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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 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.

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.

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:

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.

Ask a specific question about this device

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 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.

The subject Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition, BlueSeal, MR 5300 and MR 7700 MR Systems are 60 cm and 70 cm bore 1.5 and 3.0 Tesla (1.5T and 3.0T) Magnetic Resonance Diagnostic Devices.

A new optional software feature SmartSpeed Precise is contained in software R12.3 for the subject Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition, BlueSeal, MR 5300 and MR 7700 MR Systems.

SmartSpeed Precise is a machine learning based reconstruction technique designed to increase the signal-to-noise (SNR), increase the sharpness, and reduce residual ringing artifacts in MR images.

The introduction of SmartSpeed Precise only required updates to the MR System Software.

The subject Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition, BlueSeal, MR 5300 and MR 7700 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 Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition, BlueSeal, MR 5300 and MR 7700 MR Systems have not changed compared to the predicate device and can be found in the Instructions for Use accompanying the 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.

This FDA 510(k) clearance letter describes the acceptance criteria and study proving the Philips MR systems meet these criteria, particularly focusing on the new SmartSpeed Precise feature.

Here's an breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The FDA clearance letter does not provide a specific quantitative table of acceptance criteria with corresponding numerical performance metrics for the SmartSpeed Precise feature. Instead, it describes the acceptance criteria implicitly through the study design and the qualitative assessments.

The core acceptance is that the new SmartSpeed Precise feature, as implemented in the Philips MR Systems, maintains at least equivalent image quality for diagnostic purposes while providing benefits like increased SNR, sharpness, and reduced ringing artifacts, and does not negatively impact safety or effectiveness compared to the predicate device.

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

The document mentions "a reader evaluation by ABR board certified radiologists" was performed, and "qualitative image review" by application specialists. However, the specific sample size (number of cases/images) used for these evaluations (testing) is not explicitly stated in the provided text.

The data provenance is not specified regarding country of origin. It is described as non-clinical performance data, suggesting it's likely retrospective data (existing images) or phantom/simulated data, rather than prospective patient recruitment solely for this study. The phrasing "Simulated use validation was executed" further supports this.

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

• Experts for Qualitative Image Review: "application specialists" performed the qualitative review. Their specific number and detailed qualifications (e.g., years of experience, certifications beyond "application specialist") are not specified.
• Experts for Reader Evaluation: "ABR board certified radiologists" performed the reader evaluation. The number of radiologists is not specified. Their qualification is clearly stated as "ABR board certified radiologists."

4. Adjudication Method for the Test Set

The document does not explicitly describe an adjudication method (e.g., 2+1, 3+1) for resolving disagreements among readers. It states "a reader evaluation by ABR board certified radiologists was performed" and "the review evaluation shows that the proposed device is assessed as equivalent." This suggests a consensus or majority opinion might have been reached amongst them, but the process is not detailed.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

Yes, a multi-reader multi-case comparative effectiveness study appears to have been done implicitly as part of the "reader evaluation by ABR board certified radiologists."

• Effect Size of Human Readers' Improvement with AI vs. Without AI Assistance:
  The study was designed to compare the new SmartSpeed Precise (AI-enhanced reconstruction) against the predicate device's reconstruction technology. The document states:
  "The review evaluation shows that the proposed device is assessed as equivalent for diagnosis and holds significantly better SNR and sharpness compared to the predicate reconstruction technology, also in the presence of (subtle) abnormalities and pathology."
  This indicates a positive effect size on image quality metrics (SNR, sharpness) directly impacting the interpretability for human readers. However, specific numerical effect sizes (e.g., mean difference in reader performance metrics, confidence intervals, p-values) are not provided in this summary. The primary claim is "equivalent for diagnosis" but with "significantly better SNR and sharpness."

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

The description focuses on the impact of SmartSpeed Precise on image quality for human interpretation. While a machine learning model is central to SmartSpeed Precise, the assessment is not described as a purely standalone (algorithm-only) performance evaluation independent of human interpretation. The features explicitly assessed (SNR, sharpness, CNR, artifact level) are objective image quality metrics that could be evaluated standalone, but their context in this document is in relation to human reader assessment ("radiologists have assessed the quality of the visualization of abnormalities...").

7. Type of Ground Truth Used

The ground truth for the reader evaluation appears to be based on:

• Expert Consensus/Judgment: The "ABR board certified radiologists" assessed image properties (SNR, sharpness, CNR, artifacts) and the "quality of the visualization of abnormalities and pathologies" and whether images were "of sufficient quality for diagnostic purposes." This implies their collective professional judgment formed the ground truth for diagnostic equivalence and quality assessment.
• Implicit Clinical Ground Truth: For cases with abnormalities/pathologies, the underlying clinical diagnosis (presumed to be established through other means like prior imaging, clinical follow-up, or pathology reports) would serve as the ultimate ground truth against which the visualization of these abnormalities was assessed by the radiologists. However, the specific method for establishing this clinical ground truth for the cases themselves is not detailed.

8. Sample Size for the Training Set

The document does not specify the sample size used for training the SmartSpeed Precise machine learning model. It only states that "SmartSpeed Precise is a machine learning based reconstruction technique."

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

The document does not specify how the ground truth for the training set was established. Given that it's a "machine learning based reconstruction technique" focused on improving SNR, sharpness, and reducing artifacts, the training ground truth would typically involve pairs of noisy/artifact-ridden input images and corresponding "ideal" or "truth" images (e.g., acquired with very long scan times or gold-standard techniques not feasible in routine clinical practice) against which the model learns to reconstruct improved images. However, the exact methodology is not described.

Ask a specific question about this device

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.

The proposed Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition, MR 5300 and MR 7700 MR Systems R12 are 60 cm and 70 cm bore 1.5 and 3.0 Tesla (1.5T and 3.0T) Magnetic Resonance Diagnostic Devices, hereafter to be known as Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition, MR 5300 and MR 7700 MR Systems.

This bundled abbreviated 510(k) submission, is prompted by the introduction of a new optional software feature called Precise Image contained in software R12 for the proposed Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition, MR 5300 and MR 7700 MR Systems, as compared to our legally marketed primary predicate device Achieva, Ingenia, Ingenia CX, Ingenia Elition, and Ingenia Ambition MR Systems (R11) (K213583) and the secondary predicate device MR 5300 and MR 7700 R11 MR Systems (K223442).

Precise Image is a deep learning based reconstruction technique designed to increase signal-to-noise ratio (SNR), increase sharpness and decrease ringing artefacts from MR images.

The introduction of Precise Image only required updates to the MR System Software.

The proposed Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition, MR 5300 and MR 7700 MR Systems are 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

The accessories to be used with the proposed device Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition, MR 5300 and MR 7700 MR Systems have not changed compared to the primary predicate device and secondary predicate device and can be found in the Instructions for Use accompanying the device:
System coils PPU Sensor for wireless physiology Pediatric PPU Sensor FlexTrak trolleys (FlexTrak / HA FlexTrak II) Acoustic Hood MR Elastography

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:
Flextrak OR MR-RT CouchTop RT CouchTop XD

The provided text describes the acceptance criteria and the study conducted for the Philips Ingenia, Ingenia CX, Ingenia Elition, Ingenia Ambition, MR 5300, and MR 7700 MR Systems, specifically focusing on the new "Precise Image" software feature.

Here's a breakdown of the requested information:

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

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

The document mentions "a reader evaluation by ABR board certified radiologists was performed" and refers to "MR images," but does not explicitly state the sample size (number of images or cases) used for the test set. It also does not specify the country of origin of the data or whether it was retrospective or prospective.

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

The document states "ABR board certified radiologists" were used for the reader evaluation. It does not specify the exact number of experts or their years of experience.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

The document does not specify the adjudication method used for the reader evaluation. It only mentions that radiologists performed the evaluation.

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

The study was a reader evaluation comparing MR images reconstructed with the new "Precise Image" feature (deep learning-based) to images from the predicate device reconstruction technology. While it involved multiple readers (radiologists) and multiple cases (implied by "MR images" and "abnormalities and pathologies"), it was primarily an evaluation of the image quality and diagnostic equivalence of the algorithm's output rather than a direct MRMC comparative effectiveness study measuring human reader improvement with AI assistance versus without.

Therefore, the document does not provide an effect size of how much human readers improve with AI vs without AI assistance. The focus was on the performance of the algorithm's output itself in comparison to existing technology.

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

Yes, a standalone evaluation was implicitly done through the "reader evaluation by ABR board certified radiologists." The radiologists assessed the properties of the images generated by the new Precise Image technique against images from the predicate reconstruction technology. This assesses the algorithm's output quality and diagnostic value in a standalone capacity, even though humans are interpreting its output.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

The ground truth for the reader evaluation seems to be based on expert assessment/consensus by the ABR board-certified radiologists, who evaluated image properties (SNR, artifact level, sharpness, CNR) and the visualization of abnormalities/pathologies. The document doesn't explicitly mention external pathology or outcomes data as the primary ground truth for this specific evaluation, rather the expert interpretation of the images.

8. The sample size for the training set

The document does not mention the sample size used for the training set of the deep learning-based "Precise Image" reconstruction technique.

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

The document does not provide information on how the ground truth for the training set was established for the deep learning-based "Precise Image" technique. It only describes the nature of the technique as "deep learning based reconstruction."

Ask a specific question about this device

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 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.

The proposed MR 5300 and MR 7700 R11 MR Systems are 60 cm and 70 cm bore 1.5 and 3.0 Tesla (1.5T and 3.0T) Magnetic Resonance Diagnostic Devices, hereafter to be known as MR 5300 and MR 7700 MR Systems.

This Special 510(k) submission will include modifications of the proposed MR 5300 and MR 7700 R11 MR Systems as compared to our legally marketed devices, primary predicate device Achieva, Ingenia, Ingenia CX, Ingenia Elition and Ingenia Ambition MR Systems R11 (K213583, 05/16/2022) and the secondary predicate devices Ingenia 3.0T, Ingenia 3.0T CX, Ingenia Elition, and MR 7700 with distributed Multi Nuclei (K213516, 03/03/2022) and MR 5300 (K212673, 11/19/2021).

The proposed MR 5300 and MR 7700 MR systems will be brought up to the new baseline software R11. This R11 software is cleared on the Achieva, Ingenia, Ingenia CX, Ingenia Elition, and Ingenia Ambition MR Systems in the following primary predicate 510(k) Achieva, Ingenia, Ingenia CX, Ingenia Elition and Ingenia Ambition MR Systems R11 (K213583, 04/15/2022). Both the proposed MR 5300 and MR 7700 MR systems are already cleared with the secondary predicate devices Ingenia 3.0T, Ingenia 3.0T CX, Ingenia Elition, and MR 7700 with distributed Multi Nuclei (K213516, 03/03/2022) and MR 5300 (K212673, 11/19/2021).

Here's an analysis of the acceptance criteria and study information provided in the document:

1. Table of Acceptance Criteria and Reported Device Performance:

The document states: "The verification and/or validation test results demonstrate that the proposed MR 5300 and MR 7700 R11 MR Systems meet the acceptance criteria and are adequate for the intended use." and "The results of these tests demonstrate that the proposed MR 5300 and MR 7700 R11 MR Systems meet the acceptance criteria and are adequate for the intended use."

However, the provided text does not explicitly list specific acceptance criteria in a tabular format, nor does it quantify specific performance metrics for the device against such criteria. Instead, it refers to broad compliance with standards and successful completion of verification/validation tests. The device's performance is implicitly stated as "meeting the acceptance criteria" of these tests and compliance with recognized standards.

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

The document broadly mentions "Non-Clinical verification and or validation tests have been performed with regards to the intended use, the technical claims, the requirement specifications and the risk management results."

However, the text does not provide any details about the sample size (e.g., number of cases, number of images) used for these non-clinical verification and validation tests. It also does not specify the data provenance (e.g., country of origin, retrospective or prospective nature) of any data used in these tests.

3. Number of Experts Used to Establish Ground Truth and Qualifications:

The document makes no mention of experts being used to establish ground truth for a test set. The validation primarily focuses on technical compliance and functional verification against internal specifications and external standards.

4. Adjudication Method for the Test Set:

No information is provided regarding an adjudication method. This is consistent with the lack of expert involvement in establishing ground truth for a test set described in the document.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

The document explicitly states: "The proposed Ingenia MR 5300 and MR 7700 R11 MR Systems did not require a clinical study since substantial equivalence to the legally marketed predicate device was proven with the verification/validation testing."

Therefore, no MRMC comparative effectiveness study was done, and consequently, no effect size of human readers improving with AI vs. without AI assistance is reported.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

The device is an MR System, a diagnostic imaging device. The various software enhancements (e.g., SmartSpeed AI, SmartSpeed MotionFree) listed are features of the MR system. The evaluation appears to be of the integrated system's technical and safety compliance rather than a standalone algorithm with distinct performance metrics evaluated without human intervention. The provided text does not describe a standalone algorithm-only performance study.

7. Type of Ground Truth Used:

Given that the document describes "Non-Clinical verification and or validation tests" and mentions compliance with "technical claims, the requirement specifications and the risk management results," the "ground truth" for the tests appears to be technical specifications, functional requirements, and established industry standards rather than expert consensus on medical images, pathology results, or outcomes data. The clearance is based on substantial equivalence to predicate devices demonstrated through these non-clinical tests.

8. Sample Size for the Training Set:

The document does not provide any information regarding a training set sample size. This is consistent with the nature of the submission, which focuses on hardware and software enhancements to existing medical devices rather than the development and validation of a new AI model requiring a separate training dataset. The AI functions mentioned (SmartSpeed AI) are integrated into the system, and their validation is part of the overall system's non-clinical testing.

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

As no training set is described, no information is provided on how ground truth for a training set was established.

Ask a specific question about this device

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 extremites, 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.

The proposed MR 5300 R5.8 with Breeze Workflow Solution is a 70 cm bore 1.5 Tesla (1.5T) Magnetic Resonance Diagnostic Device, hereafter to be known as MR 5300. Philips Medical Systems Nederland B.V. believes that the proposed MR 5300 is a modification of our legally marketed devices Achieva, Intera, Ingenia, Inqenia CX, Ingenia Elition and Ingenia Ambition MR systems (K193215, 04/10/2020), among which MR 5300 is specifically predicated to the Ingenia Ambition S. In this 510(k) submission, Philips Medical Systems Nederland B.V. will be addressing the following modifications to the proposed MR 5300 when compared to the legally marketed predicate Ingenia Ambition S: 1. Introduction of new product model: MR 5300 2. Introduction of Breeze Workflow Solution: a. dS Interface: newly developed 16 channel dS interface to connect coils to the MR 5300 system. The dS Interface allows to connect two coils at the same time to one dS Interface. dS Interface is available in two variants: dS interface S 1.5T with a short cable o dS interface L 1.5T with a longer cable O b. Rearrangement of connector layout of the patient table to fit to the dS Interface. Connectors are not changed. Comfort Mattress Partner to improve patient setup, C. patient comfort and cable management. Besides enable the new product model MR 5300 and the coils mentioned above. There is no new software features introduced in SW R5.8. The proposed MR 5300 is intended to be marketed with the following pulse sequences and coils that are previously cleared by FDA: 1. mDIXON (K102344) 2. SWlp (K131241) 3. mDIXON-Quant (K133526) 4. mDIXON XD (K143128) 5. O-MAR (K143253) 6. MultiBand SENSE software application (K162940), to support MutiBand SENSE for 1.5T and to support diffusion body imaging on 1.5T and 3.0T.

Based on the provided text, the device in question is the Philips MR 5300, a Magnetic Resonance Diagnostic Device. This submission is an abbreviated 510(k) and focuses on modifications to a legally marketed predicate device (Ingenia Ambition S).

It is crucial to understand that this document does not describe acceptance criteria or a study that proves the device meets specific performance criteria in the context of an AI/algorithm. Instead, it is a 510(k) summary for a hardware magnetic resonance imaging (MRI) system (MR 5300) and its software release R5.8, along with a "Breeze Workflow Solution" that includes interface and patient comfort improvements.

The document explicitly states that the proposed MR 5300 is demonstrated to be substantially equivalent to its predicate device through non-clinical performance (verification and validation) tests that comply with international and FDA-recognized consensus standards. Crucially, it states: "The proposed MR 5300 did not require a clinical study since substantial equivalence to the legally marketed predicate device was proven with the verification/validation testing."

Therefore, I cannot provide the information requested about acceptance criteria and a study proving the device meets an AI/algorithm-specific acceptance criteria, as this information is not present in the provided text. The device described is a medical imaging system, not an AI or algorithm that generates a diagnostic output requiring a performance study in the way requested for AI.

However, I can extract information related to the general acceptance of the device's safety and effectiveness based on the non-clinical testing performed:

1. Table of Acceptance Criteria and Reported Device Performance (as inferred from the provided text for a hardware MRI system):

Since this is a hardware device clearance based on substantial equivalence and compliance with standards, the "acceptance criteria" are compliance with various technical and safety standards, and the "performance" is that it meets these standards and is comparable to the predicate.

2. Sample size used for the test set and data provenance:
Not applicable as this is not an AI/algorithm performance study. The "tests" are non-clinical verification and validation of the hardware against engineering requirements and safety standards. No patient data "test set" in the context of an AI algorithm is mentioned or implied.

3. Number of experts used to establish the ground truth for the test set and qualifications:
Not applicable. No ground truth for an AI/algorithm test set was established. The "ground truth" for a hardware device is compliance with its engineering specifications and safety standards.

4. Adjudication method for the test set:
Not applicable.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:
"The proposed MR 5300 did not require a clinical study since substantial equivalence to the legally marketed predicate device was proven with the verification/validation testing." Therefore, no MRMC study was done.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
Not applicable. This is a hardware MRI system.

7. The type of ground truth used:
For a hardware device, the ground truth is its compliance with validated engineering specifications, safety standards (e.g., electrical, mechanical, RF safety, EMC), and functional performance parameters (e.g., field homogeneity, gradient linearity, signal-to-noise ratio, image quality metrics) established through non-clinical testing. This is not derived from clinical outcomes or expert consensus in the typical sense for AI, but from objective physical measurements and adherence to regulations.

8. The sample size for the training set:
Not applicable. This is a hardware MRI system, not a machine learning model that requires a training set in this context.

9. How the ground truth for the training set was established:
Not applicable.

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