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The Encompass™ 15 Channel Head Coil is intended to be used in conjunction with a Magnetic Resorance Scanner for the MR examination of the human brain just before, during, and at the end of brain surgery. The Encompass™ 15 Channel Head Coil can also be used as a standard diagnostic examinations and fMRI (Functional Magnetic Resonance Imaging). When used with magnetic resonance imaging systems, it is indicated for use as a diagnostic imaging device to produce transverse, sagittal, coronal and oblique images of the internal structures of the head. When interpreted by a trained physician, these images provide information that can be useful in determining diagnosis.

Qfix and NORAS MRI products GmbH have jointly developed a head coil designed to enable MRI for diagnosis and to inform additional clinical actions, the Encompass™ 15 Channel Head Coil, 3T. The Encompass 15 Channel Head Coil is a diagnostic imaging device for use in 3T environments for obtaining diagnostic MR images to be used to inform procedures which use MR imaging to guide interventional procedures and other treatments. The Encompass™ 15 Channel Head Coil has been specifically designed to interface with the Encompass™ SRS Immobilization System (cleared with K152321 December 4, 2015).

The Encompass™ 15 Channel Head Coil is a ridged receive only coil featuring a 7 Channel Top Coil, an 8 Channel Bottom Coil, and an optional mirror holder. Imaging is performed with a 15-Channel "phased array" co-developed by Qfix and NORAS and manufactured by NORAS. The coils are mounted in a rigid Coil Frame and connection to the MRI is managed by the applicable MRI software. The Encompass™ 15 Channel MRI Head Coil has been designed for use with Siemens Healthineers MAGNETOM 3T systems e.g. MAGNETOM Skyra.

Encompass™ 15 Channel Head Coil has been optimized for use with the Encompass™ SRS Immobilization System. The use of the Encompass™ 15 Channel Head Coil together with the Encompass™ SRS Immobilization System allows immobilization of the patient while obtaining diagnostic MR images to be used to inform procedures which use MR imaging to guide interventional procedures and other treatments.

This FDA 510(k) summary describes the Qfix Encompass™ 15 Channel Head Coil, 3T, which is an MRI head coil. The document primarily focuses on demonstrating substantial equivalence to a predicate device (NORAS OR Head Coil 3T) through non-clinical performance and safety testing. It does not present an independent study with acceptance criteria involving specific performance metrics like sensitivity, specificity, or AUC for an AI/device's diagnostic accuracy.

Therefore, many of the requested elements for an AI/device performance study (like test set sample size, expert ground truth, effect size with AI assistance, standalone performance, training set details) are not applicable to the information provided in this 510(k) summary.

However, based on the provided text, I can infer the general acceptance criteria and describe the general study approach used to demonstrate substantial equivalence for this type of medical device (an MRI coil).

Here's the breakdown:

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

For an MRI coil, "acceptance criteria" and "reported device performance" are typically framed around safety and technical imaging performance, often compared to a predicate device, rather than diagnostic accuracy metrics.

2. Sample size used for the test set and the data provenance

• Sample Size: Not applicable in the context of an "AI/device test set." This document describes testing for an MRI coil. The "test set" would primarily refer to technical performance measurements on imaging systems. There's no mention of a defined "test set" of patient images or specific clinical cases for evaluating diagnostic accuracy in the way an AI algorithm would be evaluated.
• Data Provenance: Not applicable for a typical AI/device test set. The performance data comes from non-clinical bench testing conducted by Qfix and NORAS. It indicates testing on "3T Siemens Healthineers MAGNETOM MRI scanners."

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Not applicable. No expert review for establishing ground truth on a 'test set' of patient data for diagnostic accuracy is mentioned. The "interpretation by a trained physician" is mentioned in the Indications for Use, which is standard for diagnostic imaging, but this is not part of a study to establish ground truth for algorithm performance.

4. Adjudication method for the test set

• Not applicable. No adjudication method is mentioned as there's no diagnostic accuracy study described involving a test set and experts.

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. An MRMC comparative effectiveness study was not performed. This document is for an MRI head coil, not an AI-powered diagnostic device, so AI assistance is not a component.

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

• Not applicable. This device is an MRI head coil, not an algorithm. Its performance is inherent to its physical design and interaction with the MRI scanner. It does not perform a standalone diagnostic function akin to an algorithm.

7. The type of ground truth used

• For an MRI coil, "ground truth" relates to the accuracy and quality of the image acquisition, not diagnostic findings from patient cases. The "ground truth" (or reference standard) in this context would be:
  • Engineering specifications and standards: Adherence to NEMA standards for MRI performance (e.g., SNR, uniformity).
  • Safety standards: Compliance with IEC 60601-1 series and ISO 14971.
  • Predicate device performance: Functional equivalence and demonstrated improvements over the NORAS OR Head Coil 3T.

8. The sample size for the training set

• Not applicable. This device is hardware (an MRI coil), not an AI algorithm, so there is no "training set."

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

• Not applicable. As there is no training set for an AI algorithm.

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