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This system is a Magnetic Resonance Medicated for use as a diagnostic device. The system can produce cross-sectional images spectra in any orientation of the internal structure of the head, body or extremities.

Magnetic Resonance images represent 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. The image acquisition process can be synchronized 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 the 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. The use of contrast agents for diagnostic imaging applications should be performed consistent with the approved labeling for the contrast agent.

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 1.5T, Ingenia 1.5T S, Ingenia 1.5T CX, Ingenia 3.0T, and Ingenia 3.0T CX R5.4 with Compressed SENSE feature is applicable for the 60 cm (CX) and 70 cm magnet systems. The systems and control software are substantially equivalent to the legally marketed primary predicate device Ingenia 1.5T, Ingenia 1.5T S and Ingenia 3T R5.3 (K163116, 01/06/2017).

The proposed Ingenia 1.5T, Ingenia 1.5T S, Ingenia 1.5T CX, Ingenia 3.0T, and Ingenia 3.0T CX R5.4 with the Compressed SENSE feature also includes minor software changes since the clearance of the legally marketed primary predicate device, Ingenia 1.5T, Ingenia 1.5T S and Ingenia 3T R5.3 (K163116, 01/06/2017).

The following modifications are covered in this submission:

1. Upgrade software platform to Windows 10
2. Compressed SENSE feature allows ultra-high acceleration factors for shorter scan times and higher resolution in 2D and 3D imaging based on the principle of Compressed sensing in combination with SENSE.
3. PerformanceBridge Protocol Manager Release 1.0 offering intended to help customers increase collaboration within a healthcare facility group. Customers will enter the Protocol Manager cloud functionality via the PerformanceBridge portal. Protocol Manager is a subscription service to a cloud based protocol repository that will allow a user to standardize protocols over the various connected MRI systems, enable editing of protocols and scan parameters and make central protocols available for use on local MRI systems.

The proposed Ingenia 1.5T, Ingenia 1.5T S and Ingenia 3.0T, Ingenia 1.5T CX, and Ingenia 3.0T CX R5.4 with Compressed SENSE feature is intended to be marketed with the following pulse sequences and coils that were 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. MultiBand SENSE K143606
8. Ingenia Coils See Appendix 004 and Appendix 007

The Philips Ingenia 1.5T, Ingenia 1.5T S, Ingenia 1.5T CX, Ingenia 3.0T, and Ingenia 3.0T CX R5.4 with the Compressed SENSE feature did not involve an AI algorithm in the typical sense of machine learning for diagnosis or prediction. Instead, "Compressed SENSE" refers to an image acquisition and reconstruction technique for Magnetic Resonance Imaging (MRI) that uses compressed sensing principles to achieve faster scan times and/or higher resolution. Therefore, the device's performance acceptance criteria and study design are related to image quality and system functionality rather than AI diagnostic performance.

Here's an analysis of the provided information based on your request, with the understanding that the "device" in question is an MRI system with an advanced imaging feature:

Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of numerical acceptance criteria for a "device performance" in terms of diagnostic accuracy, sensitivity, or specificity, as would be expected for an AI-powered diagnostic tool. Instead, the acceptance criteria are generally stated as compliance with regulatory standards and the demonstration of substantial equivalence to a predicate device. The performance is assessed based on a comparison of images produced by the new feature to those from the predicate device and established imaging principles.

Study Details:

1. Sample size used for the test set and the data provenance:

   • The document states that "sample clinical images" were used. However, it does not specify a numerical sample size for a test set in the context of an analytical or clinical performance study.
   • Data provenance: Not explicitly stated, but given Philips' global operations, it's likely a combination of internal data or data from clinical sites where their systems are installed. The study is described as "non-clinical verification and or validation tests" combined with sample clinical images, suggesting a retrospective evaluation of existing images or images acquired during validation protocols.

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

   • This information is not provided in the document, as the submission focuses on the technical equivalence and safety of the MRI system and its new imaging feature (Compressed SENSE), rather than a diagnostic performance study requiring expert ground truth establishing for a specific pathology. The "ground truth" for an MRI system's image reconstruction capability is typically evaluated against physical phantoms (known objects) and expert review of image quality (e.g., signal-to-noise ratio, spatial resolution, artifact levels, anatomical depiction) by MR physicists and radiologists.

3. Adjudication method for the test set:

   • This information is not applicable/provided as there was no formal diagnostic performance study described that would require an adjudication method for ground truth establishment by multiple experts.

4. 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 done. The document explicitly states: "The proposed Ingenia 1.5T, Ingenia 1.5T S, Ingenia 1.5T CX, Ingenia 3.0T, and Ingenia 3.0T CX R5.4 with the Compressed SENSE feature did not require a clinical study since substantial equivalence to the legally marketed predicate device was proven with the verification/validation testing."
   • Furthermore, the "Compressed SENSE" feature is an imaging technique, not an AI diagnostic tool, so improving human readers with AI assistance is not the objective here. The goal is to produce images of comparable diagnostic quality with faster acquisition or higher resolution.

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

   • Not applicable in the context of an AI diagnostic algorithm. The "Compressed SENSE" is an image reconstruction algorithm that operates intrinsically within the MRI system to produce images for interpretation by a human. Its performance is effectively its ability to produce diagnostically acceptable images.

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

   • For the technical validation of Compressed SENSE, the "ground truth" would likely involve:
     • Physical phantoms: Objects with known properties used to objectively measure image quality metrics (e.g., spatial resolution, signal-to-noise ratio, uniformity).
     • Comparison to gold standard MRI sequences: Images acquired with conventional, fully sampled sequences (considered the "gold standard" for image quality, though slower) would serve as a reference for images reconstructed using Compressed SENSE.
     • Expert review of image quality: Radiologists and MR physicists would qualitatively assess the images for diagnostic acceptability, presence of artifacts, depiction of anatomical structures, and comparability to predicate device images.
   • The document mentions "sample clinical images" were part of the validation, implying expert review of these images for diagnostic acceptability.

7. The sample size for the training set:

   • Not applicable/provided. Compressed SENSE, while employing sophisticated mathematics (compressed sensing), is primarily a signal processing and image reconstruction technique rather than a machine learning algorithm that requires a separate "training set" for diagnostic classification. The parameters for compressed sensing reconstruction are typically derived from theoretical principles and validated through experimentation, rather than trained from a large labeled dataset in the same way a deep learning model would be.

8. How the ground truth for the training set was established:

   • Not applicable/provided as there was no distinct "training set" in the context of an AI diagnostic model. The development of Compressed SENSE relies on mathematical principles and engineering validation.

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This system is a Magnetic Resonance Medical Electrical Systems indicated for use as a diagnostic device. The system can produce cross-sectional images, spectroscopic images and/or spectra in any orientation of the internal structure of the head, body or extremities.

Magnetic Resonance images represent 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. The image acquisition process can be synchronized 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 the 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. The use of contrast agents for diagnostic imaging applications should be performed consistent with the approved labeling for the contrast agent.

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 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 Elition S and Ingenia Elition X R5.4 with new gradient system/specifications are modifications of the 70 cm Ingenia 3.0T system, included in the legally marketed predicate device Ingenia 1.5T, Ingenia 1.5T S and Ingenia 3.0T R5.3 (K163116, 01/06/2017). The systems and control software are substantially equivalent to the legally marketed predicate device Ingenia 1.5T, Ingenia 1.5T S and Ingenia 3.0T R5.3 (K163116, 01/06/2017). Hereafter Ingenia Elition S and Ingenia Elition X R5.4 will be used to indicate the proposed device Ingenia Elition S and Ingenia Elition X R5.4 with new gradient system/specifications The proposed Ingenia Elition S and Ingenia Elition X R5.4 also includes minor software changes since the clearance of the legally marketed predicate device, Ingenia 1.5T, Ingenia 1.5T S and Ingenia 3.0T R5.3 (K163116, 01/06/2017). The following modifications are covered compared to legally marketed predicate device: 1. Upgrade of SW platform to Windows 10 and PSC 6.1 (to be compatible with Windows 10); 2. PerformanceBridge Protocol Manager Release 1.0; 3. Introduction of new gradient system hardware with new qradient specifications: 4. Introduction of new product name and covers. The proposed Ingenia Elition S and Ingenia Elition X R5.4 are intended to be marketed with the following pulse sequences and coils that were 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. MultiBand SENSE K143606 8. Ingenia Coils See Appendix 004

The provided text is a 510(k) summary for the Philips Ingenia Elition S and Ingenia Elition X R5.4 Magnetic Resonance Diagnostic Devices. This document does not describe acceptance criteria or a specific study proving the device meets acceptance criteria in the way typically expected for an AI/algorithm-based device's performance.

Instead, this submission focuses on demonstrating substantial equivalence to a predicate device (Ingenia 1.5T, Ingenia 1.5T S and Ingenia 3.0T R5.3, K163116) through non-clinical performance data and compliance with recognized standards. The "acceptance criteria" referred to in the document are general statements about meeting regulatory and safety standards for an MRDD, rather than specific performance metrics (e.g., sensitivity, specificity, AUC) for an AI algorithm.

Therefore, many sections of your requested output cannot be fulfilled from the provided text.

Here's what can be extracted and inferred:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Not Applicable. The document explicitly states: "The proposed Ingenia Elition S and Ingenia Elition X R5.4 did not require a clinical study since substantial equivalence to the legally marketed predicate device was proven with the verification/validation testing."
• The "test set" in this context refers to non-clinical verification and validation tests, not a dataset of patient images for an algorithm's performance evaluation. No information on sample size or data provenance (country of origin, retrospective/prospective) for such tests is provided.

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

• Not Applicable. As no clinical study was performed for AI algorithm performance, there's no mention of experts establishing a ground truth for a test set.

4. Adjudication Method for the Test Set:

• Not Applicable. No clinical study or performance evaluation with a test set requiring adjudication is described.

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

• No. The document explicitly states no clinical study was required. Therefore, an MRMC study was not performed.

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

• Not Applicable. This submission is for an MRI system, not a standalone AI algorithm. The performance evaluation focuses on the safety and effectiveness of the MRI system, not an AI component's standalone diagnostic capabilities.

7. The Type of Ground Truth Used:

• Not Applicable. For the non-clinical verification and validation tests, the "ground truth" would be established by engineering specifications, regulatory standards, and expected physical performance parameters of the MRI system, rather than expert consensus, pathology, or outcomes data related to an algorithm's diagnostic output. The document doesn't detail the specifics of these non-clinical ground truths.

8. The Sample Size for the Training Set:

• Not Applicable. This is not a submission for an AI/ML algorithm that requires a training set. The "software changes" mentioned are minor updates to the operating system and existing functionalities, not the development of a new AI model requiring training data.

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

• Not Applicable. No AI/ML algorithm requiring a training set is described.

In summary:

This 510(k) submission primarily details the device (an MRI system) modifications and demonstrates substantial equivalence to a previously cleared predicate device through compliance with various non-clinical standards and tests. It does not involve the evaluation of an AI algorithm's diagnostic performance against specific acceptance criteria using patient data, and thus, many of the requested details are not present in this type of regulatory filing.

Ask a specific question about this device

This system is a Magnetic Resonance Medical Electrical Systems indicated for use as a diagnostic device. The system can produce cross-sectional images, spectroscopic images and/or spectra in any orientation of the internal structure of the head, body or extremities.

Magnetic Resonance images represent 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, and the MR scan technique applied. The image acquisition process can be synchronized 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 the 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. The use of contrast agents for diagnostic imaging applications should be performed consistent with the approved labeling for the contrast agent.

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 Elition S and Ingenia Elition X R5.4 with new gradient system/specifications are modifications of the 70 cm Ingenia 3.0T system, included in the legally marketed predicate device Ingenia 1.5T, Ingenia 1.5T S and Ingenia 3.0T R5.3 (K163116, 01/06/2017).

The systems and control software are substantially equivalent to the legally marketed predicate device Ingenia 1.5T, Ingenia 1.5T S and Ingenia 3.0T R5.3 (K163116, 01/06/2017).

Hereafter Ingenia Elition S and Ingenia Elition X R5.4 will be used to indicate the proposed device Ingenia Elition S and Ingenia Elition X R5.4 with new gradient system/specifications

The proposed Ingenia Elition S and Ingenia Elition X R5.4 also includes minor software changes since the clearance of the legally marketed predicate device, Ingenia 1.5T, Ingenia 1.5T S and Ingenia 3.0T R5.3 (K163116, 01/06/2017).

The following modifications are covered compared to legally marketed predicate device:

1. Upgrade of SW platform to Windows 10 and PSC 6.1 (to be compatible with Windows 10);
2. PerformanceBridge Protocol Manager Release 1.0;
3. Introduction of new gradient system hardware with new gradient specifications;
4. Introduction of new product name and covers.

The proposed Ingenia Elition S and Ingenia Elition X R5.4 are intended to be marketed with the following pulse sequences and coils that were 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. MultiBand SENSE K143606

This document describes the 510(k) summary for the Philips Ingenia Elition S and Ingenia Elition X R5.4 Magnetic Resonance Diagnostic Devices. The submission focuses on demonstrating substantial equivalence to a predicate device (Ingenia 1.5T, Ingenia 1.5T S and Ingenia 3.0T R5.3, K163116) rather than proving performance based on specific clinical outcomes for a novel application. Therefore, the details requested in the prompt, which are typically associated with performance studies for AI/CADe devices, are largely not present in this type of submission.

Based on the provided text, here's what can be extracted:

• Device: Ingenia Elition S and Ingenia Elition X R5.4 (Magnetic Resonance Diagnostic Device - MRDD)
• Submission Type: 510(k) Premarket Notification, Abbreviated 510(k)
• Purpose of Submission: To demonstrate substantial equivalence to a legally marketed predicate device due to modifications (new gradient system/specifications, software upgrades like Windows 10 compatibility and PerformanceBridge Protocol Manager, new product name/covers).

Here's an analysis of the provided text in relation to your specific questions:

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

The document states: "The verification and/or validation test results demonstrate that the proposed Ingenia Elition S and Ingenia Elition X R5.4: • Complies with the aforementioned international and FDA recognized consensus standards and Device specific guidance document, entitled "Guidance for the Submission Of Premarket Notifications for Magnetic Resonance Diagnostic Devices - November 18, 2016" • Meets the acceptance criteria and is adequate for its intended use."

It further concludes: "The results of these tests demonstrate that the proposed Ingenia Elition S and Ingenia Elition X R5.4 meet the acceptance criteria and is adequate for its intended use."

However, the specific "acceptance criteria" (e.g., in terms of image quality metrics, diagnostic accuracy, or specific performance thresholds) and the "reported device performance" against those criteria are not detailed in this 510(k) summary. This type of submission relies on demonstrating compliance with recognized standards and that the modifications do not raise new questions of safety or effectiveness compared to the predicate device. The performance is implied to be equivalent to the predicate, which presumptively met certain performance standards.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not provided in the document. The submission states, "The proposed Ingenia Elition S and Ingenia Elition X R5.4 did not require a clinical study since substantial equivalence to the legally marketed predicate device was proven with the verification/validation testing." This indicates that formal clinical studies with distinct test sets, common for AI/CADe devices, were not performed or submitted for this 510(k). The "verification/validation testing" likely refers to engineering, phantom, and perhaps limited clinical image quality checks, rather than a full-scale clinical trial.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This information is not provided. As no clinical study needing ground truth establishment was conducted for this 510(k) submission, there's no mention of experts or their qualifications for establishing ground truth on a test set.

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

This information is not provided. As no clinical study needing a test set with ground truth was conducted for this 510(k) submission, there's no mention of an adjudication method.

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 MRMC comparative effectiveness study was done as part of this submission. This device is a Magnetic Resonance Diagnostic Device (an MRI scanner itself), not an AI/CADe algorithm designed to assist human readers. The clearance is for the hardware and basic software functionality rather than an AI-driven interpretive aid.

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

This question is not directly applicable. This is an MRI device, not a standalone algorithm. The "performance" relates to its ability to acquire images, not to automatically interpret them.

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

This information is not provided. Given that no clinical study was performed for this 510(k) submission (as stated: "The proposed Ingenia Elition S and Ingenia Elition X R5.4 did not require a clinical study..."), the concept of ground truth for a clinical validation set is not applicable here. The "ground truth" for the performance of an MR system typically relies on physical measurements in phantoms and comparison against established image quality metrics, rather than clinical outcomes or expert consensus for diagnosis.

8. The sample size for the training set

This information is not provided and is not relevant for this type of device submission. This is not an AI/ML device that requires a training set. The changes are hardware (gradient system) and basic software (OS upgrade, protocol manager).

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

This information is not provided and is not relevant for this type of device submission, as there's no training set mentioned for an AI/ML model.

Summary of the Study Proving Acceptance (as implied by the document):

The "study" proving the device meets acceptance criteria was a series of non-clinical verification and validation tests. These tests were designed to demonstrate:

• Compliance with recognized standards: IEC 60601-1 (medical electrical equipment), IEC 60601-1-2 (EMC), IEC 62366 (usability), IEC 60601-1-8 (alarms), IEC 60601-2-33 (MR specific safety), IEC 62304 (software life cycle), NEMA MS-1, MS-4, MS-8, PS 3.1-3.20 (MR performance and DICOM standards), ISO 14971 (risk management).
• Compliance with FDA guidance documents: Specifically, "Guidance for the Submission Of Premarket Notifications for Magnetic Resonance Diagnostic Devices – November 18, 2016" and other relevant guidances for software, human factors, cybersecurity, biocompatibility, and EMC.
• Equivalence to the predicate device: The new gradient system and software changes were evaluated to ensure they did not negatively impact the imaging performance (image quality, safety parameters) or introduce new risks compared to the predicate device.

The document states that these tests demonstrate the device "Meets the acceptance criteria and is adequate for its intended use." The "acceptance criteria" are intrinsically tied to meeting these regulatory standards and demonstrating that the modifications do not alter the substantial equivalence to the predicate. The document does not provide quantitative performance metrics from these tests.

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