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This coil is indicated for use in conjunction with 1.5T and 3.0T GE Healthcare Magnetic Resonance Scanner systems to produce images and/or spectra of the head, that when interpreted by a trained physician yield information that may assist in diagnosis.

The MC 1504G-16R (1.5T) and MC 3004G-16R (3.0T) Head Coils are multi-channel receive only coils consisting of 16 RF elements. Each RF element has active and passive blocking networks, and integrated preamplifiers. The MC 1504G-16R RF elements are tuned to 'H at 1.5T (63.9 MHz), while the MC 3004G-16R RF elements are tuned to 'H at 3.0T (127.8 MHz). The coil housing is constructed out of a rigid plastic with an opening for patient viewing and comfort; the head support/base is included with each coil assembly.

Here's an analysis of the provided text to extract the requested information about the device's acceptance criteria and testing:

This document primarily describes the substantial equivalence of a new head coil (MC 1504G-16R and MC 3004G-16R) to existing predicate devices. The focus is on demonstrating that the new device performs similarly to or better than the predicates, rather than establishing acceptance criteria against a specific, quantitative performance threshold for a diagnostic outcome. Therefore, the information provided isn't in the typical format of acceptance criteria for an AI/CADe device where metrics like sensitivity, specificity, or AUC are assessed against predefined targets.

However, based on the text, we can infer the performance comparisons made.

1. Table of Acceptance Criteria and the Reported Device Performance

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

• Sample Size (Test Set): Not explicitly stated numbers.
  • Volunteer Scans: "Volunteer scans were performed." The number of volunteers is not specified.
  • Phantoms: "Performance evaluations (phantoms) were completed." The number of phantoms is not specified.
• Data Provenance: Not specified, but generally, such studies for medical device clearance are conducted internally or at partnering institutions within the country of the manufacturer. The study is prospective in nature, involving new scans/tests specifically for this evaluation.

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

• Number of Experts: Not explicitly stated, but "registered technologists in magnetic resonance" were used. This implies more than one.
• Qualifications of Experts: "Registered technologists in magnetic resonance." No specific experience level (e.g., years of experience) is provided. Their role was to assess "equivalence in resulting image quality," meaning they were evaluating the technical quality of the images rather than making clinical diagnoses.

4. Adjudication Method for the Test Set

• Adjudication Method: "Scan images were then reviewed in blind fashion by registered technologists in magnetic resonance." No specific adjudication method (e.g., 2+1, 3+1) is mentioned beyond the blind review. This suggests a qualitative assessment rather than a structured consensus process.

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 MRMC study was done. This device is a hardware component (MRI head coil), not an AI/CADe system designed to assist human readers. Therefore, there's no mention of human reader improvement with AI assistance.

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

• Not applicable. This is a hardware device (MRI coil), not an algorithm or AI system. Its performance is evaluated through physical and imaging characteristics.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

• For image quality evaluation, the "ground truth" was essentially the subjective assessment of "equivalence in resulting image quality" by "registered technologists in magnetic resonance" when comparing images from the proposed device to images from predicate devices. This can be considered a comparative expert assessment of image quality.
• For physical performance, the "ground truth" was established by engineering specifications and industry standards (e.g., IEC 60601-1 for safety, NEMA MS-1 for SNR measurements).

8. The Sample Size for the Training Set

• Not applicable / No specific training set. As a physical hardware device, there isn't a "training set" in the machine learning sense. The device design and specifications are based on engineering principles and knowledge, not data-driven training.

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

• Not applicable. See point 8.

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