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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.

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.

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

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.

Ask a specific question about this device

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.

The subject devices, MAGNETOM Avanto® and MAGNETOM Skyra™ with software syngo MR XA61A, consist of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Sola with syngo MR XA51A (K221733) and MAGNETOM Vida with syngo MR XA50A (K213693).

The provided text is a 510(k) summary for MRI devices (MAGNETOM Avanto fit; MAGNETOM Skyra fit) and does not contain detailed acceptance criteria or a study proving that a specific device meets those criteria in the typical sense for an AI/ML medical device.

This document describes hardware and software updates to existing MR systems, which are general Magnetic Resonance Diagnostic Devices (MRDD). The "acceptance criteria" here are mainly related to maintaining substantial equivalence to predicate devices and conforming to recognized standards for safety and performance (e.g., IEC 60601-1, ISO 14971, NEMA standards for SNR and uniformity, and software validation guidance).

Here's a breakdown based on the information provided, highlighting why it doesn't fit the typical AI/ML device study request:

1. Table of Acceptance Criteria and Reported Device Performance

Instead of specific quantitative performance metrics for a diagnostic task (like sensitivity/specificity for disease detection), the acceptance criteria for these MR systems are based on demonstrating that new and modified components maintain safety and performance comparable to their predicate devices and adhere to relevant standards.

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

The document mentions "sample clinical images" were used for image quality assessment. However, it does not specify the sample size, country of origin, or whether the data was retrospective or prospective.

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. The document states that the devices are intended for use by "healthcare professionals familiar with and responsible for the acquisition and post processing of magnetic resonance images," and the images are "interpreted by a trained physician" to assist in diagnosis, but it does not detail an expert ground truth establishment process for a specific test set.

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

This information is not 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 such study was mentioned. This submission is for an MR system, not an AI/ML-assisted diagnostic device, so a comparative effectiveness study of human readers with/without AI assistance would not be applicable here.

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

This is not an AI/ML algorithm-only device; it's a general MR system. Therefore, a standalone algorithm performance study is not applicable or mentioned.

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

Given the nature of the device (an MR system), the "ground truth" for image quality assessment would typically be visual comparison by trained MR physicists or radiologists, ensuring that the new sequences or hardware components produce images of diagnostic quality, comparable to, or better than, existing methods. However, the exact type of ground truth (e.g., specific metrics, qualitative expert assessment) is not explicitly stated beyond "image quality assessment by sample clinical images."

8. The sample size for the training set

This information is not applicable. The document describes updates to an MR system, not a machine learning model that requires a training set.

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

This information is not applicable as there is no mention of a training set for a machine learning algorithm.

Ask a specific question about this device

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.

The subject devices, MAGNETOM Aera (including MAGNETOM Aera Mobile), MAGNETOM Skyra, MAGNETOM Prisma, MAGNETOM Prisma™, MAGNETOM Vida, MAGNETOM Lumina with software syngo MR XA60A, consist of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Vida with syngo MR XA50A (K213693).

This FDA 510(k) summary describes several updates to existing Siemens Medical Solutions MRI systems (MAGNETOM Vida, Lumina, Aera, Skyra, Prisma, and Prisma fit), primarily focusing on software updates (syngo MR XA60A) and some modified/new hardware components. The document highlights the evaluation of new AI features, specifically "Deep Resolve Boost" and "Deep Resolve Sharp."

Here's an analysis of the acceptance criteria and the study details for the AI features:

1. Table of Acceptance Criteria and Reported Device Performance

The document provides a general overview of the evaluation metrics used but does not explicitly state acceptance criteria in a quantitative format (e.g., "Deep Resolve Boost must achieve a PSNR of X" or "Deep Resolve Sharp must achieve Y SSIM"). Instead, it describes the types of metrics used and qualitative assessments.

• Impact characterized by PSNR and SSIM. | 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. |
  | Deep Resolve Sharp | - Preservation of image quality (image sharpness) compared to original.
• Impact characterized by PSNR, SSIM, and perceptual loss.
• Verification and validation by visual rating and evaluation of image sharpness by intensity profile comparisons. | 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. |

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

• Deep Resolve Boost: The document doesn't explicitly state a separate "test set" size. It mentions the "Training and Validation data" which includes:
  • TSE: more than 25,000 slices
  • HASTE: pre-trained on the TSE dataset and refined with more than 10,000 HASTE slices
  • EPI Diffusion: more than 1,000,000 slices
  • Data Provenance: The data covered a broad range of body parts, contrasts, fat suppression techniques, orientations, and field strength. No specific country of origin is mentioned, but the manufacturer (Siemens Healthcare GmbH) is based in Germany, and Siemens Medical Solutions USA, Inc. is the submitter. The data was "retrospectively created from the ground truth by data manipulation and augmentation."
• Deep Resolve Sharp: The document doesn't explicitly state a separate "test set" size. It mentions "Training and Validation data" from "on more than 10,000 high resolution 2D images."
  • Data Provenance: Similar to Deep Resolve Boost, the data covered a broad range of body parts, contrasts, fat suppression techniques, orientations, and field strength. Data was "retrospectively created from the ground truth by data manipulation." No specific country of origin is mentioned.

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

Not specified. The document states that the acquired datasets "represent the ground truth." There is no mention of expert involvement in establishing ground truth for the test sets. The focus is on technical metrics (PSNR, SSIM) and "visual comparisons" or "visual rating" which implies expert review, but the number and qualifications are not provided.

4. Adjudication Method for the Test Set

Not explicitly stated. The document mentions "visual comparisons" for Deep Resolve Boost and "visual rating" for Deep Resolve Sharp. This suggests subjective human review, but no specific adjudication method (like 2+1 or 3+1 consensus) is detailed.

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 described for the AI features. The studies mentioned (sections 8 and 9) focus on evaluating the technical performance and image quality of the AI algorithms themselves, not on their impact on human reader performance.

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

Yes, standalone performance evaluation of the algorithms was conducted. The "Test Statistics and Test Results Summary" for both Deep Resolve Boost and Deep Resolve Sharp detail the evaluation of the network's impact using quantitative metrics (PSNR, SSIM, perceptual loss) and qualitative assessments ("visual comparisons," "visual rating," "intensity profile comparisons"). This represents the algorithm's performance independent of a human reader's diagnostic accuracy.

7. The Type of Ground Truth Used

The ground truth used for both Deep Resolve Boost and Deep Resolve Sharp was the acquired datasets themselves, representing the original high-quality or reference images/slices.

• For Deep Resolve Boost, input data was "retrospectively created from the ground truth by data manipulation and augmentation," including undersampling k-space lines, lowering SNR, and mirroring k-space data. The original acquired data serves as the target "ground truth" for the AI to reconstruct/denoise.
• For Deep Resolve Sharp, input data was "retrospectively created from the ground truth by data manipulation," specifically by cropping k-space data to create low-resolution input, with the original high-resolution data serving as the "output / ground truth" for training and validation.

8. The Sample Size for the Training Set

• Deep Resolve Boost:
  • TSE: more than 25,000 slices
  • HASTE: pre-trained on the TSE dataset and refined with 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

The ground truth for the training set was established as the acquired, unaltered (or minimally altered, e.g., removal of k-space lines to simulate lower quality input from high quality ground truth) raw imaging data.

• For Deep Resolve Boost: "The acquired datasets (as described above) represent the ground truth for the training and validation. Input data was retrospectively created from the ground truth by data manipulation and augmentation." This implies that the original, high-quality scans were considered the ground truth, and the AI was trained to restore manipulated, lower-quality versions to this original quality.
• For Deep Resolve Sharp: "The acquired datasets represent the ground truth for the training and validation. Input data was retrospectively created from the ground truth by data manipulation. 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." Similar to Boost, the original, higher-resolution scans served as the ground truth.

Ask a specific question about this device

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/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 inages 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.

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 Skyra Fit with software syngo MR XA50A includes new and modified hardware and software compared to the predicate device, MAGNETOM Vida with software syngo MR XA31A. A high level summary of the new and modified hardware and software is provided below:

Hardware
Modified Hardware

• Cover: The cover has been modified to bring the system up to the Siemens Healthineers Design incl. all BioMatrix components and interfaces.
• EPC (Electronic Cabinet and Measurement Control / Electronic Power Cabinet): upgrade of components to upgrade the EPC to the newest electronic cabinet series

Software
New Features and Applications

• TSE MoCo: TSE MoCo is an image-based motion correction in the averagedimension for the TSE pulse sequence type.
• Automatic fiducial detection: MR Breast Biopsy is improved with an automatic fiducial detection.

Modified Features and Applications

• Fast GRE RefScan: A speed-optimized reference scan for GRAPPA and SMS kernel calibration for echo planar imaging pulse sequence types.
  Other Modifications and / or Minor Changes
• The MAGNETOM Skyra Fit is a new MRI System which is the result of an upgrade from a MAGNETOM Verio.

The provided document is a 510(k) summary for the MAGNETOM Skyra Fit device, which is a Magnetic Resonance Diagnostic Device (MRDD). This document primarily focuses on establishing substantial equivalence to a predicate device (MAGNETOM Vida) and does not detail a clinical study with acceptance criteria, human reader performance, or training/test set specifics for an AI algorithm.

The document states:

• "No additional clinical tests were conducted to support substantial equivalence for the subject device; however, as stated above, sample clinical images were provided. No clinical publications were referenced." (Page 6, Section 10. Clinical Tests / Publications)
• The performance tests conducted were "Sample clinical images" and "Image quality assessments by sample clinical images." (Page 6, Section 9. Nonclinical Tests)

Therefore, based on the provided text, a detailed answer to your request, particularly concerning acceptance criteria for an AI device, human reader studies, and AI training/test set specifics, cannot be fully provided directly from this document. This document describes a new MR system, not an AI software.

However, I can extract the information that is present and explain where the requested information is not available:

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

   • Not explicitly provided in terms of numerical acceptance criteria for a clinical study comparing performance against a predicate. The document states: "The results from each set of tests demonstrate that the subject device performs as intended and is thus substantially equivalent to the predicate device to which it has been compared." (Page 6, Section 9. Nonclinical Tests). The performance assessment appears to be qualitative based on "sample clinical images" and "image quality assessments."
   • Device Performance (as described): "The subject device performs as intended and is thus substantially equivalent to the predicate device." (Page 6)

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

   • Not provided. The document mentions "sample clinical images" but does not specify the sample size, data provenance, or whether they were retrospective or prospective.

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)

   • Not provided. The document refers to images interpreted by a "trained physician" for diagnosis (Page 5, Section 5. Intended Use), but this is a general statement about the use of an MRDD, not specific to establishing ground truth for a test set in the context of a new feature evaluation or AI study.

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

   • Not 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 MRMC study was done. The document explicitly states, "No additional clinical tests were conducted to support substantial equivalence for the subject device..." (Page 6).

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

   • Not applicable/Not done for an AI algorithm. This document is for an MR imaging system, not an AI diagnostic algorithm.

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

   • Not explicitly stated/not applicable in the context of an AI study. The "sample clinical images" were likely evaluated for image quality and equivalence to the predicate, rather than for diagnostic ground truth for an AI algorithm.

8. The sample size for the training set

   • Not applicable/Not provided. This is not a submission for an AI algorithm that would require a distinct training set.

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

   • Not applicable/Not provided.

Summary based on the provided document:

This 510(k) submission for the MAGNETOM Skyra Fit MRI system focuses on demonstrating substantial equivalence to a previously cleared predicate device (MAGNETOM Vida) by showing that new and modified hardware and software features maintain equivalent safety and performance. This is typically achieved through non-clinical performance testing, including image quality assessments, software verification and validation, and electrical/mechanical safety tests, rather than multi-reader clinical studies or AI algorithm performance evaluations.

The "sample clinical images" mentioned are likely used to qualitatively demonstrate that the new system's output images are comparable in quality to those of the predicate device, thereby supporting the claim of substantial equivalence for diagnosis when interpreted by a trained physician. The document explicitly states that no additional clinical tests were conducted, meaning there were no new studies involving human readers or comparative effectiveness with or without AI assistance.

Ask a specific question about this device

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/ 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.

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.

MAGNETOM Aera, MAGNETOM Skyra and MAGNETOM Prisma/ Prisma/ with software syngo MR XA30A, include new and modified hardware and software compared to the predicate device, MAGNETOM Vida with software syngo MR XA20A. A high-level summary of the new and modified hardware and software is provided below:

Hardware

• New Computer

Software
New Features and Applications

• SVS EDIT is a special variant of the SVS SE pulse sequence type, which acquires two different spectra (one with editing pulses on resonance, one with editing pulses off resonance) within a single sequence.
• BEAT_FQ_nav is a pulse sequence that allows the user to make use of navigator echo based respiratory gating for flow imaging to acquire 4D flow data. Both navigator echo based respiratory gating and flow imaging are cleared features available on the predicate device. However, the combination of the two is new.
• Injector coupling is a software application that allows the connection of certain contrast agent injectors to the MR system for simplified, synchronized contrast iniection and examination start.
• The Prostate Dot Engine provides an assisted and guided workflow for prostate imaging. This automated workflow leads to higher reproducibility of slice angulation and coverage based on the segmentation algorithm described and cleared with syngo.via VB40; this may support exams not having to be repeated.

Modified Features and Applications

• An optimized high bandwidth inversion recovery pulse is combined with gradient echo readout to improve diagnostic image quality when imaging myocardial tissue.
• The AbsoluteShim mode is a shimming procedure based on a 3-echo gradient echo protocol.

Other Modifications and / or Minor Changes

• Elastography-AddIn synchronizes settings between the Elastography sequence and the active driver.
• HASTE MoCo is an image-based motion correction function in the averagedimension for the HASTE pulse sequence type.
• Coil independent pulse sequences remove the coil information from the pulse sequences and generate this information during run-time from automatic coil detection and localization.

The provided document is a 510(k) summary for the Siemens MAGNETOM Aera, MAGNETOM Skyra, and MAGNETOM Prisma/Prismafit MR systems with syngo MR XA30A software. It details the device's substantial equivalence to a predicate device but does not describe specific acceptance criteria for a new feature's performance or a study demonstrating the device meets such criteria.

The document primarily focuses on demonstrating substantial equivalence by outlining:

• Device Description: New and modified hardware/software features (e.g., SVS EDIT, BEAT_FQ_nav, Injector coupling, Prostate Dot Engine, optimized high bandwidth inversion recovery pulse, AbsoluteShim mode, Elastography-AddIn, HASTE MoCo, Coil independent pulse sequences).
• Nonclinical Tests: These include "Sample clinical images," "Image quality assessments using sample clinical images," "Performance bench test," and "Software verification and validation." The results "demonstrate that the devices perform as intended and are therefore, substantially equivalent to the predicate device to which it has been compared."
• Clinical Tests/Publications: No clinical tests were conducted to support substantial equivalence for the subject devices. However, "sample clinical images were provided," and "clinical publications were referenced to provide information on the use of the following features and functions" (listing publications for SVS_EDIT and Prostate Dot Engine).

Therefore, I cannot extract the specific information requested because it is not present in the provided text. The document does not contain:

• A table of acceptance criteria and reported device performance.
• Details on sample sizes, data provenance, number of experts for ground truth, or adjudication methods for any specific test set.
• Information regarding MRMC comparative effectiveness studies or standalone algorithm performance.
• Details on the type of ground truth used for specific features.
• Training set sample size or how ground truth was established for a training set.

The document's purpose is to show that the new/modified features are substantially equivalent to existing ones and perform as intended through verification and validation activities, rather than presenting a performance study against predefined acceptance criteria for novel functionalities.

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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 systems 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 mages 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 systems 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.

MAGNETOM Aera, MAGNETOM Skyra and MAGNETOM Prisma/Prisma" with syngo MR E11C software were cleared with K153343 and MAGNETOM Avanto" and MAGNETOM Skyrafff systems with syngo MR E11C software were cleared with K162102.

To address the new feature GOKnee3D and the modifications summarized in Section 3 and furthermore described in this Premarket Notification Siemens intends to make the software application package syngo MR E11C - AP04 available to the systems mentioned above.

The additional options for the synqo MR E11C software is being made available for the following MAGNETOM MR Systems:

• . MAGNETOM Aera,
• MAGNETOM Skyra / Skyraf" ●
• MAGNETOM Prisma / Prisma™ ●
• MAGNETOM Avantofit .

Those options include a new feature with a modified sequence and modified features for the above mentioned MR systems. A high level summary of sequences, features and improvements made available for the above systems is included below.

The provided text does not contain information about specific acceptance criteria, a study proving a device meets these criteria, or detailed performance metrics. The document is a 510(k) premarket notification summary for Siemens MAGNETOM MRI systems, explaining their substantial equivalence to previously cleared devices.

It discusses:

• Device Name: MAGNETOM Aera, MAGNETOM Skyra/Skyrafit, MAGNETOM Prisma/Prismafit, MAGNETOM Avantofit with syngo MR E11C - AP04 software.
• Intended Use: Magnetic resonance diagnostic device (MRDD) for imaging internal structures and functions of the head, body, or extremities, assisting in diagnosis.
• New Feature: GOKnee3D (fast, push-button knee examination with AutoAlign knee localizer and two CAIPIRINHA SPACE sequences).
• Modified Features: SPACE with CAIPIRINHA acquisition technique, Dual Monitor support, Compressed Sensing Cardiac Cine (BEAT_CS Sequence).
• Technological Characteristics: Similar to predicate devices, conforming to IEC 62304:2006 and other standards.
• Nonclinical Tests: Performance testing for modified sequence (CAIPIRINHA SPACE), image quality assessments of new sequences/algorithms, software verification and validation.
• Clinical Tests: "No clinical tests were conducted to support the subject devices and the substantial equivalence argument; however, clinical images and LV evaluation were provided to support the argumentation and documentation which demonstrate the clinical utility and technical capabilities of the method."
• Safety and Effectiveness: Risk management via ISO 14971:2007, adherence to IEC 60601-1 series, and compliance with FDA recognized standards.
• Substantial Equivalence: Concluded based on identical intended use and similar technological characteristics to predicate devices. The hardware is unchanged.

Therefore, I cannot populate the requested table or answer the specific questions about acceptance criteria, study details, sample sizes, expert involvement, and ground truth establishment, as this information is not present in the provided text. The document explicitly states that no clinical tests were conducted, and the assessment relies on nonclinical tests and substantial equivalence to predicate devices.

Ask a specific question about this device

Your MAGNETOM MR 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 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 inages 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 MR 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 Aera and MAGNETOM Skyra with syngo MR E11C Software is cleared with K153343. To address the Compressed Sensing Cardiac Cine and the modified Software Features described in this Premarket Notification Siemens intends to make the Software Application Package syngo MR E11C - AP02 available to the MAGNETOM Aera and Skyra.

The additional options for the synqo MR E11C software is being made available for the following MAGNETOM MR Systems:

• . MAGNETOM Aera,
• MAGNETOM Skyra .

The additional Options for the MR Scanner Software syngo MR E11C include a new feature with a new sequence and modified features for the above mentioned MR systems. A high level summary of sequences, features and improvements made available for the above systems is included below.

The provided text describes a 510(k) premarket notification for Siemens Medical Solutions USA, Inc.'s MAGNETOM Aera and MAGNETOM Skyra with syngo MR E11C - AP02 Software. This document is a summary of the safety and effectiveness information supporting substantial equivalence to a predicate device.

However, the document specifically states: "No clinical tests were conducted to support the subject devices and the substantial equivalence argument; however, clinical images and LV evaluation were provided to support the argumentation and documentation which demonstrate the clinical utility and technical capabilities of the method."

This means that the information requested regarding acceptance criteria and a study proving the device meets these criteria (including details on sample size, expert ground truth, adjudication, MRMC studies, standalone performance, and training set details) is not available in this document because a clinical study of this nature was not performed.

The substantial equivalence argument is based on non-clinical tests (image quality assessments, software verification and validation, and demonstrating similar technological characteristics to the predicate device) rather than a comparative clinical study.

Therefore, I cannot provide a detailed answer to your request based on the provided text, as the specific clinical study details you're asking for were explicitly stated as not having been conducted.

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The MAGNETOM systems [MAGNETOM Avantofit, MAGNETOM Skyrafit] 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 MAGNETOM systems 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.

Not Found

This document is a letter from the FDA to Siemens Medical Solutions USA, Inc. regarding their 510(k) premarket notification for the MAGNETOM Avanto and MAGNETOM Skyra devices. It confirms the substantial equivalence of these magnetic resonance diagnostic devices.

The document does not contain any information about acceptance criteria, device performance, a specific study, sample sizes, expert qualifications, adjudication methods, multi-reader multi-case studies, standalone performance, or ground truth establishment.

Therefore, I cannot provide the requested information based on the provided text.

Ask a specific question about this device

The MAGNETOM systems are indicated for use as magnetic resonance diagnostic devices (MRDD) that produce transverse, sagittal, coronal and oblique cross sectional images, spectroscopic images and/or spectra, and that display 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 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, syngo MR E11C system software, is being made available for the following MAGNETOM MR Systems:

• MAGNETOM Aera,
• MAGNETOM Skyra, ●
• MAGNETOM Prisma and
• MAGNETOM Prisma™ ●

The syngo MR E11C SW includes new sequences. new features and minor modifications of already existing features.

The provided text describes a 510(k) premarket notification for new software (syngo MR E11C) for Siemens MAGNETOM MR systems. However, it does not contain the detailed information required to answer all aspects of your request regarding acceptance criteria and a study proving device performance as typically expected for AI/ML device submissions.

This submission is for a software update to existing Magnetic Resonance Diagnostic Devices (MRDDs), and the focus is on demonstrating substantial equivalence to previously cleared predicate devices. The "study" mentioned is primarily non-clinical performance testing and software verification/validation, rather than a clinical study with acceptance criteria for specific diagnostic outcomes.

Here's an attempt to extract and infer information based on the provided text, highlighting what is present and what is missing:

1. Table of acceptance criteria and the reported device performance

The document does not explicitly state quantitative acceptance criteria for diagnostic performance or specific metrics. Instead, it relies on demonstrating that the new software's features perform "as intended" and maintain "equivalent safety and performance profile" compared to predicate devices.

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

• Test Set Sample Size: "Sample clinical images were taken for particular new and modified sequences." The specific number or characteristics of these images (sample size) is not provided.
• Data Provenance: The document does not specify the country of origin of the data or whether it was retrospective or prospective. It only mentions "sample clinical images," suggesting clinical data was used for assessment.

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. The document states "Image quality assessments... were completed," but does not detail who performed these assessments or how ground truth was established for them. For a diagnostic device, interpretation by a "trained physician" is mentioned in the Indications for Use, but this is a general statement about the device's usage, not specific to the assessment of the new software.

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

• This information is not 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, an MRMC comparative effectiveness study was not done. The document explicitly states: "No clinical tests were conducted to support the subject device and the substantial equivalence argument..."
• This submission is not for an AI-enhanced diagnostic tool in the sense of providing automated interpretations or assisting human readers in a measurable way with specific diagnostic outcomes. It's an update to MR imaging acquisition software. Therefore, the concept of "how much human readers improve with AI vs without AI assistance" does not apply in this context.

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

• The device is a Magnetic Resonance Diagnostic Device (MRDD) software update. Its output is images and/or spectra that are "interpreted by a trained physician" to "assist in diagnosis." As such, it is inherently a human-in-the-loop system. The non-clinical tests involved "Image quality assessments" and "Acoustic noise measurements," which are performance evaluations of the acquisition capabilities, not a standalone diagnostic interpretation by the algorithm.
• Therefore, a standalone diagnostic performance evaluation (algorithm only) in the context of providing a diagnosis was not performed or described.

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

• For "Image quality assessments," the type of ground truth is not explicitly stated. It can be inferred that it would likely involve visual assessment by experts against what is considered normal or expected for an MR image, potentially comparing to images acquired with predicate software or known anatomical/pathological features. However, specific ground truth methods like pathology or long-term outcomes data are not mentioned.

8. The sample size for the training set

• The document does not mention a separate training set or details about its size. This submission focuses on software changes and their verification, not on the development of a new AI model that requires a distinct training phase.

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

• Since a separate training set is not mentioned, the method for establishing its ground truth is also not provided.

Summary of what's present and what's missing:

This 510(k) submission primarily focuses on demonstrating that new software features (like quiet diffusion imaging, improved fast TSE, simultaneous multi-slice imaging, and a short acquisition time brain examination protocol) for existing MR systems maintain the fundamental technological characteristics, safety, and effectiveness of predicate devices. The "study" here is a series of non-clinical tests (image quality review, acoustic noise measurements, software V&V) rather than a clinical trial measuring diagnostic accuracy or reader performance. The level of detail you're asking for, especially concerning clinical study design elements like sample size, expert reader qualifications, adjudication methods, and ground truth establishment for diagnostic output, is typically found in submissions for AI/ML diagnostic tools that directly interpret images or provide diagnostic assistance, which is not the primary claim of this particular device update.

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