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Philips Magnetic Resonance (MR) systems are Medical Electrical Systems indicated for use as a diagnostic device. This MR system enables trained physicians to obtain cross-sectional images, spectroscopic images and/or spectra of the internal structure of the head, body or extremities, in any orientation, representing the spatial distribution of protons or other nuclei with spin.

Image appearance is determined by many different physical properties of the tissue and the MR scan technique applied, and presence of contrast agents. The use of contrast imaging applications should be performed consistent with the approved labeling for the contrast agent.

The trained clinical user can adjust the MR scan parameters to customize image appearance, accelerate image acquisition, and synchronize with the patient's breathing or cardiac cycle.

The systems can use combinations of images to produce physical parameters, and related derived images, spectra, and measurements of physical parameters, when interpreted by a trained physician, provide information that may assust diagnosis and therapy planning. The accuracy of determined physical parameters depends on system and scan parameters, and must be controlled and validated by the clinical user.

In addition the Philips MR systems provide imaging capabilities, such as MR fluoroscopy, to guide and evaluate interventional and minimally invasive procedures in the head, body and extremities. MR Interventional procedures, performed inside or adjacent to the Philips MR system, must be performed with MR Conditional or MR Safe instrumentation as selected and evaluated by the clinical user for use with the specific MR system configuration in the hospital. The appropriateness and use of information from a Philips MR system for a specific interventional procedure and specific MR system configuration must be validated by the clinical user.

This Special 510(k) submission will include modifications of the proposed Ingenia Elition R5.7.1 SP4 MR Systems as compared to Philips legally marketed predicate device Ingenia Elition of the 510(k) submission Achieva, Intera, Ingenia, Ingenia CX, Ingenia Elition and Ingenia Ambition MR Systems (K193215, 04/10/2020).

In this 510(k) submission, Philips Medical Systems Nederland B.V. will be addressing the following minor software enhancements for the proposed Ingenia Elition R5.7.1 SP4 MR Systems:

1. Introduction of a persistence latch which will prevent the currently available Interlock of SmokeDetector to be reset by customer, which is against the current labeling (abnormal use).
2. The UI (User Interface) and IfU (Instructions for Use) are also updated to provide clear instructions for the user in case the currently available SmokeDetector Alarm Interlock is activated and to further clarify current instructions to prevent powercycling the system (abnormal use).
3. SW Compatibility with the PD-Break Heat Detector

Identical to the predicate device, the proposed Ingenia Elition R5.7.1 SP4 MR Systems is intended to be marketed with the following pulse sequences and coils that are previously cleared by FDA:

1. mDIXON (K102344)
2. SWIp (K131241)
3. mDIXON-Quant (K133526)
4. MRE (K140666)
5. mDIXON XD (K143128)
6. O-MAR (K143253)
7. 3D APT (K172920)
8. Compatible System Coils (identical to the predicate devices)

The provided document, a 510(k) Summary for Philips Medical Systems Nederland B.V.'s Ingenia Elition R5.7.1 SP4 MR Systems, focuses on demonstrating substantial equivalence to a predicate device. It addresses minor software enhancements, specifically related to a persistence latch for a SmokeDetector interlock, UI/IfU updates for the SmokeDetector alarm, and SW compatibility with a PD-Break Heat Detector.

Crucially, this document states that "The proposed Ingenia Elition R5.7.1 SP4 MR Systems did not introduce any modification to the indication for use or technological characteristics relative to the predicate devices that would require clinical testing." This implies that the device is not an AI/ML-powered medical device that would involve a study proving how AI-assistance improves human reader performance or the standalone performance of an AI algorithm.

Therefore, the requested information regarding acceptance criteria and a study proving the device meets those criteria, specifically concerning AI/ML performance, cannot be extracted from this document, as it describes a non-AI/ML device undergoing a Special 510(k) for minor software changes. The "acceptance criteria" discussed are related to compliance with consensus standards and general safety/performance, not AI/ML specific metrics.

However, based on the non-clinical performance data and the conclusion, we can infer the acceptance criteria for the software changes and how the device (with these changes) meets them.

Inferred Acceptance Criteria and Device Performance (for software changes)

Since the submission is a "Special 510(k)" for minor software enhancements, the acceptance criteria are primarily related to maintaining the safety and effectiveness of the existing, cleared device, and ensuring compliance with updated standards.

Information Not Applicable/Provided for an AI/ML Device

The following points are specifically requested for AI/ML-powered medical devices and are not applicable to this 510(k) summary, as it describes a conventional MR system with minor software updates.

2. Sample size used for the test set and the data provenance: Not applicable. No specific test set data for AI/ML performance is presented. The testing pertains to software verification and compliance with standards.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No clinical ground truth establishment for AI/ML performance.
4. 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. This device is not AI-assisted.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an AI algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable.
8. The sample size for the training set: Not applicable. This is not an AI/ML device requiring a training set in the context of machine learning.
9. How the ground truth for the training set was established: Not applicable.

In summary, this 510(k) document indicates that the device is a Philips MR system with minor software changes and not an AI/ML-powered device. Therefore, the detailed AI/ML-specific study information requested is not present. The acceptance criteria and performance data are related to general device safety, effectiveness, and compliance with established medical device standards for MR systems.

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