FDA 510(k) Search - By Innolitics (SaMD and AI Experts)

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 anatomy, the MR scan technique applied, and presence of contrast agents. The use of contrast agents for diagnostic 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. Images, spectra, and measurements of physical parameters, when interpreted by a trained physician, provide information that may assist 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.

Device Description

The subject Achieva, Intera, Ingenia 1.5T, Ingenia 3.0T, Ingenia 1.5T CX, Ingenia 3.0T CX, Ingenia Elition S, Ingenia Elition X, Ingenia Ambition S, Ingenia Ambition X and MR 5300 MR Systems are 60 cm and 70 cm bore 1.5 and 3.0 Tesla (1.5T and 3.0T) Magnetic Resonance Diagnostic Devices.
In this 510(k) submission, Philips Medical Systems Netherlands B.V. will be addressing the following software changes for the subject device since the last 510(k) submission (primary predicate device (K212673, 11/19/2021), secondary predicate device (K193215, 04/10/2020)):

Software functionality that allows early detection of severe gradient malfunctions. The system is locked for scanning if a malfunction is detected.
Smoke detector software support extension from Ingenia Elition S and X to all other 70cm bore systems
SENSE XL Torso Coil workflow extensions to guide the operator on safe usage of the SENSE XL Torso Coil and monitoring of the SENSE XL Torso Coil temperature

The subject Achieva, Intera, Ingenia 1.5T, Ingenia 3.0T, Ingenia 1.5T CX, Ingenia 3.0T CX, Ingenia Elition S, Ingenia Elition X, Ingenia Ambition S, Ingenia Ambition X and MR 5300 MR Systems are intended to be marketed with the same pulse sequences and coils that are previously cleared by FDA. The accessories to be used with the subject devices have not changed compared to the predicate device.
When Philips MRI system is used in combination with the Philips MR-RT or MR-OR solutions, the user is referred to the dedicated MR-RT and MR-OR Instructions for Use for information on additional accessories that may apply.

AI/ML Overview

The provided FDA 510(k) clearance letter and its associated 510(k) Summary for Philips MR Systems (K251808) DO NOT contain the detailed information required to describe the acceptance criteria and the study that proves the device meets the acceptance criteria in the manner requested.

This submission is a Special 510(k), which is used for modifications to a manufacturer's own legally marketed device where the modified device is still substantially equivalent to the cleared device, and the modifications do not raise new questions of safety and effectiveness. This type of submission often relies heavily on risk management and performance testing to demonstrate that the changes have not degraded the safety or effectiveness of the device.

The document primarily focuses on software changes related to safety-critical functions (gradient malfunction detection, smoke detector interlock, SENSE XL Torso Coil temperature monitoring) and asserts substantial equivalence to existing predicate devices.

Here's why the requested information cannot be fully extracted and what can be inferred:

Summary of Information NOT Present in the Document:

Detailed Acceptance Criteria Table with Performance Data: The document states that "The verification and/or validation test results demonstrate that the subject... MR Systems meet the acceptance criteria and are adequate for the intended use" (Page 8), but it does not provide a specific table of these acceptance criteria nor the numerical performance data for the device against them. The information provided about the software changes focuses on their functionality and equivalence rather than quantitative performance metrics (e.g., specific thresholds for gradient malfunction detection sensitivity/specificity, or precise temperature monitoring accuracy).
Sample Size for Test Set and Data Provenance: No specific test set sample sizes (e.g., number of patients, number of scans) are mentioned. The testing described is "Non-Clinical verification and validation tests," implying it's not based on patient data in the typical sense for clinical performance.
Number of Experts and Qualifications for Ground Truth: Since no clinical data or diagnostic performance studies are described (only non-clinical V&V), there's no mention of experts establishing ground truth for a test set.
Adjudication Method for Test Set: Not applicable as no clinical study with expert reads is described.
Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: Not mentioned as no clinical study evaluating human reader performance is described.
Standalone (Algorithm Only) Performance: While the software features operate automatically, no quantitative standalone performance data (e.g., TPR, FPR for malfunction detection) is provided. The focus is on the functionality of the safety mechanisms (e.g., "system is locked," "enforces a cool down period").
Type of Ground Truth Used: For the safety software functions, the "ground truth" would likely be derived from engineering specifications, simulated fault conditions, or direct sensor readings validated against known physical parameters, rather than expert consensus on medical images or pathology. The document hints at this by stating "verification and/or validation test results demonstrate that the subject... meet the acceptance criteria and are adequate for the intended use."
Sample Size for Training Set & Ground Truth Establishment for Training Set: Since these are modifications to existing, cleared devices, and the described changes are primarily safety and workflow enhancements, it's unlikely that new deep learning models requiring large imaging training sets were developed for these specific features. If machine learning was involved in the gradient malfunction detection, the specific training methodology is not disclosed. The document implies engineering-based verification and validation rather than large-scale data-driven model training.

Information that CAN be Inferred or Directly Stated:

Study Type: Non-clinical verification and validation tests, adhering to recognized international and FDA-recognized consensus standards (e.g., IEC 60601-1-6 for usability, IEC 62304 for software lifecycle, ISO 14971 for risk management).
Overall Conclusion: The non-clinical testing demonstrates that the modified MR Systems "meet the acceptance criteria and are adequate for the intended use" and that "all risks are sufficiently mitigated, that no new risks are introduced, and that the overall residual risks are acceptable." This leads to the conclusion of substantial equivalence.
Basis for Ground Truth (Implied): For the safety features, the "ground truth" is established by engineering specifications, simulated fault conditions, and internal testing to ensure the alarm/lockout mechanisms activate correctly under defined hazardous conditions and that the temperature monitoring is accurate.
Key Software Changes and Their Demonstrated Functionality:
- Severe Gradient Malfunction Detection: Modifies the system to lock when the frequency of gradient amplifier errors exceeds predefined thresholds, preventing severe malfunctions. The previous system only aborted individual errors and allowed continuation. The "study" here would be demonstrating that the system properly locks when these new thresholds are met and does not falsely lock otherwise.
- Smoke Detector Software Support Extension: Extends existing 60cm MR System smoke detector interlock software to 70cm MR Systems. The "study" would show that the same logic and safety performance are maintained on the new platform.
- SENSE XL Torso Coil Workflow Extensions: Software now enforces a cool-down period for the coil and guides the operator on temperature management. The "study" likely involved testing the logic of the cool-down enforcement and the accuracy/timing of the temperature warnings.

Based on the provided document, here's the most that can be extracted and inferred about the acceptance criteria and studies:

Device: Philips Achieva, Intera, Ingenia 1.5T, Ingenia 3.0T, Ingenia 1.5T CX, Ingenia 3.0T CX, Ingenia Elition S, Ingenia Elition X, Ingenia Ambition S, Ingenia Ambition X and MR 5300 MR Systems (software modifications).

Purpose of the Study: To demonstrate that software changes implemented for gradient malfunction detection, smoke detector interlock extension, and SENSE XL Torso Coil temperature monitoring do not raise new questions of safety and effectiveness and that the modified devices remain substantially equivalent to their predicate devices.

1. Table of Acceptance Criteria and Reported Device Performance:

Feature/Acceptance Criteria Category	Acceptance Criteria (Inferred from document)	Reported Device Performance (Inferred from document)
Severe Gradient Malfunction Detection	Software must accurately detect gradient amplifier error frequencies exceeding predefined safety thresholds.	The newly added functionality successfully detects when error frequency goes beyond predefined thresholds and preventively locks the MR Systems to avoid severe gradient malfunction.
	Software must prevent scanning/lock the system when thresholds are exceeded.	The MR Systems are preventively locked when critical thresholds are reached.
	Software must not unduly interfere with normal operation or cause false locks.	Functions similarly to the predicate in handling individual errors; additions do not impact intended use or raise new safety questions. Implies no undue false positives.
Smoke Detector Interlock Software	Smoke detector interlock software functionality from 60cm systems must be correctly implemented and perform identically on 70cm MR Systems.	The implementation of the Smoke Detector Interlock software in the 70cm MR Systems is the same compared to the predicate device for 60cm MR Systems; the technology is consistent.
	The system must be locked for scanning if a malfunction is detected (consistent with predicate).	As with the predicate, the system is locked for scanning if a malfunction is detected. Performance maintained across MR System types.
SENSE XL Torso Coil Workflow Extensions	Software must accurately track coil temperature during usage.	Temperature information is used to guide the operator.
	Software must enforce a cool-down period when temperature reaches predefined acceptable levels for the next examination or during examination.	The MR System software enforces a cool down period for the coil when temperature reaches a level that would go beyond an acceptable level in the next examination.
	Software must provide adequate warnings/guidance to the operator regarding coil temperature to ensure safe usage.	Temperature information is used to guide the operator, suggesting stopping examination and enforcing cool down to enable staying within acceptable temperature limits.
Overall Safety and Effectiveness	Compliance with relevant international and FDA-recognized consensus standards (e.g., IEC 60601-1-6, IEC 62304, ISO 14971, ISO 15223-1, ISO 20417).	Non-clinical performance testing demonstrates compliance with listed standards.
	All identified risks must be sufficiently mitigated.	Risk management activities show that all risks are sufficiently mitigated.
	No new risks introduced.	No new risks are introduced.
	Overall residual risks are acceptable.	The overall residual risks are acceptable.

2. Sample Size Used for the Test Set and Data Provenance:
The document states "Non-Clinical verification and validation tests have been performed." This implies engineering-level testing rather than patient-based clinical studies. No specific sample sizes (e.g., number of scan instances, number of patients) are provided. The data provenance is internal Philips testing, likely performed in the Netherlands (Philips Medical Systems Nederland B.V.). It is retrospective in the sense that it evaluates modifications to existing systems.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications:
Not applicable. Ground truth for these safety software functions is based on engineering specifications and direct measurement/simulation of system states and physical parameters (e.g., gradient performance, temperature, smoke detection), not on expert interpretations of medical images.

4. Adjudication Method for the Test Set:
Not applicable. There is no mention of human readers or adjudication processes for clinical image interpretation.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:
No, an MRMC comparative effectiveness study was not done or reported in this 510(k) summary. The nature of these software modifications (safety and workflow enhancements) does not typically necessitate such a study for 510(k) clearance, especially in a Special 510(k). The document explicitly states "the indications for use remain unchanged and there were no technological characteristics relative to the predicate device that would require clinical testing."

6. If a Standalone (Algorithm Only) Performance was done:
Yes, in the sense that the software features (e.g., gradient malfunction detection, temperature monitoring logic) are algorithms operating on system data. However, quantitative performance metrics (e.g., sensitivity, specificity, accuracy) for these algorithms are not explicitly provided in the summary. The "performance" described is functional—that the system does lock, does enforce cool-downs, etc., when conditions are met.

7. The Type of Ground Truth Used:
For the software changes described, the ground truth is primarily based on:
* Engineering Specifications: Defining thresholds for gradient errors, acceptable temperature ranges for the coil.
* Simulated Fault Conditions: Testing whether the gradient malfunction detection activates correctly under controlled, simulated error rates or conditions.
* Direct Physical Measurements: Verifying the accuracy of temperature sensors and the initiation of cool-down periods.
* Compliance with Standards: Ensuring the robust implementation of software safety features as per recognized industry standards.

8. The Sample Size for the Training Set:
The document does not specify a training set sample size. Given the nature of the software changes (safety logic and workflow enhancements) and this being a Special 510(k), it is unlikely to involve large-scale machine learning model training on medical image datasets. If any internal parameters were 'trained' (e.g., for optimal gradient error thresholds), the details are not disclosed.

9. How the Ground Truth for the Training Set Was Established:
Not explicitly stated. If there were any trainable parameters for the safety functions, the ground truth would have been established via engineering analysis, simulation, and empirical testing to define the optimal setpoints for safety interlocks and warnings.

Summary

Regulation Number and Section

§ 892.1000 Magnetic resonance diagnostic device.

(a)
Identification. A magnetic resonance diagnostic device is intended for general diagnostic use to present images which reflect the spatial distribution and/or magnetic resonance spectra which reflect frequency and distribution of nuclei exhibiting nuclear magnetic resonance. Other physical parameters derived from the images and/or spectra may also be produced. The device includes hydrogen-1 (proton) imaging, sodium-23 imaging, hydrogen-1 spectroscopy, phosphorus-31 spectroscopy, and chemical shift imaging (preserving simultaneous frequency and spatial information).(b)
Classification. Class II (special controls). A magnetic resonance imaging disposable kit intended for use with a magnetic resonance diagnostic device only is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.