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Your MAGNETOM system is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional 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 the physical parameters derived from the images and/or spectra, when interpreted by a trained physician, yield information that may assist in diagnosis.

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

Software syngo MR E11E with Ischemic Heart Disease (HD) Workflow, when used with a gadolinium-based contrast agent (GBCA) approved for cardiac MRI (CMRI) is indicated for the acquisition and display of images of myocardial perfusion (stress, rest) and late gadolinium enhancement (LGE) during post-contrast CMRI examination in patients with known or suspected coronary artery disease (CAD).

MAGNETOM Aera and MAGNETOM Skyra with Software syngo MR E11E with IHD Workflow are the subject devices. The Software syngo MR E11E with IHD Workflow, when used with a gadolinium-based contrast agent (GBCA) approved for CMRI, extends the capability of the cleared Cardiac Dot Engine (K121434) for post-contrast CMRI exams for patients with known or suspected coronary artery disease (CAD). Software syngo MR E11E with IHD Workflow is available for MAGNETOM Aera and MAGNETOM Skyra excluding the 24-channel configuration.

A. The cleared Cardiac Dot Engine (syngo MR D13A, K121434) helps acquisition and display of cardiac morphology and function (noncontrast CMRI).
A comprehensive post-contrast CMRI exam includes stress/rest perfusion and late gadolinium enhanced (LGE) imaging. To accomplish post-contrast CMRI imaging, basic morphologic / functional imaging (noncontrast CMRI) is required. Therefore, the cleared Cardiac Dot Engine (syngo MR D13A, K121434) is a pre-requisite to the subject devices.

B. The Cardiac Dot Engine together with the IHD Workflow and a GBCA approved for post-contrast CMRI provides for a complete (pre- and post-contrast) examination.

The primary predicate devices are modified to include a new Dot Workflow named "Ischemic Heart Disease" (IHD) Workflow for a post-contrast CMRI exam using pulse sequences already cleared in the USA (syngo MR D13A, K121434). A new Dot Workflow "Ischemic Heart Disease" is added in Cardiac Dot Engine dropdown list, under the region "heart". This Dot Workflow includes the following: six new post-contrast CMRI measurement protocols and one workflow step:

New Measurement protocols:

1. DynamicTest (test protocol for perfusion imaging without contrast agent)
2. DynamicStress (protocol for perfusion imaging under stress conditions)
3. DynamicRest (protocol for perfusion imaging under rest conditions)
4. DE overview (protocol for delayed enhancement (DE) or LGE with low spatial resolution as an overview)
5. DE_seg_high-res_LAX (protocol for DE or LGE with high spatial resolution in long axis view)
6. DE seg high-res SAX (protocol for DE or LGE with high spatial resolution in short axis view)

New workflow step:

1. Inject contrast agent. This step prompts the user to start the contrast agent injection for post-contrast CMRI exams.

This document describes the regulatory approval for the Siemens MAGNETOM Aera and MAGNETOM Skyra with Software syngo MR E11E with Ischemic Heart Disease (IHD) Workflow. The IHD Workflow is an extension to the cleared Cardiac Dot Engine, intended for post-contrast Cardiac MRI (CMRI) exams for patients with known or suspected Coronary Artery Disease (CAD).

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria or quantitative performance metrics for the IHD Workflow. Instead, it refers to the efficacy results of two clinical studies (GadaCAD1 and GadaCAD2) to support the device's performance. The "acceptance criteria" can therefore be inferred as the successful demonstration of the device's ability to acquire and display myocardial perfusion and late gadolinium enhancement (LGE) images that adequately detect CAD when interpreted by qualified readers.

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

• Sample Size for Test Set: A total of 764 subjects were evaluated across two studies: 376 subjects in GadaCAD1 and 388 subjects in GadaCAD2. These subjects represent the test set for evaluating the post-gadobutrol CMRI capabilities.
• Data Provenance: The GadaCAD studies were prospectively controlled, multi-national, single-arm clinical studies. The document states that they were performed by Bayer HealthCare AG.

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

• Number of Experts: The document states that the CMRI images were "interpreted by qualified independent readers". While it doesn't specify an exact number, the use of "readers" (plural) across multi-center, multi-national studies implies multiple experts were involved in the interpretation process.
• Qualifications of Experts: The readers were described as "radiologists and cardiologists experienced in CMRI".

4. Adjudication Method for the Test Set

The document does not explicitly describe an adjudication method (e.g., 2+1, 3+1 consensus) for establishing the ground truth from the expert interpretations in the GadaCAD studies. It simply states that the images were "interpreted by qualified independent readers." The primary endpoint of the GadaCAD studies, as mentioned in the GADAVIST™ package insert, was likely the diagnostic accuracy of CMRI for CAD detection, which would have implicitly relied on these interpretations, but the specific consensus mechanism is not detailed.

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

• The document does not describe a multi-reader multi-case (MRMC) comparative effectiveness study designed to assess the improvement of human readers with AI vs. without AI assistance.
• The IHD Workflow is presented as a set of modified measurement protocols and a workflow step for image acquisition and display, extending the capabilities of the existing Cardiac Dot Engine. The clinical studies evaluated the efficacy of the imaging technique itself (using the IHD Workflow components) for CAD detection, not the comparative performance of human readers with and without AI assistance for interpretation.

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

• The document does not present a standalone performance study for an algorithm without human-in-the-loop performance.
• The IHD Workflow focuses on image acquisition and display protocols. The interpretation of these images for diagnosis still relies on "trained physicians." The clinical studies validate the acquisition and display capabilities to produce images sufficient for expert interpretation.

7. Type of Ground Truth Used

The ground truth used in the GadaCAD studies was expert consensus / clinical interpretation by qualified independent readers (radiologists and cardiologists experienced in CMRI) for the detection of CAD. The document explicitly states: "The post-gadobutrol CMRI specific acquisition protocols supported adequate detection of CAD in two multi-center, multinational clinical studies."

8. Sample Size for the Training Set

The document does not provide information on the sample size used for the training set. The IHD Workflow's development and validation are largely described in terms of non-clinical software verification and validation, and clinical validation using the GadaCAD studies. The GadaCAD studies served as the validation set for the device's performance, not a training set for an AI/algorithm component requiring labeled data for learning. The IHD Workflow primarily introduces new measurement protocols and a workflow step, not necessarily a machine learning algorithm that requires a distinct training set in the conventional sense.

9. How Ground Truth for the Training Set Was Established

Since no training set is explicitly mentioned or relevant for the described IHD Workflow (which consists of acquisition protocols and workflow steps, not an AI model requiring a training phase), the method for establishing ground truth for a training set is not applicable/not provided in this document.

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The MAGNETOM Terra system is indicated for use as a magnetic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional images and that displays the internal structure and/or function of the head or extremities. Other physical parameters derived from the images may also be produced. These images and the physical parameters derived from the interpreted by a trained physician vield information that may assist in diagnosis.

The device is intended for patients > 30 kg/66 lbs.

MAGNETOM Terra is a 60 cm bore Magnetic Resonance Imaging system with an actively shielded 7T superconducting magnet. With the interplay of the magnetic field, gradients, radio frequency (RF) transmitter and receiver coil and software this magnetic resonance scanner produces transverse, sagittal, coronal and oblique cross sectional images that represent the spatial distribution of protons with spin. The MAGNETOM Terra uses two local coils 1Tx32Rx Head Coil 7T Clinic and 1Tx28Rx Knee Coil 7T Clinic for head and knee imaging.

The provided text describes the Siemens MAGNETOM Terra, a 7T Magnetic Resonance Imaging (MRI) system. However, it focuses on demonstrating substantial equivalence to a predicate device (MAGNETOM Trio A Tim System with syngo MR B19A) rather than establishing novel safety and effectiveness through specific acceptance criteria and a dedicated study demonstrating the device meets those criteria for a new clinical indication or outcome.

The text outlines various non-clinical tests and a clinical study primarily to ensure the device's fundamental safety and performance within the established framework for MRI devices, especially given the increased magnetic field strength (7T). It does not present a study designed to prove the device meets specific acceptance criteria related to a new clinical performance claim or diagnostic accuracy.

Therefore, many of the requested sections (Table of acceptance criteria, device performance, sample size for test set, data provenance, number of experts for ground truth, adjudication method, MRMC study, standalone performance, type of ground truth used for test set, training set details) are not applicable or extractable from this document as the submission does not detail a study aimed at proving a specific clinical performance criterion for this device as a new clinical claim.

Below is a summary of the information that can be extracted or inferred based on the document's content:

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

No explicit "acceptance criteria" table for a specific clinical performance claim is provided. The submission focuses on demonstrating compliance with recognized standards and substantial equivalence to a predicate device. Performance is generally assessed via image quality and safety parameters.

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

• Sample size for nerve stimulation threshold study: 35 individuals.
• Data provenance: Not explicitly stated whether retrospective or prospective, or country of origin. It is a "clinical study" performed to set PNS thresholds.
• Sample images for image quality assessment: Not specified beyond "sample clinical images were acquired for all available clinical pulse sequences and local coils."

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)

• For nerve stimulation threshold study: Not applicable, as this study determines physiological thresholds, not ground truth for diagnostic imaging interpretation.
• For image quality assessment: "reports from two U.S. board-certified radiologists have been provided after the radiologists reviewed image pairs comparing the subject and the predicate device." Their specific experience level is not mentioned beyond "board-certified." This implies a qualitative assessment, not a formal ground truth establishment for a diagnostic study.

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

• For image quality review: Not explicitly detailed beyond "two U.S. board-certified radiologists... reviewed image pairs comparing the subject and the predicate device [and their] comments on any observed artifacts and concerns have also been included." This suggests a qualitative comparison rather than a formal adjudication process for diagnostic accuracy.

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 is mentioned, nor is there any AI component described in the device. This device is an MRI scanner, not an AI-powered diagnostic tool.

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

• Not applicable, as this is an MRI scanner, not an algorithm being evaluated for standalone diagnostic performance.

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

• For nerve stimulation threshold study: The "ground truth" is the empirically observed nerve stimulation thresholds in the 35 individuals, which defines the physiological limits for setting the PNS threshold level.
• For image quality assessment: The "ground truth" or reference is implied to be the qualitative assessment and comparison by board-certified radiologists against the predicate device, focusing on image characteristics and artifacts. No objective ground truth (e.g., pathology, clinical outcomes) is stated as being used to assess diagnostic accuracy.

8. The sample size for the training set

• Not applicable/provided. This submission does not describe a machine learning algorithm that requires a training set. The software development is based on an existing software line and adapted for 7T parameters. The SAR control software enhancements are based on simulations with human models.

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

• Not applicable, as no training set for a machine learning algorithm is described. The SAR control software relies on computational modeling and simulation data using established human models (Virtual Population, MIDA Model) to estimate local SAR.

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Your 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 that displays the internal structure and/or function of the head, body, or extremittes. 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 mages 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.

Your 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.

MAGNETOM Vida with software syngo MR XA10A is similar to the previous cleared predicate device MAGNETOM Skyra with syngo MR E11C (K153343) but includes new and modified hardware and software compared to MAGNETOM Skyra.

Here's a breakdown of the acceptance criteria and study information for the MAGNETOM Vida device, based on the provided text:

Preamble: It's important to note that this document is a 510(k) summary for a premarket notification for a Class II medical device (Magnetic Resonance Diagnostic Device). The primary goal of a 510(k) submission is to demonstrate "substantial equivalence" to a legally marketed predicate device, not necessarily to prove absolute efficacy in a clinical setting in the same way a PMA (Premarket Approval) might require. Therefore, the "acceptance criteria" and "device performance" are primarily focused on meeting established standards and showing that changes do not negatively impact safety or effectiveness compared to the predicate.

Acceptance Criteria and Reported Device Performance

The general acceptance criteria are that the device performs as intended and is "substantially equivalent" to the predicate device, especially regarding safety and effectiveness. The specific performance reported largely revolves around conformance to recognized standards and successful completion of verification and validation.

Table of Acceptance Criteria and Reported Device Performance:

Study Information

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

   • Clinical Study (PNS Threshold): 33 individuals. The document does not specify the country of origin or whether it was retrospective or prospective, but clinical studies for such thresholds are typically prospective.
   • Nonclinical Tests (Image Quality, Software V&V, Performance Tests): The document does not specify a numerical sample size but mentions "sample clinical images were taken" for new coils and software features. It does not provide provenance (country, retrospective/prospective) for these samples specifically, but they would likely be internal studies.

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

   • The document does not explicitly state the number or qualifications of experts used to establish ground truth for the image quality assessments, software V&V, or performance tests. However, it indicates that the interpretation of images and spectra is done "by a trained physician." For image quality assessments, it's implied that Siemens' internal experts or qualified personnel performed these.

3. Adjudication Method for the Test Set:

   • The document does not specify an adjudication method like 2+1 or 3+1 for any of the tests described.

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

   • No MRMC comparative effectiveness study is mentioned for the entire device. The submission focuses on demonstrating substantial equivalence through compliance with standards, verification, and validation, rather than a direct comparison of reader performance with and without the new AI features (if any specific AI features are implied, they are integrated within the "new software" and not evaluated separately as AI-assisted reading).
   • There is no mention of an effect size for human readers with vs. without AI assistance.

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

   • No standalone performance study of an algorithm is explicitly described. The device is an MRI system, which always involves a human operator and physician interpretation. The "new software" features are part of the overall system performance, not presented as a discrete AI algorithm for standalone evaluation.

6. Type of Ground Truth Used:

   • PNS Threshold Study: The ground truth would be the observed physiological response (nerve stimulation) in the 33 individuals, used to set the safety threshold.
   • Image Quality Assessments: The ground truth would likely be internal Siemens expert assessment of expected image characteristics, clarity, and diagnostic interpretability against established quality metrics or comparisons to images from the predicate device.
   • Software V&V/Performance Tests: Ground truth would be derived from specifications, expected functional outputs, and adherence to regulatory standards.
   • General Diagnosis: The "Indications for Use" state that images and spectra, "when interpreted by a trained physician yield information that may assist in diagnosis." This implies physician interpretation is the ultimate ground truth for diagnostic purposes in clinical use, but not for the technical performance studies described in the 510(k).

7. Sample Size for the Training Set:

   • The document does not provide information on a specific training set size. This type of 510(k) submission generally does not detail the internal development and training data for software components, especially when the changes are primarily updates to an existing system, rather than a de novo AI algorithm approval.

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

   • Since no specific training set or study for algorithm training is described, the method for establishing its ground truth is not provided.

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The Siemens MR-PET system combines magnetic resonance diagnostic devices (MRDD) and Positron Emission Tomography (PET) scanners that provide registration and fusion of high resolution physiologic and anatomic information. acquired simultaneously and isocentrically. The combined system maintains independent functionality of the MR and PET devices, allowing for single modality MR and / or PET imaging.

These systems are intended to be utilized by appropriately trained health care professionals to aid in the detection, localization, and diagnosis of diseases and disorders.

The MR is intended to produce transverse, sagittal, coronal and oblique crossectional MR images, spectroscopic inages and/or spectra, and displays the internal structure and/or function of the human body. Other physical parameters derived from the images and or spectra may also be produced. Depending on the region of interest, approved contrast agents may be used, as described in their labeling. This system may also be used for imaging during interventional procedures when performed with MR compatible devices, such as MR safe biopsy needles.

The PET images and measures the distribution of PET radiopharmaceuticals in humans to aid the physician in determining various metabolic (molecular) and physiologic functions within the human body for evaluation of diseases and disorders such as, but not limited to, cardiovascular disease, neurological disorders and cancer.

The combined system utilizes the MR for radiation-free attenuation correction maps for PET studies. The system provides inherent anatomical reference for the fised PET and MR images due to precisely aligned MR and PET image coordinate systems.

The subject device, syngo MR E11P system software, is being introduced for the Biograph mMR system.

The syngo MR E11P SW includes new sequences, new features and minor modifications of already existing features. A high level summary of the new sequences and features is included below.

Migrated sequences and features from the previously cleared secondary predicate devices MAGNETOM Verio with syngo MR D13A and Siemens E-line Software with MAGNETOM Skyra with syngo MR E11C (K153343) are not described separately as these are commercially available and no changes are introduced for this system.

Improvement in Attenuation Correction
Atlas-based bones in u-map generation
The bone attenuation map is computed based on a reqular 4-compartment (air, lung, fat, water) segmentation from a Dixon sequence. As improvement, the bone information is added to these u-maps with a model-based bone segmentation algorithm using continuous linear attenuation coefficients (LACs) for bone to represent the variation in cortical bone density in different anatomical areas.

The model consists of the most relevant bones in the body torso in terms of overall attenuation. It consists of the skull, spine, pelvis and femur bone as individual components.

MR based FoV extension for attenuation correction - (HUGE)
In this SW version syngo MR E11P the attenuation map can be improved by using an optional MR-based FoV extension technique. This technique requires an additional MR measurement optimized for distortion reduced acquisition of the patient's arms resting along the body at the edge of the FoV.

New and Modified Features
Multimodal (Elastic) Motion Correction (BodyCOMPASS)
Elastic motion correction is introduced to reduce the effect of blur induced by respiratory motion during a PET acquisition. As a basic principle, periodic motion information is collected by means of the MR as a 4D image series and used for PET to

• . bin the PET counts into separate respiratory states
• provide a mapping for each spatial position and each respiratory state to a . reference state, which can be used in the PET reconstruction

Hence, the resulting PET image combines the advantages of a gated PET image with reduced motion blur while preserving the signal-to-noise ratio of static non-gated reconstruction.

Improvement in DIXON fat water separation
In this SW version syngo MR E11P the DIXON reconstruction technique (fat/water separation) is improved. The improved algorithm is based on global optimization and thus minimizes the probability of local fat/water swaps where part of water image is wrongly assigned to fat image and/or vice versa.

Dot Cockpit (DotGO), including PET Workflow
The previously cleared DotGO with the Dot Cockpit and the MR only Dot Engines is now available on the Biograph mMR with syngo MR E11P. The configuration of PET workflows is now integrated into the Dot Cockpit for higher productivity.

This modification increases the robustness and usability for the clinical workflow with the new PET Planning Group. PET Planning Step and special reduced MR Parameter cards while still offering the full parameter access with detail views, PET and AC specific steps with their parameter cards.

Improved MR PET Workflow
With the software syngo MR E11P a set of protocols are included in order to run a clinical whole body workflow with 5 beds, AC, T1-, T2-, DWI-contrast, adjustments and SAR pauses in 45 minutes.

In this workflow the AC protocol is acquired in high resolution (1.3 mm * 1.3mm in plane) using CAIPIRINHA acceleration. Alternatively, an AC protocol in conventional resolution (2.6 mm * 2.6 mm in plane) using CAIPIRINHA acceleration is available in order to reduce the acquisition time for AC measurement in case T1-contrast is not requested from AC scan.

Other Software Improvements
NEMA NU 2:2012
As it is possible that routine NEMA testing may be required to retain ACR accreditation, Siemens has developed an optional software package which enables a Biograph mMR system user to quantify image quality for certain performances according to the most recent available NEMA standards.

Improvements in Retro Recon Task Card
In the RetroRecon Task Card of the Biograph mMR with syngo MR E11P, an additional identifier in the list of the parameter Attenuation Correction indicates gated u-Maps.

Furthermore a Tooltip for the Attenuation Correction parameter explains the identifier.

For respiratory gating a new Respiratory Curve Display shows the recorded cushion signal as well as the specified gates for some gating types.

Third Party Interface for AC
An Interface functionality is added to the synqo MR E11P software to import attenuation maps of third party components for hardware attenuation correction.

Other Modifications
Front Cover Panel Refresh for Biograph mMR
The Biograph mMR with syngo MR E11P will receive new system covers. The graphic design of the cover has been changed to give the systems an updated and more modern look to highlight the introduction of a new software version.

MaRS - technology for Biograph mMR
The modified control system of the Biograph mMR integrates the functions of the AMC (Advanced Measurement Control) and MRIR (MR Image Reconstructor) into one computer called MaRS (Measurement and Reconstruction System).

The MaRS system performs sequence control and image reconstruction without additional MRIR. The introduction of the MaRS was part of the secondary predicate device MAGNETOM Verio with syngo MR D13A (K121434). This is now updated to new computer hardware with this submission.

Physiological Monitoring Unit (PMU)
The Physiological Measurement Unit (PMU) was modified to improve the accuracy of triggers on the respiration signal. The PMU provides ECG, respiration and peripheral pulse as well as external trigger input to control of the MR imaging sequences for synchronization.

Syngo MR Software Features
Other features were included unchanged from the secondary predicate devices (K121434 and K153343). These features expand the Biograph mMR's MR scanning capabilities and update the feature set to be more similar to currently released Siemens MR software.

Acceptance Criteria and Device Performance for Biograph mMR with syngo MR E11P system software (K163234)

Based on the provided FDA 510(k) summary, the acceptance criteria and supporting studies focus on demonstrating that the new syngo MR E11P software for the Biograph mMR system maintains the safety and effectiveness of the predicate device while introducing improvements and new features. The document highlights the substantial equivalence argument, rather than providing explicit numeric acceptance criteria and performance tables for specific clinical tasks. However, we can infer the performance goals and the studies conducted to support them.

1. Table of Acceptance Criteria and Reported Device Performance

As explicit numeric acceptance criteria and a detailed performance table are not provided in the 510(k) summary, the table below represents the implied acceptance criteria (based on the device's intended use and the nature of the modifications) and the general results reported for demonstrating substantial equivalence.

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

• Test Set Sample Size: The document does not explicitly state the numerical sample size (e.g., number of patients, cases) for the clinical images used in the comparison studies. It mentions "Sample clinical images were taken for particular new and modified sequences" and "Additionally clinical images were provided to support the substantial equivalence for the new software features of the subject device." The quantitative comparison studies also imply a dataset, but the size is not specified.
• Data Provenance: The provenance of the data (country of origin, retrospective/prospective) is not explicitly detailed. The manufacturer is Siemens Healthcare GmbH based in Erlangen, Germany, and Siemens Medical Solutions USA, Inc. is the establishment in the USA. It is common for such validation studies to involve data from internal research or collaborating institutions, but the document does not specify. The nature of "clinical images" and "quantitative comparison studies" suggests real patient data, likely retrospective or a mix, but this is not confirmed.

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 summary. While clinical images and quantitative comparisons were performed, the method of establishing ground truth and the involvement and qualifications of experts for defining "ground truth" are not described. It's likely that in the context of imaging system performance, "ground truth" for image quality and diagnostic accuracy would implicitly rely on expert assessment, but the details are omitted.

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

This information is not provided in the summary. Without details on expert involvement in ground truth establishment, no adjudication method can be inferred.

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:

A multi-reader multi-case (MRMC) comparative effectiveness study focusing on the improvement of human readers with AI assistance was not explicitly described in this 510(k) summary. The document describes improvements to the imaging system's software components (e.g., attenuation correction, motion correction, fat/water separation) that likely improve image quality and potentially diagnostic accuracy, but it doesn't quantify reader performance improvement with "AI assistance" in the sense of a decision support system. The listed studies are more focused on the technical performance and quantitative accuracy of the imaging system's outputs.

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

Yes, a form of standalone performance assessment was conducted for many of the technical improvements. The "Nonclinical Tests" section details:

• "Image quality assessments of all new/modified sequences and algorithms, were completed."
• The "Clinical Tests" section describes "Quantitative comparison study of attenuation maps of CT-based AC and MR-based AC method..." and "Quantitative comparison study of SUV estimation for MR-based AC methods..." These are direct technical evaluations of the algorithm's output (image quality, quantitative accuracy) independent of a human reader's diagnostic performance.

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

The type of ground truth used varies based on the specific study:

• For attenuation correction and SUV estimation studies: The ground truth appears to be established by comparison to established methods, specifically "reference CT AC." This implies that CT attenuation maps are considered the gold standard for comparison in these contexts.
• For general image quality and new feature performance: The "ground truth" is likely based on visual assessment by experts (implied, though not stated) combined with quantitative metrics relevant to image quality (e.g., minimizing motion blur, reducing fat/water swaps) derived from predefined technical standards or expected outcomes.

8. The sample size for the training set:

This information is not provided in the summary. The document describes modifications and improvements to existing software components and introduces new sequences and features. While these often involve internal development and testing cycles that might use various datasets, specific training set sizes for machine learning components (if any, beyond the "atlas-based bones" model) are not detailed.

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

This information is not provided in the summary. Given the nature of the improvements (e.g., atlas-based bone models, global optimization for Dixon), it's likely that internal reference datasets and expert knowledge were used, but the specifics of their ground truth establishment are not disclosed. For the "atlas-based bones in u-map generation," the "model consists of the most relevant bones in the body torso" which implies a pre-defined anatomical model or a training process that derived this model from a dataset with defined bone attenuation properties. However, details are absent.

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The MAGNETOM systems described above are indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional 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 systems described above may also be used for imaging during interventional procedures when performed with MR compatible devices such as in-room display and MR-Safe biopsy needles.

The subject device, software syngo MR E11A for MAGNETOM Aera and MAGNETOM Skyra offers two new applications, LiverLab (an application of non-invasive liver evaluation) and MyoMaps (an application designed to provide a means to generate pixel maps for myocardial MR relaxation times). In addition, software syngo MR E11A makes the Dot Cockpit available for the user to modify and create Siemens Dot Engine workflows in a very intuitive way which supplements some of the support of an application specialist. The software syngo MR E11A also includes new and modified sequences as well as minor modifications of already existing features. In additional coils are offered and some hardware components have been modified.

Siemens Medical Solutions, USA Inc., intends to market MAGNETOM Aera and MAGNETOM Skyra with new software, syngo MR E11A. While syngo MR E11A offers additional capabilities with respect to the predicate device, the MAGNETOM Aera and MAGNETOM Skyra have the same technological characteristics as the predicate device (K121434; Cleared November, 5, 2012).

Furthermore, Siemens Medical Solutions, USA Inc., intends to market a new configuration of the MAGNETOM Skyra with 24 receive channels with software syngo MR E11A.

The MAGNETOM Aera and MAGNETOM Skyra will be offered ex-factory (new production) as well as in-field upgrades for the currently installed MAGNETOM Aera and MAGNETOM Skyra systems. The new MAGNETOM Skyra configuration with 24 receive channels will be offered as an ex-factory option (new production).

This FDA 510(k) summary describes a new software version (syngo MR E11A) for existing Siemens MAGNETOM Aera and MAGNETOM Skyra MRI systems. The primary focus of the document is to demonstrate substantial equivalence to previous versions and other cleared devices, rather than establishing new acceptance criteria for a novel device.

Therefore, the requested information regarding acceptance criteria, device performance, and specific study details (like sample size for test sets, expert qualifications, and adjudication methods) is largely not present for the overall system or its new features as this is an equivalence submission. The closest equivalent to "acceptance criteria" are the results of performance tests demonstrating the device performs as intended and is "substantially equivalent."

However, I can extract the available information regarding testing for the new features:

1. Table of Acceptance Criteria and Reported Device Performance

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

• MyoMaps Comparison Study:
  • Sample Size: 100 persons.
  • Data Provenance: Not specified, but involved "volunteers."
• LiverLab Validation:
  • Sample Size: Not specified beyond "volunteer" and "phantom scans."
  • Data Provenance: Not specified, beyond "volunteer" and "phantom scans" and "synthetic raw data."
• New Coils, Sequences, Algorithms, Acoustic Noise: Sample sizes not specified; phantom testing mentioned.
• Clinical tests (overall device): No clinical tests were conducted to support the substantial equivalence argument beyond the provision of clinical images to support new coils and software features.

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 document states that the images and spectra, "when interpreted by a trained physician, yield information that may assist in diagnosis." However, for validation studies, the specifics of expert involvement or ground truth establishment are not detailed.

4. Adjudication method for the test set

• This information is not provided in the document.

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

• A MRMC study comparing human readers with and without AI assistance was not mentioned or performed as part of this submission. The "MyoMaps" feature was compared to "Thalassaemia Tools," which is a comparison of two tools, not a human-AI comparison.

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

• The document describes "LiverLab" validation using "volunteer as well as phantom scans, and synthetic raw data" and "MyoMaps" being "tested on volunteers." This suggests standalone performance evaluation for these specific features. However, detailed metrics of standalone performance are not provided, only that the "results... demonstrate that the device performs as intended."

7. The type of ground truth used

• MyoMaps: The comparison was against "Thalassaemia Tools." For the "volunteers" testing, the method of establishing ground truth for myocardial MR relaxation times beyond direct measurement is not specified.
• LiverLab: Validation involved "volunteer as well as phantom scans, and synthetic raw data." The ground truth for phantom scans would be known parameters. For volunteer scans, the ground truth source for liver evaluation is not explicitly stated (e.g., biopsy results, clinical diagnosis).
• For other features (coils, sequences), the ground truth generally relies on physical measurements and expected image properties.

8. The sample size for the training set

• This information is not provided in the document. The submission focuses on verification and validation of implemented features rather than detailing the development or training of algorithms.

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

• This information is not provided in the document. Given that details on a training set are absent, the method for establishing its ground truth is also not mentioned.

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The iMRI 1.5T A and 3T S are 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 iMRI 1.5T A and 3T S systems may also be used for imaging during intra-operative and interventional procedures when performed with MR safe devices or MR conditional devices approved for use with the MR scanner.

The iMRI 1.5T A and 3T S MRI systems may also be used for imaging in a multi-room suite.

The IMRIS Intraoperative MRI systems (iMRI 1.5T A and iMRI 3T S) are a traditional MRI unit that has been suspended on an overhead rail system, and is designed to operate inside an RF shielded room to facilitate intra-operative and multi-room use. The magnet is normally situated in a diagnostic room until imaging is requested. For Diagnostic room purposes, the system retains the standard diagnostic features of an MRI system. The diagnostic room is separated from the intra-operative suite by sliding doors that are part of the facility structure.

The iMRI system (1.5T A/3T S) is a tool for radiologists and surgeons, used to acquire images for diagnostic, intra-operative or interventional procedures. For OR purposes, high-resolution images can be obtained immediately prior to surgical incision, intraoperative and after wound closure. The iMRI 1.5T A is based on the IMRIS Neuro II-SE predicate cleared under 510(k) K071099 and the Siemens MAGNETOM Aera/Skyra MRI system cleared under 510(k) K101347. The iMRI 3T S is based on the IMRIS Neuro III-SV cleared under 510(k) K083137 and the Siemens MAGNETOM Aera/Skyra MRI system cleared under 510(k) K101347. The major components of the iMRI systems are: the Siemens MAGNETOM MRI system with minor modifications; IMRIS Magnet Mover System, OR Table, RF coils and 3-pin head fixation device.

The provided text is a 510(k) Premarket Notification for the IMRIS iMRI 1.5T A and 3T S systems, which are Magnetic Resonance Diagnostic Devices (MRDD). This document focuses on demonstrating substantial equivalence to predicate devices and adherence to relevant safety and performance standards. It does not describe a study involving specific acceptance criteria for diagnostic performance outcomes (like sensitivity, specificity, accuracy) using a clinical dataset and expert review, as would be typical for an AI-powered diagnostic device.

Instead, the "study" described is a verification and validation process primarily focused on demonstrating safety, effectiveness, and substantial equivalence to existing MRI systems.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not describe a "test set" in the context of clinical image data for diagnostic performance evaluation, nor does it mention data provenance (country of origin, retrospective/prospective). The "Sample clinical images" mentioned under "Design Verification and Validation Test (Bench Testing)" are likely for qualitative visual assessment and system validation, not for quantitative diagnostic performance metrics.

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

Not applicable. The filing does not detail a study involving expert-established ground truth for a test set of patient cases. The evaluation is focused on engineering and system performance standards, and comparison to predicate devices, rather than the diagnostic interpretive accuracy of the images by human readers.

4. Adjudication Method for the Test Set

Not applicable, as there is no specific test set requiring expert adjudication for establishing ground truth on diagnostic findings.

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

Not applicable. This 510(k) pertains to an MRI system itself, not an AI-powered diagnostic algorithm designed to assist human readers. Therefore, an MRMC study comparing human reader performance with and without AI assistance was not conducted or reported.

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

Not applicable. This device is a diagnostic imaging system, not an algorithm.

7. The Type of Ground Truth Used

For the safety and performance evaluations, the "ground truth" used is adherence to established engineering and medical device standards (IEC 60601 series, IEC 62304), and comparison against the technical specifications and performance characteristics of predicate and reference MRI devices for substantial equivalence. "Sample clinical images" were part of the V&V, implying visual assessment against expected image quality, but not a formally established clinical ground truth from pathology or outcomes.

8. The Sample Size for the Training Set

Not applicable. This is not an AI algorithm requiring a training set.

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

Not applicable.

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syngo.via is a software solution intended to be used for viewing, manipulation, communication, and storage of medical images. It can be used as a stand-alone device or together with a variety of cleared and unmodified syngo based software options. syngo.via supports interpretation and evaluation of examinations within healthcare institutions, for example, in Radiology, Nuclear Medicine and Cardiology environments. The system is not intended for the displaying of digital mammography images for diagnosis in the U.S.

syngo.via is a software solution intended to be used for viewing, manipulation, communication, and storage of medical images. It can be used as a stand-alone device or together with a variety of cleared and unmodified syngo based software options. syngo.via supports interpretation and evaluation of examinations within healthcare institutions, for example, in Radiology, Nuclear Medicine and Cardiology environments. The system is not intended for the displaying of digital mammography images for diagnosis in the U.S. The system is a software only medical device. It defines minimum requirements to the hardware it runs on. The hardware itself is not seen as a medical device and not in the scope of this 510(k) submission. It supports the physician in diagnosis and treatment planning. syngo.via also supports storage of Structured DICOM Reports. In a comprehensive imaging suite syngo.via integrates Radiology Information Systems (RIS) to enable customer specific workflows. The predicate device, syngo.via allows for the use of a variety of advanced applications (clinical applications) These applications are medical devices on their own rights and filed separately. They are not part of this 510(k) submission and not part of the syngo.via medical device. syngo.via has a universal component called generic reader application which is part of this medical device and it allows no newly introduced imaging and post processing algorithms compared to the above mentioned predicate devices. syngo.via is based on Windows. Due to special customer requirements and the clinical focus syngo.via can be configured in the same way as the predicate device with different combinations of syngo- or Windows based software options and clinical applications which are intended to assist the physician in diagnosis and/or treatment planning. This includes commercially available post-processing software packages.

Here's an analysis of the provided 510(k) summary regarding acceptance criteria and supporting studies:

This 510(k) pertains to "syngo.via," a PACS system. Based on the document, this 510(k) is for enhanced functionalities of syngo.via, making it an update or extension of a previously cleared device (K123375). The key here is that it's not a new AI algorithm designed for a
specific diagnostic task with associated performance metrics. Instead, it seems to be primarily a software platform update that integrates functionalities already present in other cleared Siemens products.

Therefore, the typical structure for reporting AI/CADe/CADx device performance (sensitivity, specificity, AUROC, etc.) involving a test set, ground truth, and expert readers is not applicable in this submission. The "acceptance criteria" discussed are likely related to software verification and validation, adherence to standards, and demonstrating substantial equivalence to existing devices with similar functionalities.

1. Table of Acceptance Criteria and Reported Device Performance

As mentioned above, this 510(k) is for an enhanced PACS system and does not present specific diagnostic performance metrics. The "performance" is primarily demonstrated through compliance with standards and equivalence to predicate devices. There are no explicit quantitative acceptance criteria for diagnostic performance in terms of sensitivity, specificity, etc., as it's not a new diagnostic algorithm.

The "performance" described is in terms of:

• Software Functionality: Viewing, manipulation, communication, and storage of medical images.
• Integration: HL7-/DICOM-compatible RIS workflow.
• Technological Characteristics: Runs on Windows OS, supports DICOM images, image data compression (lossless and lossy).
• Imaging Algorithms (inherited/similar to predicates): MPR, MIP, MinIP, VRT, SSD, Digitally Reconstructed Radiograph, Editor functionality, Registration, Region Growing, Quantitative measurements.
• Automatic Spine Labeling (inherited/similar to predicates): Anatomy Labeling of Vertebra bodies, automatically suggested labels with manual override.

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

The document does not describe a "test set" in the context of diagnostic performance evaluation (e.g., a set of medical images used to evaluate an algorithm's diagnostic accuracy). The testing performed was software verification and validation testing at Unit, Integration, and System levels, as per IEC 62304. This type of testing uses various software inputs and configurations to ensure functional correctness, rather than a diagnostic image dataset. No specific sample size of images or data provenance (country, retrospective/prospective) is provided because it's not relevant for this type of submission.

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

Not applicable. There was no diagnostic "test set" requiring expert ground truth for diagnostic accuracy evaluation.

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

Not applicable. There was no diagnostic "test set" requiring expert ground truth or adjudication.

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

Not applicable. This 510(k) does not present an MRMC study comparing human reader performance with and without AI assistance, as it is a PACS system enhancement, not a new AI-powered diagnostic tool.

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

Not applicable. This is not a standalone diagnostic algorithm. syngo.via is a platform for viewing, manipulation, communication, and storage of medical images, intended to "support the physician in diagnosis and treatment planning." The functionalities described (like automatic spine labeling) are features within this broader platform, and their performance is indicated as being similar to those from previously cleared predicate devices.

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

Not applicable. As there was no diagnostic test set in the traditional sense, there was no ground truth for diagnostic accuracy established through expert consensus, pathology, or outcomes data. The "ground truth" for the software's functional performance would be defined by the software requirements and design specifications, verified through testing procedures.

8. The sample size for the training set

Not applicable. This 510(k) does not describe a new AI algorithm that requires a training set. The enhanced functionalities are stated to have "similar technological characteristics as the predicate device" and incorporate "imaging and post processing algorithms compared to the above mentioned predicate devices." This implies that any underlying algorithms for features like "Automatic Spine Labeling" are either existing, well-established, or derived from components previously cleared, rather than newly developed and trained models.

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

Not applicable, as there is no mention of a training set for a new algorithm in this 510(k) submission.

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