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General disease and vascular imaging of the head and cervical regions

The Flexart™ Head and Neck Coil is essentially a QD (quadrature) extension of the standard receive only Cervical Collar cleared with the Flexart. The extension consists of adding a figure-8 planar loop onto the printed circuit coil trace board, so that there are now two independent RF loops (one rectangular and one figure-8). The RF magnetic fields from the two loops are oriented at 90 degrees with respect to each other (in quadrature).

The two loops are matched in impedance and tuned to the imaging system's center frequency by using varactors and the RF outputs are then amplified with low noise amplifiers. The active decoupling of the coil during transmit is achieved by use of two (one for each loop) high impedance parallel resonant traps which are activated by diodes. These diodes turn on because of the inductively coupled voltage from the transmitter coil's RF magnetic field.

This document describes the Flexart Head and Neck Coil for an MRI system, not an AI/ML powered medical device. Therefore, many of the requested fields regarding acceptance criteria, study design, and ground truth are not applicable.

Here's an attempt to extract relevant information and note the inapplicable sections:

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

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Not Applicable. This is a hardware component (MRI coil) and its performance is evaluated through technical specifications and physical measurements, not typically with "test sets" of patient data in the same way an AI algorithm would be. The data provenance would refer to engineering measurements and phantom studies, not clinical data subsets.

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. Ground truth for an MRI coil's performance relates to its physical properties (e.g., SNR measurements from phantoms), not expert interpretation of images.

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

• Not Applicable. Adjudication methods are for clinical interpretations, not hardware performance.

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 device is an MRI coil, not an AI software. Therefore, an MRMC study related to AI assistance is irrelevant.

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

• Not Applicable. This is a hardware component.

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

• Physical Measurements/Engineering Specifications. The "ground truth" for the coil's performance (e.g., SNR, field strength) is established through standardized engineering tests, phantom studies, and adherence to established MRI system performance metrics.

8. The sample size for the training set

• Not Applicable. This is a hardware component. There is no "training set" in the context of machine learning. Design and validation are based on engineering principles and prototypes.

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

• Not Applicable. There is no "training set" or associated ground truth in the context of machine learning for this device. The coil's design is based on established physics and engineering principles, and its performance is verified through physical measurements.

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