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The MRIaudio PREM System with MRIview is intended to provide audio and visual entertainment to patients and facilitate patient communication in MRI environments up to, and including, 3.0 Tesla. The product is not intended for medical diagnosis or treatment. Technologist control units are intended to be used outside of the MRI scan room.

The MRIaudio PREM System with MRIview is an MRI conditional audio and video solution that provides MRI patients with music, direct communication, and hearing protection. With the addition of the MRIview technology, the system provides MRI patients with video and allows technologists to view the patient.

The provided document is a 510(k) summary for the MRIaudio PREM System with MRIview. This document primarily focuses on establishing substantial equivalence to a predicate device and does not detail specific acceptance criteria for a new performance claim or a comprehensive study proving a device meets such criteria in the way typically seen for AI/CADe devices.

In this case, the device is an MRI conditional audio and video solution intended to provide entertainment and communication in MRI environments, not for medical diagnosis or treatment. The performance data presented focuses on safety and not on diagnostic accuracy metrics.

Here's a breakdown based on the information provided, addressing your requested points directly where possible, and noting where the information is not applicable or unavailable in this document:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not explicitly stated for each test. For the "Magnetic field interactions at 3-Tesla" and electrical/EMC testing, these are typically conducted on a limited number of device units (prototypes or production samples). For the "clinical images," it's mentioned that "sample clinical images submitted exhibit a mix of pulse sequences and imaging options," but a specific number is not provided, implying this was a qualitative assessment rather than a quantitative study with a defined test set.
• Data Provenance: Not specified. The clinical images seem to have been used to assess the device's impact on MRI image quality, but details regarding their origin (country, retrospective/prospective) are absent.

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

• Not Applicable. The device is not intended for medical diagnosis or treatment, so there is no diagnostic "ground truth" to establish through expert review for its primary function. The assessment of MR image quality implies expert review, but the number and qualifications of experts are not mentioned.

4. Adjudication Method for the Test Set

• Not Applicable. As there's no diagnostic ground truth derived from expert review mentioned, an adjudication method is not described.

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

• No. An MRMC study is not mentioned as this device is not a diagnostic aid.

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

• No. This device is an audio/video system, not an algorithm, so a standalone performance study in the context of diagnostic algorithms is not applicable.

7. The Type of Ground Truth Used

• For the safety and performance tests (magnetic interactions, electrical safety, EMC), the "ground truth" is defined by the standards and test protocols themselves, which specify passing/failing criteria.
• For the assessment of MR image quality, the "ground truth" is based on qualitative expert assessment that the device does not adversely affect MR image production. This is inferred from the statement "No adverse events were reported; therefore, the subject MRIaudio PREM System with MRIview does not adversely affect MR image production in the worst-case environment."

8. The Sample Size for the Training Set

• Not Applicable. This device is not an AI/ML algorithm that requires a training set.

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

• Not Applicable. As this device does not use an AI/ML algorithm requiring a training set, ground truth for a training set was not established.

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