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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 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 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, 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 R 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 submission covers the proposed Achieva 1.5T, Achieva 3.0T, and the Intera 1.5T MR Systems R5.6, hereafter to be known as Achieva 1.5T, 3.0T, and Intera 1.5T MR Systems. The proposed Achieva 1.5T, 3.0T, and Intera 1.5T MR Systems are 60 cm bore 1.5 Tesla (1.5T) and 3.0 Tesla (3.0T) Magnetic Resonance Diagnostic Devices. This submission of the proposed Achieva 1.5T, 3.0T, and Intera 1.5T MR Systems contains a description of the software and hardware modifications made since the last 510(k) clearance of the primary predicate Achieva, Intera & Panorama 1.0T R2.5 (K063559, 01/04/2007). The Achieva 1.5T and Intera 1.5T systems differ in outside covers only, both systems function in an identical manner. The proposed Achieva 1.5T, 3.0T and Intera 1.5T MR Systems are substantially equivalent to the primary predicate Achieva, Intera & Panorama 1.0T R2.5 (K063559, 01/04/2007), and the 1st legally marketed reference device Ingenia, Ingenia CX, Ingenia Elition, and Ingenia Ambition (K183063, 02/14/2019) and the 2nd legally marketed reference device Achieva R4 1.5T and Achieva R4 3.0T (aka Ingenia, K110151, 03/22/2011). The proposed Achieva 1.5T, 3.0T, and Intera 1.5T MR Systems 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. 3D APT (K172920) 9. Achieva and Intera Coils

Here's a breakdown of the acceptance criteria and study information for the Philips Achieva 1.5T, 3.0T, and Intera 1.5T MR Systems, based on the provided text:

Important Note: The provided document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed clinical study for a novel device. As such, information typically found in a clinical study report (like detailed statistical methods, effect sizes for human readers with and without AI, or specific ground truth methodologies for a novel algorithm) is not present in this type of submission. The device described is a Magnetic Resonance (MR) system, which is a diagnostic imaging device, not a specific AI-powered diagnostic algorithm.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Sample Size: Not applicable. This submission relies on non-clinical verification and validation tests rather than a separate clinical test set with patient data for assessing a new algorithm's performance. The device is an MR system, and the evaluation focuses on its technical performance and safety, not on the diagnostic accuracy of a new AI algorithm processing patient data.
• Data Provenance: Not applicable for a separate clinical test set. The non-clinical tests would involve engineering and performance evaluations in a controlled environment, not patient data from a specific country or collected retrospectively/prospectively for a new algorithm's evaluation.

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

• Number of Experts/Qualifications: Not applicable. As this involves non-clinical verification and validation testing of an MR system's performance and safety features (e.g., image quality, electromagnetic compatibility, software functionality), the "ground truth" would be established by engineering and quality assurance standards, benchmarks, and regulatory requirements, not by expert interpretation of patient images for diagnostic accuracy.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. Since there's no clinical test set requiring expert interpretation and consensus, there's no need for an adjudication method.

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

• MRMC Study Done: No. An MRMC study is typically performed to evaluate the impact of a new diagnostic algorithm on human reader performance (e.g., radiologists interpreting images with and without AI assistance). This submission pertains to an MR system, which is the imaging hardware and associated software to acquire images. The document explicitly states: "The proposed Achieva 1.5T, 3.0T, and Intera 1.5T MR Systems did not require a clinical study since substantial equivalence to the primary predicate device was proven with the verification/validation testing."
• Effect Size of Human Readers with vs. without AI: Not applicable, as no MRMC study was performed.

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

• Standalone Study Done: No. The device is an MR imaging system; it is not a standalone AI algorithm designed to provide diagnostic outputs independently. The output of the MR system (images, spectra, measurements) is intended to be interpreted by a trained physician.

7. Type of Ground Truth Used

• Type of Ground Truth: Not applicable in the context of diagnostic accuracy for a specific algorithm. For the non-clinical verification and validation, the ground truth would be defined by engineering specifications, regulatory standards, and established benchmarks for parameters like image quality, signal-to-noise ratio, spatial resolution, gradient linearity, safety limits (e.g., SAR), and software functionality.

8. Sample Size for the Training Set

• Training Set Sample Size: Not applicable. The document describes an MR imaging system, not a machine learning or AI algorithm that would typically require a training set of data. While the system's software components were developed and tested, the information provided does not indicate the use of a data-driven training set in the context of an FDA-cleared AI/ML algorithm.

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

• Ground Truth for Training Set: Not applicable, as there is no mention of a training set or an AI/ML algorithm requiring such.

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mDIXON is a software option intended for use on Intera 1.5T, Achieva 1.5T and Achieva 3T. MR Systems. It is indicated for magnetic resonance imaging of the chest, abdomen and pelvis. mDIXON is a multipoint (echo) method for 3D clinical imaging with the possibility to reformat into multiple planes (axial, sagittal and coronal). mDIXON provides improved fat suppression, increased scan speed in addition and/or an improved signal-to-noise relative to other current 3D volumetric fat suppressed imaging methods

The modified-DIXON (mDIXON) sequence is a novel two and multi-point method for 2D and 3D water-fat magnetic resonance imaging. mDIXON is a modification of previous DIXON implementations due to the unrestricted echo-time (TE) approach. This allows more freedom in protocol optimization resulting in more efficient (faster) scanning and an increase in signal to noise (SNR). Additionally, it provides a technique for improved fat suppression (in comparison to other current 3D volumetric fat suppressed imaging methods.) While the primary use is for torso imaging, it may also be applicable to other anatomies requiring in- and opposed-phase, water-only, and/or fatonly imaging. While the current 3D volumetric fat suppressed technique (e-THRIVE) is an imaging method, mDIXON is a multi echo sequence with multiple gradient echo readouts. Phase and amplitude of complex data acquired at different echo times are used to separate the water and fat signals. The separation is made possible by the chemical shift difference between water and fat. The resultant images can be reconstructed to produce "water-only" images, "fat-only" images and in-phase/opposed-phase images (synthesized from the acquired multiecho images). The fat suppression is enhanced especially at the edges of larger fields of view due to the mDIXON reconstruction algorithm and its use of the chemical shift difference between water and fat.

Acceptance Criteria and Study for Philips mDIXON Software Option (K102344)

The provided document describes the Philips mDIXON software option for MR systems. It highlights the device's improvements over existing 3D volumetric fat-suppressed imaging methods, specifically regarding fat suppression, scan speed, and signal-to-noise ratio (SNR). However, it does not explicitly state specific numerical acceptance criteria or detail a formal clinical study to prove these criteria.

Instead, the documentation focuses on:

• Verification and Validation (V&V) Testing: Stating that "mDIXON verification and validation tests were performed on the complete system relative to the requirement specification and risk management results. Corresponding test results are included in this submission." This implies that internal tests were conducted against pre-defined requirements, but the specifics of these requirements and their quantitative thresholds are not provided in this summary.
• Substantial Equivalence: The primary strategy for regulatory clearance (510(k)) relies on demonstrating substantial equivalence to predicate devices (INTERA 1.5T, ACHIEVA 1.5T, ACHIEVA 3.0T MR systems Release 2.5-series and the IDEAL software option). The core argument is that the mDIXON option does not introduce new risks and maintains the safety and effectiveness profile of these predicate devices, while offering improved performance.

Given the information, a table of explicit acceptance criteria and corresponding performance cannot be created directly as they are not explicitly mentioned in this summary. The assessment revolves around the general claims of improvement and the maintenance of safety and effectiveness as per predicate devices.

Based on the provided text, here's an analysis of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document does not explicitly list quantitative acceptance criteria for mDIXON. The performance claims are qualitative improvements over current 3D volumetric fat-suppressed imaging methods. The "acceptance" is implied by the successful completion of V&V testing and the FDA's determination of substantial equivalence.

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

• Sample Size: Not specified. The document only mentions "mDIXON verification and validation tests were performed," but no details on the number of cases, subjects, or data points in the test set.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective).

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

• Not specified. The document does not describe the involvement of human experts or ground truth establishment for specific test cases. The V&V process likely involved technical assessments rather than clinical evaluations by experts described here.

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

• Not specified. There is no mention of an adjudication process for a test set in the summary provided.

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, a MRMC comparative effectiveness study is not mentioned. This document pertains to a software option for an MR system, enhancing image acquisition and reconstruction, not a diagnostic AI tool for interpretation. Therefore, a study comparing human reader performance with and without AI assistance is not described or relevant for this type of device based on the provided information.

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

• The mDIXON is itself an "algorithm only" (software option) that generates images. The "standalone" performance
  is assessed by its ability to produce images with improved characteristics (fat suppression, scan speed, SNR) compared to existing methods. The validation of these characteristics is stated to have been performed through V&V tests, but no specific study details are given beyond this general statement. Essentially, the device is the algorithm, and its performance is evaluated on the quality of the output images.

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

• Not explicitly stated. Given the nature of the device (image acquisition/reconstruction), the "ground truth" for the V&V tests would likely be related to objective measures of image quality (e.g., quantitative fat suppression metrics, SNR measurements, acquisition time) compared against a reference standard or expected performance, rather than clinical ground truth like pathology or expert consensus on disease presence.

8. The sample size for the training set

• Not applicable/Not specified. The mDIXON sequence is a physics-based magnetic resonance imaging technique, not a machine learning model that requires a "training set" in the conventional sense. Its development would involve engineering and physics principles rather than data-driven training.

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

• Not applicable. See point 8.

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ACHIEVA 1.5T & INTERA 1.5T family consists of diagnostic devices that produce crosssectional images, spectroscopy images and/or spectra in any orientation of the internal structure of the whole body. These images when interpreted by a trained physician yield information that may assist in diagnosis.

The ACHIEVA 1.5T & INTERA 1.5T family is the successor of the predicate ACHIEVA family release 1-series. The design of ACHIEVA 1.5T & INTERA 1.5T family is based on the same software platform and hardware technology as its predicate device. All MR system parts of the ACHIEVA 1.5T & INTERA 1.5T family have the same appearance. The new gradient configurations are more powerful than their previous versions available on the Intera 1.5T and Achieva 1.5T systems. Especially the slewrate of these systems is improved. This improved slewrate allows for shorter echo times (TE), Echo Spacing (ES) and repetition times (TR).

The provided document is a 510(k) summary for the Philips ACHIEVA 1.5T & INTERA 1.5T family of Magnetic Resonance Diagnostic Devices (MRDD). This submission focuses on demonstrating substantial equivalence to a predicate device, rather than proving performance against specific acceptance criteria through a clinical study.

Therefore, many of the requested details about acceptance criteria, study design, sample sizes, expert involvement, and ground truth are not applicable (N/A) because they are typically part of a de novo submission or a premarket approval (PMA) application, not a 510(k) for substantial equivalence based on technology upgrades.

Here's a breakdown of the information that can be extracted or that is N/A based on the document:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• N/A. This submission leverages the substantial equivalence pathway, not a clinical trial with a distinct test set to evaluate performance against specific criteria. The comparison is primarily against the predicate device's existing clearance and safety profile.

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

• N/A. As no new clinical study with a test set for diagnostic accuracy was conducted for this 510(k), there wasn't a process described for establishing clinical ground truth for a test set. The "ground truth" implicitly relies on the established safety and effectiveness of the existing predicate device.

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

• N/A. No clinical test set requiring adjudication was used as part of this substantial equivalence submission.

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:

• N/A. This device (Magnetic Resonance Diagnostic Device) is a foundational imaging modality, not an AI-assisted diagnostic tool. No MRMC study or AI-related effectiveness study was performed or described.

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

• N/A. This device is an imaging hardware system, not an algorithm, and thus standalone algorithm performance is not applicable.

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

• N/A. For this 510(k) submission, the "ground truth" for demonstrating substantial equivalence is the performance and safety record of the predicate device (ACHIEVA family release 1-series, K043147). The submission asserts that the new device shares the same fundamental technology and does not introduce new safety or effectiveness concerns.

8. The sample size for the training set:

• N/A. This is a hardware and software upgrade to an existing MRI system. The concept of a "training set" as understood in machine learning/AI is not applicable here. The development would involve engineering design, testing, and validation against technical specifications rather than a data-driven training process in the AI sense.

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

• N/A. As explained above, the concept of a "training set" with established ground truth is not relevant to this type of device submission.

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