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The 8ch Wrist Coil by Shenzhen RF Tech Co.,Ltd is receive-only coil and is designed for use as general purpose coil. The 8ch Wrist Coil is designed to be use with GE 1.5T MRI systems to produce diagnostic images of the wrists and fingers that can be interpreted by a trained physician.

The 8ch Wrist Coil is receive only phased array coil to produce diagnostic images of the wrists and fingers in adult population.
The 8ch Wrist Coil is tuned to receive RF frequency corresponding to the proton precession in a 1.5 Tesla magnetic field, which is governed by the Larmor equation.
The 8ch Wrist Coil is based on phased array technique to produce the images from 8 different channels with intergraded preamplifiers. The 8ch Wrist Coil is tuned to the proton frequency of 63.86MHz.

The provided text is a 510(k) Summary for the 8ch Wrist Coil, a medical device. This document focuses on demonstrating substantial equivalence to a predicate device, rather than providing a detailed study of an AI algorithm's performance. Therefore, much of the requested information regarding AI algorithm performance (e.g., acceptance criteria for AI, training set details, multi-reader multi-case studies) is not present in this document.

However, based on the information provided, I can address the aspects related to the device's performance and validation, particularly in relation to its physical and imaging characteristics:

Acceptance Criteria and Device Performance for 8ch Wrist Coil

The document primarily focuses on demonstrating that the 8ch Wrist Coil performs "as well as" the predicate device and meets established industry standards for MRI coils.

1. Table of Acceptance Criteria and Reported Device Performance

The study proving the device meets these criteria is the "Summary of verification Tests," which states: "Bench testing was conducted to demonstrate that image uniformity, SNR and coil surface heating met specified requirements. The test results also show that the 8ch Wrist Coil achieved the expected results and satisfied the standards listed above."

Regarding AI-specific criteria, the document does not present information about an AI algorithm. This device is a passive MRI coil, not an AI software. Therefore, the following points are not applicable based on the provided text:

• 2. Sample size used for the test set and the data provenance: Not applicable for a hardware device validation based on bench testing. The "test set" here refers to the physical coil and its performance measurements.
• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for hardware performance is established by metrology and standard comparisons (e.g., NEMA, IEC).
• 4. Ground truth Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
• 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, as this is a hardware device, not an AI algorithm.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): For the hardware coil, the "ground truth" for its performance (SNR, uniformity) is established by adherence to recognized industry standards (NEMA MS-1, NEMA MS-3) and validated bench testing procedures.
• 8. The sample size for the training set: Not applicable (no AI component).
• 9. How the ground truth for the training set was established: Not applicable (no AI component).

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The 8ch Wrist Coil is intended to be used in conjunction with a SIGNA Prime Magnetic Resonance scanner to produce diagnostic images of the wrist anatomy that can be interpreted by a trained physician.

The 8ch Wrist Coil magnetic resonance (MR) coil is a receive only phased array coil with 8 channels for wrist imaging. This Wrist Coil is designed for use with the SIGNA Prime (K211980). The 8ch Wrist Coil is designed to be used vertically at the patient's side or horizontally overhead. The wrist array comes with two rigid base plates (for flat or curved tabletops) for fixation to reduce patient motion. The coil receives magnetic resonance signals generated in hydrogen nuclei (protons) in the wrist while blocking the high-frequency B1 field applied by the MRI scanner at specified timing. The 8ch Wrist Coil is tuned to receive RF frequency corresponding to the proton precession in a 1.5 tesla magnetic field, which is governed by the Larmor equation. Images are typically generated as axial, sagittal, coronal oblique slices and include coverage of the wrist anatomy.

The provided document is a 510(k) summary for the Philips 8ch Wrist Coil, a magnetic resonance (MR) coil. It describes the device, its intended use, and the testing conducted to demonstrate its safety and effectiveness.

Here's an analysis of the acceptance criteria and study information, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding device performance metrics. Instead, it lists the types of performance testing conducted and generally states that the device "meets predefined performance criteria."

However, based on the non-clinical and clinical performance data summary, we can infer the areas of acceptance:

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: The document does not specify a numerical sample size for the clinical test set. It mentions "clinical images" were reviewed by a radiologist. It does not indicate the number of images or cases.
• Data Provenance: The document does not explicitly state the country of origin or whether the data was retrospective or prospective. It simply refers to "clinical images reviewed by a radiologist provided in this submission."

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

• Number of Experts: One expert was used.
• Qualifications of Expert: "US Board Certified radiologist." No specific information on years of experience is provided.

4. Adjudication Method for the Test Set

The document states that a "US Board Certified radiologist's review of clinical images" was conducted. This suggests that a single expert provided the assessment, implying no formal adjudication method (like 2+1 or 3+1 consensus) was used for establishing ground truth from multiple readers.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly described. The study focused on the performance of the device itself, rather than comparing human reader performance with and without AI assistance. The device is an MRI coil, not an AI diagnostic tool.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, in a sense, a "standalone" performance evaluation of the device itself was conducted through the non-clinical and clinical image review. This device is an MRI coil, which is a component of an imaging system, not an AI algorithm. The performance being evaluated is its ability to acquire diagnostic-quality images. The "standalone" aspect here refers to the intrinsic performance of the coil (e.g., SNR, uniformity, safety) and the quality of the images it produces, which are then interpreted by a human.

7. The Type of Ground Truth Used

The ground truth for the clinical performance assessment was primarily based on expert assessment/consensus (from a single US Board Certified radiologist) of the diagnostic quality of the images produced by the device. Pathology or outcomes data are not mentioned as being used for ground truth in this context.

8. The Sample Size for the Training Set

The document does not mention a training set because the device is a physical MRI coil, not an AI algorithm that requires training data.

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

Not applicable, as the device is not an AI algorithm and therefore does not have a training set or associated ground truth for training purposes.

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