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For use with a Toshiba 1.5T EXCELART Vantage or 1.5T Vantage Titan magnetic resoluce scanner to produce diagnostic images of the shoulder that can be interpreted by a trained physician.

The SPEEDER Shoulder coil is designed for use with the 1.5T EXCELART Vantage and the 1.5T Vantage Titan MR Systems manufactured by Toshiba Medical Systems Corporation.

This looks like a 510(k) premarket notification for a medical device called the "SPEEDER Shoulder Coil." The document describes the device, its intended use, and its comparison to predicate devices, ultimately concluding its substantial equivalence.

However, a comprehensive study presenting acceptance criteria and performance data from such a study, as you've requested, is not present within the provided text.

Here's an explanation of why and what information is available:

Explanation:

The provided document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a legally marketed predicate device. For devices like an MR coil (which is essentially a component that helps acquire images, not an AI-powered diagnostic tool), the regulatory review for substantial equivalence typically relies on:

• Engineering and Safety Testing: Demonstrating that the new coil performs equivalently to the predicate coil in terms of image quality metrics (e.g., signal-to-noise ratio, uniformity, spatial resolution) and safety (e.g., heating, electromagnetic compatibility) within a controlled environment, often on phantoms and potentially healthy volunteers.
• Intended Use Comparison: Showing that the intended use of the new device is the same as or very similar to the predicate device.
• Material and Design Comparison: Ensuring that the materials and design choices are similar and do not introduce new risks.

The kind of detailed clinical study with acceptance criteria, ground truth, expert adjudication, and MRMC effectiveness that you've asked for is more typical for software as a medical device (SaMD) or AI-powered diagnostic tools where the algorithm itself is making a diagnostic interpretation or aiding in one.

Based on the provided text, I can answer some of your points, but most of them regarding a clinical performance study with acceptance criteria cannot be addressed:

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

• Not Available. The document does not describe specific acceptance criteria for a performance study nor does it report device performance against such criteria. The focus is on demonstrating substantial equivalence to predicate devices based on design, materials, and intended use.

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/Not Available. The document does not describe a clinical test set in the context of a diagnostic performance study.

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/Not Available. The document does not describe a process for establishing ground truth from expert consensus for a clinical test set.

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

• Not Applicable/Not Available. The document does not describe an adjudication method for a clinical test set.

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

• No. This device is an MR imaging coil, not an AI-powered diagnostic tool. Therefore, an MRMC comparative effectiveness study comparing human readers with and without AI assistance is not relevant and was not performed/reported here.

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

• Not Applicable. This is an MR imaging coil; it is not an algorithm that performs a standalone diagnostic function. Its performance is evaluated on its ability to produce good quality images for human interpretation.

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

• Not Applicable/Not Available. For an MR coil, "ground truth" in the diagnostic sense is not typically established. Performance is usually assessed by technical parameters of image quality in comparison to a predicate device.

8. The sample size for the training set

• Not Applicable/Not Available. This device does not involve a "training set" in the context of machine learning or AI.

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

• Not Applicable/Not Available. This device does not involve a "training set" or "ground truth establishment" for a training set.

Summary of what is provided in relation to your request (though not directly addressing an acceptance criteria study):

The regulatory submission (K093667) for the SPEEDER Shoulder Coil outlines:

• Intended Use: "For use with a Toshiba 1.5T EXCELART Vantage or 1.5T Vantage Titan magnetic resonance scanner to produce diagnostic images of the shoulder that can be interpreted by a trained physician." (Page 4, and Page 2 Point 9)
• Predicate Devices: The device is compared to the "420 GE-64 Phased Array Shoulder Coil" (K945778) manufactured by Medical Advances Inc. (now INVIVO) and the "1.5T Atlas SPEEDER Head-Neck Coil" (K083160) by Quality Electrodynamics. (Page 2, Point 10)
• Basis for Equivalence: The conclusion for substantial equivalence is based on the new coil having the same intended use, similar designs, and being constructed of similar materials as the predicate devices, with no new potential hazards. (Page 2, Point 11)

In essence, this 510(k) submission demonstrates that the SPEEDER Shoulder Coil is substantially equivalent to existing, legally marketed coils, implying that its performance is implicitly considered acceptable because the predicate devices have established safety and effectiveness. However, it does not detail a specific performance study against defined acceptance criteria in a clinical setting as would be required for a novel diagnostic algorithm.

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