail is a physical medical device, not an AI algorithm. Therefore, "standalone performance" in the context of an algorithm without human-in-the-loop is not relevant.

7. Type of Ground Truth Used

The "ground truth" for the Flow-Nail's substantial equivalence is based on engineering standards, material specifications, and the established performance of existing predicate devices through standardized mechanical testing. This includes:

• ASTM F136 for titanium alloy composition.
• Static and dynamic compression bending loads for mechanical performance.
• Qualification testing for BVF delivery (Injectability Testing, Experimental Void Fill Imaging Studies, Static Extraction Torque, BVF Property characterization).

8. Sample Size for the Training Set

Not applicable. The concept of a "training set" is relevant for machine learning algorithms. The Flow-Nail is a physical medical device, and its development and testing do not involve a training set in this context.

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

Not applicable, as there is no "training set" for this physical device.

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