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510(k) Data Aggregation

    Why did this record match?
    Device Name :

    MAGNETOM Avanto Fit; MAGNETOM Skyra Fit; MAGNETOM Sola Fit; MAGNETOM Viato.Mobile

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The MAGNETOM system is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional images, spectroscopic images and/or spectra, and that displays the internal structure and/or function of the head, body, or extremities. Other physical parameters derived from the images and/or spectra may also be produced. Depending on the region of interest, contrast agents may be used. These images and/or spectra and the physical parameters derived from the images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis.

    The MAGNETOM system may also be used for imaging during interventional procedures when performed with MR compatible devices such as in-room displays and MR Safe biopsy needles.

    Device Description

    The subject device, MAGNETOM Avanto Fit with software syngo MR XA70A, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Avanto Fit with syngo MR XA50A (K220151).

    A high-level summary of the new and modified hardware and software is provided below:

    For MAGNETOM Avanto Fit with syngo MR XA70:

    Hardware

    New Hardware:
    myExam 3D Camera
    BM Head/Neck 20

    Modified Hardware:
    Sanaflex (cushions for patient positioning)

    Software

    New Features and Applications:
    myExam Autopilot Brain
    myExam Autopilot Knee
    3D Whole Heart
    HASTE_interactive
    GRE_PC
    Open Recon
    Deep Resolve Gain
    Fleet Reference Scan
    Physio logging
    complex averaging
    AutoMate Cardiac
    Ghost Reduction
    BLADE diffusion
    Beat Sensor
    Deep Resolve Sharp
    Deep Resolve Boost and Deep Resolve Boost (TSE)
    Deep Resolve Boost HASTE
    Deep Resolve Boost EPI Diffusion

    Modified Features and Applications:
    SPACE improvement (high band)
    SPACE improvement (incr grad)
    Brain Assist
    Eco power mode
    myExam Angio Advanced Assist (Test Bolus)

    The subject device, MAGNETOM Skyra Fit with software syngo MR XA70A, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Skyra Fit with syngo MR XA50A (K220589).

    A high-level summary of the new and modified hardware and software is provided below:

    For MAGNETOM Skyra Fit with syngo MR XA70:

    Hardware

    New Hardware:
    myExam 3D Camera

    Modified Hardware:
    Sanaflex (cushions for patient positioning)

    Software

    New Features and Applications:
    Beat Sensor
    HASTE_interactive
    GRE_PC
    3D Whole Heart
    Deep Resolve Gain
    Open Recon
    Ghost Reduction
    Fleet Reference Scan
    BLADE diffusion
    HASTE diffusion
    Physio logging
    complex averaging
    Deep Resolve Swift Brain
    Deep Resolve Sharp
    Deep Resolve Boost and Deep Resolve Boost (TSE)
    Deep Resolve Boost HASTE
    Deep Resolve Boost EPI Diffusion
    AutoMate Cardiac
    SVS_EDIT

    Modified Features and Applications:
    SPACE improvement (high band)
    SPACE improvement (incr grad)
    Brain Assist
    Eco power mode
    myExam Angio Advanced Assist (Test Bolus)

    The subject device, MAGNETOM Sola Fit with software syngo MR XA70A, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Sola Fit with syngo MR XA51A (K221733).

    A high-level summary of the new and modified hardware and software is provided below:

    For MAGNETOM Sola Fit with syngo MR XA70:

    Hardware

    New Hardware:
    myExam 3D Camera

    Modified Hardware:
    Sanaflex (cushions for patient positioning)

    Software

    New Features and Applications:
    GRE_PC
    3D Whole Heart
    Ghost Reduction
    Fleet Reference Scan
    BLADE diffusion
    Physio logging
    Open Recon
    Complex averaging
    Deep Resolve Sharp
    Deep Resolve Boost and Deep Resolve Boost (TSE)
    Deep Resolve Boost HASTE
    Deep Resolve Boost EPI Diffusion
    AutoMate Cardiac
    Implant suite

    Modified Features and Applications:
    SPACE improvement (high band)
    SPACE improvement (incr grad)
    Brain Assist
    Eco power mode

    The subject device, MAGNETOM Viato.Mobile with software syngo MR XA70A, consists of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Viato.Mobile with syngo MR XA51A (K240608).

    A high-level summary of the new and modified hardware and software is provided below:

    For MAGNETOM Viato.Mobile with syngo MR XA70:

    Hardware

    New Hardware:
    n.a.

    Modified Hardware:
    Sanaflex (cushions for patient positioning)

    Software

    New Features and Applications:
    GRE_PC
    3D Whole Heart
    Ghost Reduction
    Fleet Reference Scan
    BLADE diffusion
    Physio logging
    Open Recon
    Complex averaging
    Deep Resolve Sharp
    Deep Resolve Boost and Deep Resolve Boost (TSE)
    Deep Resolve Boost HASTE
    Deep Resolve Boost EPI Diffusion
    AutoMate Cardiac
    Implant suite

    Modified Features and Applications:
    SPACE improvement (high band)
    SPACE improvement (incr grad)
    Brain Assist
    Eco power mode

    Furthermore, the following minor updates and changes were conducted for the subject devices:

    Low SAR Protocol minor update (for all subject devices but MAGNETOM Skyra Fit): the goal of the SAR adaptive protocols was to be able to perform knee, spine, heart and brain examinations with 50% of the max allowed SAR values in normal mode for head and whole-body SAR. The SAR reduction was achieved by parameter adaptations like Flip angle, TR, RF Pulse Type, Turbo Factor, concatenations. For cardiac clinically accepted alternative imaging contrasts are used (submitted with K232494).

    Implementation of image sorting prepare for PACS (submitted with K231560).

    Implementation of improved DICOM color support (submitted with K232494).

    Needle intervention AddIn was added all subject device (submitted with K232494).

    Inline Image Filter switchable for users: in the subject device, users have the ability to switch the "Inline image filter" (implicite Filter) on or off. This filter is an image-based filter that can be applied to specific pulse sequence types. The function of the filter remains unchanged from the previous device MAGNETOM Sola with syngo MR XA61A (K232535).

    SVS_EDIT is newly added for MAGNETOM Skyra Fit, but without any changes (submitted with K203443)

    Brain Assist received an improvement and is identical to that of snygo MR XA61A (K232535)

    Open Recon is introduced for all systems. The function of Open Recon remains unchanged from the previous submissions (submitted with K221733).

    Lock TR and FA in Bold received a minor UI update

    Implant Suite is newly introduced for MAGNETOM Sola Fit and MAGNETOM Viato.Mobile, but without any changes (submitted with K232535)

    myExam Autopilot Brain and myExam Autopilot Knee are newly introduced for the subject device MAGNETOM AVANTO Fit and are unchanged from previous submissions (submitted with K221733).

    myExam Angio Advanced Assist (Test Bolus) received a bug fixing and minimal UI improvements.

    AI/ML Overview

    The provided text is an FDA 510(k) clearance letter for various MAGNETOM MRI Systems. While it details new and modified software and hardware features, it does not include specific acceptance criteria or a study that "proves the device meets the acceptance criteria" in terms of performance metrics like sensitivity, specificity, or accuracy for a diagnostic task.

    Instead, the document focuses on demonstrating substantial equivalence to predicate devices. This is achieved by:

    • Stating that the indications for use are the same.
    • Listing numerous predicate and reference devices.
    • Detailing hardware and software changes.
    • Mentioning non-clinical tests like software verification and validation, sample clinical images, and image quality assessment to show that the new features maintain an "equivalent safety and performance profile" to the predicate devices.
    • Referencing scientific publications for certain features to support their underlying principles and utility.
    • Briefly describing the training and validation data for two AI features: Deep Resolve Boost and Deep Resolve Sharp, but without performance acceptance criteria or detailed results.

    Therefore, much of the requested information cannot be extracted from this document because it is not a study report detailing clinical performance against predefined acceptance criteria for a specific diagnostic outcome.

    However, I can extract the information related to the AI features as best as possible from the "AI Features/Applications training and validation" section (Page 16).


    Acceptance Criteria and Study Details (Limited to AI Features)

    1. Table of Acceptance Criteria and Reported Device Performance

    FeatureAcceptance CriteriaReported Device Performance
    Deep Resolve Boost(Not explicitly stated in the provided document as specific numerical thresholds, but implied through evaluation metrics.)"The impact of the network has been characterized by several quality metrics such as peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). Most importantly, the performance was evaluated by visual comparisons to evaluate e.g., aliasing artifacts, image sharpness and denoising levels." (Exact numerical results not provided).
    Deep Resolve Sharp(Not explicitly stated in the provided document as specific numerical thresholds, but implied through evaluation metrics and verification activities.)"The impact of the network has been characterized by several quality metrics such as peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and perceptual loss. In addition, the feature has been verified and validated by inhouse tests. These tests include visual rating and an evaluation of image sharpness by intensity profile comparisons of reconstructions with and without Deep Resolve Sharp." (Exact numerical results not provided).

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

    • Deep Resolve Boost:
      • Test Set Sample Size: Not explicitly stated as a separate "test set" size. The document mentions "training and validation data" for over 25,000 TSE slices, over 10,000 HASTE slices (for refinement), and over 1,000,000 EPI Diffusion slices. It's unclear what proportion of this was used specifically for final testing, or if the "validation" mentioned includes the final performance evaluation.
      • Data Provenance: Retrospective, described as "Input data was retrospectively created from the ground truth by data manipulation and augmentation." Country of origin is not specified.
    • Deep Resolve Sharp:
      • Test Set Sample Size: Not explicitly stated as a separate "test set" size. The document mentions "training and validation" on more than 10,000 high resolution 2D images. Similar to Deep Resolve Boost, it's unclear what proportion was specifically for final testing.
      • Data Provenance: Retrospective, described as "Input data was retrospectively created from the ground truth by data manipulation." Country of origin is not specified.

    3. 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. The definition of "ground truth" for the AI features refers to the acquired datasets themselves rather than expert-labeled annotations. Visual comparisons are mentioned as part of the evaluation, but without details on expert involvement or qualifications.

    4. Adjudication method for the test set

    This information is not provided in the document. While "visual comparisons" and "visual rating" are mentioned, no specific adjudication method (e.g., 2+1, 3+1) is described.

    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 demonstrating human reader improvement with AI assistance is not described in this document. The focus of the AI features (Deep Resolve Boost and Deep Resolve Sharp) is on image quality enhancement (denoising, sharpness) and reconstruction rather than assisting human readers in a diagnostic task that can be quantified by an effect size.

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

    Yes, the evaluation of Deep Resolve Boost and Deep Resolve Sharp, based on metrics like PSNR, SSIM, and perceptual loss, and "visual comparisons" or "visual rating" appears to be an assessment of the algorithm's performance in enhancing image quality in a standalone capacity, without direct human-in-the-loop interaction for diagnosis.

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

    • Deep Resolve Boost: "The acquired datasets (as described above) represent the ground truth for the training and validation." This implies the original, full-quality, unaltered MRI scan data. Further, "Input data was retrospectively created from the ground truth by data manipulation and augmentation. This process includes further under-sampling of the data by discarding k-space lines, lowering of the SNR level by addition Restricted of noise and mirroring of k-space data."
    • Deep Resolve Sharp: "The acquired datasets represent the ground truth for the training and validation." Similar to Boost, this refers to original, high-resolution MRI scan data. For training, "k-space data has been cropped such that only the center part of the data was used as input. With this method corresponding low-resolution data as input and high-resolution data as output / ground truth were created for training and validation."

    8. The sample size for the training set

    • Deep Resolve Boost:
      • TSE: more than 25,000 slices
      • HASTE (for refinement): more than 10,000 HASTE slices
      • EPI Diffusion: more than 1,000,000 slices
    • Deep Resolve Sharp: more than 10,000 high resolution 2D images.

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

    • Deep Resolve Boost: The ground truth was established by the "acquired datasets" themselves (full-quality MRI scans). The training input data was then derived from this ground truth by simulating degraded images (e.g., under-sampling, adding noise).
    • Deep Resolve Sharp: Similarly, the ground truth was the "acquired datasets" (high-resolution MRI scans). The training input data was derived by cropping k-space data to create corresponding low-resolution inputs.
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    K Number
    K240608
    Date Cleared
    2024-03-29

    (25 days)

    Product Code
    Regulation Number
    892.1000
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    MAGNETOM Viato.Mobile

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The MAGNETOM system is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional images, spectroscopic images and/or spectra, and that displays the internal structure and/or function of the head, body, or extremities. Other physical parameters derived from the images and/or spectra may also be produced. Depending on the region of interest, contrast agents may be used. These images and/or spectra and the physical parameters derived from the images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis.

    The MAGNETOM system may also be used for imaging during interventional procedures when performed with MR compatible devices such as in-room displays and MR Safe biopsy needles.

    Device Description

    MAGNETOM Viato.Mobile with software syngo MR XA51A and XQ gradient system includes new hardware compared to the predicate device, MAGNETOM Viato.Mobile with software syngo MR XA51A and XJ gradient system. A highlevel summary of the modified hardware is provided below:

    Hardware
    Modified Hardware

    • Gradient Coil
    • Gradient Power Amplifier
    AI/ML Overview

    This document is a 510(k) summary for the MAGNETOM Viato.Mobile system from Siemens Medical Solutions USA, Inc. The submission is for a modification to an already cleared device, primarily involving new hardware (Gradient Coil and Gradient Power Amplifier) and an XQ gradient system option. This is a claim of substantial equivalence to an existing predicate device, not a new device requiring a full de novo study. Therefore, the information provided focuses on demonstrating that the modified device performs as safely and effectively as the predicate, rather than presenting a detailed study proving the device meets specific acceptance criteria in a clinical context.

    Here's an analysis based on the provided text, addressing your questions where information is available:

    1. Table of Acceptance Criteria and Reported Device Performance

    The document does not present a table of specific acceptance criteria (e.g., sensitivity, specificity, accuracy targets) for diagnostic performance or a direct "reported device performance" in terms of clinical outcomes. Instead, it focuses on demonstrating that the modified hardware maintains the same safety and performance profile as the predicate device and reference device. The acceptance is based on compliance with standards and non-clinical testing.

    Performance Test / Acceptance CriteriaReported Device Performance
    Nonclinical Tests:
    Performance bench test"performs as intended"
    Verification and validation"performs as intended"
    Electrical safety and EMC (IEC 60601-1-2)"performs as intended"
    ISO 14971 (Risk Management)"ensured via a risk analysis"
    IEC 60601-1 series (Electrical/Mechanical Hazards)"minimizes electrical and mechanical hazards"
    IEC 60601-2-33 (MR equipment safety)Device conforms
    NEMA MS 4:2010 (Acoustic Noise)Device conforms

    2. Sample Size for the Test Set and Data Provenance

    Since this is a submission for a hardware modification and claims substantial equivalence based on non-clinical testing and comparison to a predicate, there is no "test set" in the traditional sense of a patient cohort or imaging dataset used to assess diagnostic performance. The testing involved new hardware itself.

    • Sample Size for Test Set: Not applicable in a clinical diagnostic performance sense. Non-clinical hardware tests were performed.
    • Data Provenance: Not applicable for diagnostic performance.

    3. Number of Experts and Qualifications for Ground Truth

    • Number of Experts: Not applicable. The ground truth for this submission concerns the performance and safety of the hardware modification, established through engineering tests and compliance with recognized standards. There were no experts establishing ground truth for diagnostic interpretations for this specific submission.

    4. Adjudication Method

    • Adjudication Method: Not applicable. There was no clinical ground truth requiring adjudication.

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

    • MRMC Study: No. The document explicitly states: "No clinical study and no additional clinical tests were conducted to support substantial equivalence for the subject device." This means there was no MRMC study to compare human readers with or without AI assistance, as the device itself is an MR scanner, not an AI-assisted diagnostic tool.

    6. Standalone Performance Study

    • Standalone Performance Study: No. This submission focuses on hardware safety and performance modifications of an MR scanner, not the standalone diagnostic performance of an AI algorithm.

    7. Type of Ground Truth Used

    The "ground truth" for this submission is established through:

    • Engineering test results and measurements: For performance bench tests, electrical safety, and electromagnetic compatibility.
    • Compliance with recognized international standards: Like IEC 60601 series, ISO 14971, and NEMA MS 4:2010, which define safety and performance requirements for medical electrical equipment and MR systems.
    • Comparison to the established safety and performance profile of the predicate and reference devices: The core argument is substantial equivalence, meaning the new hardware does not introduce new questions of safety or effectiveness compared to legally marketed devices.

    8. Sample Size for the Training Set

    • Sample Size for Training Set: Not applicable. This is not an AI-driven image analysis algorithm that requires a training set of images. It is a hardware modification to an MR scanner.

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

    • How Ground Truth for Training Set Was Established: Not applicable, as there is no training set for an AI algorithm in this submission.
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    K Number
    K232482
    Date Cleared
    2023-09-06

    (21 days)

    Product Code
    Regulation Number
    892.1000
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    MAGNETOM Viato.Mobile

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The MAGNETOM system is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional images, spectroscopic images and/or spectra, and that displays the internal structure and/or function of the head, body, or extremities. Other physical parameters derived from the images and/or spectra may also be produced. Depending on the region of interest, contrast agents may be used. These images and/or spectra and the physical parameters derived from the images and/or spectra when interpreted by a trained physician vield information that may assist in diagnosis.

    The MAGNETOM system may also be used for imaging during interventional procedures when performed with MR compatible devices such as in-room displays and MR Safe biopsy needles.

    Device Description

    MAGNETOM Viato.Mobile with software syngo MR XA51A includes minor modified hardware compared to the predicate device. MAGNETOM Sola Fit with software syngo MR XA51A. A high level summary of the modified hardware is provided below:

    Hardware
    Modified Hardware

    • Cover
      Other Modifications and / or Minor Changes
    • Adaptations for installation in a mobile trailer
    • MAGNETOM Viato.Mobile is a mobile MR system which enables the customers to relocate the MRI system to different locations and therefore provide imaging services where it is needed.
    AI/ML Overview

    The provided text describes the 510(k) summary for the MAGNETOM Viato.Mobile device, focusing on its substantial equivalence to a predicate device. However, it does not contain information about acceptance criteria and a study specifically proving the device meets those criteria for software-driven performance aspects, nor does it include information about AI/ML models.

    The document states: "No clinical study and no additional clinical tests were conducted to support substantial equivalence for the subject device." It primarily focuses on hardware modifications and compliance with general medical device standards.

    Therefore, many of the requested details cannot be extracted from the provided text. Below is a summary of what can be inferred from the document and a clear indication of what information is missing.


    Acceptance Criteria and Reported Device Performance

    The document does not explicitly state quantitative "acceptance criteria" and "reported device performance" in the context of an AI/ML model for diagnostic accuracy. Instead, the "performance" discussed relates to the device's adherence to general safety and operational standards as a Magnetic Resonance Diagnostic Device (MRDD).

    Table of Acceptance Criteria and Reported Device Performance (as inferred from the document regarding the device's overall functionality and safety):

    Acceptance Criteria CategorySpecific Criteria (Inferred from Standards)Reported Device Performance (Inferred from substantially equivalent claim)
    Magnetic Resonance Imaging FunctionalityProduction of transverse, sagittal, coronal, oblique images; spectroscopic images and/or spectra; display of internal structure/function of head, body, or extremities. Interpretation by trained physician assists in diagnosis.Performs as intended, equivalent to predicate device.
    Interventional ProceduresCompatibility with MR compatible devices (e.g., in-room displays, MR Safe biopsy needles) for imaging during interventional procedures.Performs as intended, equivalent to predicate device.
    Electrical SafetyCompliance with IEC 60601-1 (general requirements for basic safety and essential performance).Compliant with IEC 60601-1.
    Electromagnetic Compatibility (EMC)Compliance with IEC 60601-1-2 (electromagnetic disturbances requirements and tests).Compliant with IEC 60601-1-2.
    MR-Specific SafetyCompliance with IEC 60601-2-33 (particular requirements for basic safety and essential performance of magnetic resonance equipment).Compliant with IEC 60601-2-33.
    Software Life Cycle ProcessesCompliance with IEC 62304 (medical device software - software life cycle processes).Compliant with IEC 62304.
    Risk ManagementCompliance with ISO 14971 (application of risk management to medical devices).Compliant with ISO 14971.
    Usability EngineeringCompliance with IEC 62366-1 (application of usability engineering to medical devices).Compliant with IEC 62366-1.
    DICOM CompatibilityCompliance with NEMA DICOM standards (Digital Imaging and Communications in Medicine).Compliant with NEMA DICOM.
    Image Quality ParametersCompliance with NEMA standards for SNR, geometric distortion, image uniformity, slice thickness, acoustic noise, SAR.Compliant with relevant NEMA standards for image quality.
    Operational EnvironmentEquivalent to predicate device.Equivalent to predicate device.
    Programming LanguageEquivalent to predicate device.Equivalent to predicate device.
    Operating SystemEquivalent to predicate device.Equivalent to predicate device.

    Regarding the study that proves the device meets acceptance criteria:

    The document explicitly states: "No clinical study and no additional clinical tests were conducted to support substantial equivalence for the subject device."

    The assessment for substantial equivalence was based on:

    1. Bench testing of modified hardware: Performed according to "Guidance for Submission of Premarket Notifications for Magnetic Resonance Diagnostic Devices."
    2. Verification and validation (V&V) of modified hardware: Performed according to "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices."
    3. Electrical safety and electromagnetic compatibility (EMC) testing of the complete system: Performed per IEC 60601-1-2.

    The conclusion is that these non-clinical data demonstrate the device performs as intended and is substantially equivalent to the predicate device, the MAGNETOM Sola Fit (K221733).


    Missing Information (Not found in the provided text):

    1. Sample size used for the test set and the data provenance: Not applicable, as no performance study for diagnostic accuracy was conducted for an AI component. The tests were for hardware and system compliance.
    2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable, as there was no test set requiring expert ground truth for diagnostic accuracy.
    3. Adjudication method for the test set: Not applicable.
    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: Not applicable. The device is a Magnetic Resonance Diagnostic Device, not an AI-assisted diagnostic tool.
    5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
    6. The type of ground truth used (expert concensus, pathology, outcomes data, etc): Not applicable.
    7. The sample size for the training set: Not applicable.
    8. How the ground truth for the training set was established: Not applicable.

    This device is primarily an MR hardware system with software for operation and image generation, not a device incorporating AI/ML for diagnostic interpretation. The substantial equivalence relies on proving the modified hardware and mobile integration retain the fundamental safety and performance characteristics of the predicate device, as demonstrated through engineering tests and adherence to recognized standards.

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