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Your MAGNETOM system is indicated for use as a magnetic 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 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.

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.

The subject devices, MAGNETOM Vida with software syngo MR XA31A, and MAGNETOM Vida with syngo MR XA20A, with the new pulse sequence MR Fingerprinting (MRF) consists of slightly modified software that are similar to what is currently offered in the predicate devices, MAGNETOM Vida with syngo MR XA31A (K203443) and MAGNETOM Vida with syngo MR XA20A (K192924) respectively.

The subject devices MAGNETOM Vida with software syngo MR XA31A, and MAGNETOM Vida with synqo MR XA20A includes features that were cleared under K203443 and K192924 respectively. In addition to these features, the subject devices include a new pulse sequence type called MR Fingerprinting (MRF), a method that permits the simultaneous non-invasive quantification mapping of MRF-derived T1 and T2 relaxation times of brain tissue. The MRF is not intended to yield the ground truth T1 and T2 relaxation times of brain tissue.

The document describes the Siemens MAGNETOM Vida MRI system with a new pulse sequence called MR Fingerprinting (MRF). The acceptance criteria for this device and the study proving it meets these criteria are outlined as follows:

1. Acceptance Criteria and Reported Device Performance

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

• Sample Size: 3 healthy volunteers were scanned multiple times using multiple systems. Additionally, several clinical patient cases demonstrating a longitudinal use case scenario (repeated scans from the same subject over time) were provided.
• Data Provenance: The document does not explicitly state the country of origin. The study appears to be prospective, as it involved actively scanning volunteers and collecting clinical patient cases for demonstration.

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

The document does not specify the number of experts or their qualifications for establishing ground truth for the provided clinical patient cases or for interpreting the volunteer scans. It states that the device provides "information that may assist in diagnosis" when interpreted by a trained physician, but this is in the general "Indications for Use" and not directly about the ground truth establishment for the performance study.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1) for the test set.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not explicitly mentioned as being done to compare human readers with and without AI assistance. The study focuses on the technical performance of the MRF sequence itself.

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

Yes, a standalone performance evaluation of the MRF sequence was performed. The "Performance bench test" and "Software verification and validation" involved quantitative evaluation of MRF-derived T1 and T2 values in phantoms and volunteers, and testing to confirm stable and reproducible parametric values across systems. This assessment of the algorithm's output without human interpretation is a standalone evaluation.

7. The Type of Ground Truth Used

The ground truth used for the quantitative evaluation of T1 and T2 values came from:

• Quantitative Phantom: For confirming stability and reproducibility of parametric values.
• Healthy Volunteers: For evaluating quantitative performance in terms of precision (repeatability and reproducibility) for T1 and T2 maps.
• The document implies that for the "Sample clinical images" and "clinical patient cases," the assessment was based on whether the sequence executed successfully and produced images free of artifacts, rather than comparing against an external, independent "ground truth" for diagnosis. The MRF itself is described as "not intended to yield the ground truth T1 and T2 relaxation times of brain tissue."

8. The Sample Size for the Training Set

The document does not provide information on the sample size used for the training set for the MRF pulse sequence.

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

The document does not provide information on how the ground truth for the training set was established, as details about a training set are not included.

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The IMRIS iMRI 3T V 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 inages and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis.

The IMRIS iMRI 3T V system 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 IMRIS iMRI 3T V MRI systems may also be used for imaging in a multi-room suite.

The IMRIS iMRI 3T V is 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 (DR) until imaging is requested. The system retains all standard diagnostic features of an MRI system in the DR. The DR is separated from the intra-operative Operating Room (OR) by sliding doors that are part of the facility structure.

The IMRIS iMRI 3T V is a tool for radiologists and surgeons, used to acquire images for diagnostic, intraoperative, or interventional procedures. For OR purposes, high-resolution images can be obtained immediately prior to surgical incision, intraoperatively, and after wound closure. The IMRIS iMRI 3T V is based on the IMRIS iMRI 3T S cleared under 510(k) K133692 and the Siemens MAGNETOM Vida MRI system cleared under 510(k) K192924. The major components of the IMRIS iMRI 3T V system are: the Siemens MAGNETOM Vida MRI system with minor modifications, IMRIS Magnet Mover System, RF coils, Application platform, OR Table Assembly, Head fixation device, IMRISeye, and Horseshoe headrest.

Here's a summary of the acceptance criteria and the study information for the IMRIS iMRI 3T V system, based on the provided text:

Acceptance Criteria and Device Performance

The FDA clearance document for the IMRIS iMRI 3T V system does not explicitly detail a table of specific numerical acceptance criteria and corresponding reported device performance values in the way one might see for an AI algorithm's sensitivity/specificity. Instead, the "acceptance criteria" are implied by the successful completion of design verification and validation tests against established standards and the confirmation of "sufficient quality for diagnostic use" by radiologists.

Study Details

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

   • The document mentions "a number of V&V tests" and that images were produced and confirmed by radiologists, but it does not specify the sample size (number of images, cases, or patients) used for a distinct test set for image quality evaluation.
   • Data Provenance: Not specified. The document does not indicate the country of origin of the data or whether it was retrospective or prospective.

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

   • The document states, "Board certified Radiologist confirmation that images produced by the device are of sufficient quality for diagnostic use."
   • Number of Experts: Singular ("Radiologist") is used, implying at least one board-certified radiologist. The exact number is not provided.
   • Qualifications: "Board certified Radiologist". (No specific years of experience are mentioned).

3. Adjudication method for the test set:

   • Not specified. The document only mentions "Board certified Radiologist confirmation," but it does not detail a specific adjudication method like 2+1 or 3+1 if multiple radiologists were involved.

4. Multi Reader Multi Case (MRMC) comparative effectiveness study:

   • No, a MRMC comparative effectiveness study was not explicitly mentioned or described. The study focuses on demonstrating the substantial equivalence of the device to its predicate through compliance with standards and expert confirmation of image quality, rather than quantifying human reader improvement with/without AI assistance. The device is an MRI system, not an AI-powered diagnostic tool for interpretation.

5. Standalone (algorithm only without human-in-the-loop performance) study:

   • Yes, in the sense that the device's technical performance and image quality were evaluated independently. The "Board certified Radiologist confirmation" would be an assessment of the output (images) produced by the device itself, rather than an assessment of how well a human interprets those images with or without AI assistance. The device is a diagnostic imaging system, designed to produce images for human interpretation, not an AI algorithm for autonomous diagnosis.

6. Type of ground truth used:

   • Expert Consensus/Opinion: The ground truth for image quality was established by a "Board certified Radiologist confirmation" that images were of "sufficient quality for diagnostic use." This relies on expert interpretation and judgment. There's no mention of pathology or outcomes data being used for this specific evaluation.

7. Sample size for the training set:

   • Not applicable/Not specified. The IMRIS iMRI 3T V is a magnetic resonance diagnostic device (hardware system), not an AI algorithm that undergoes "training" on a dataset in the conventional machine learning sense for image interpretation. The "training" of the system would refer to its engineering, calibration, and adherence to established physical principles and specifications.

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

   • Not applicable. As above, this is a hardware device, not an AI algorithm model that learns from a labeled training set.

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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/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.

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, MAGNETOM Sola, MAGNETOM Lumina, MAGNETOM Altea with software syngo MR XA31A includes new and modified hardware and software compared to the predicate device, MAGNETOM Vida with software syngo MR XA20A.

This document describes the Siemens MAGNETOM MR system (various models) with syngo MR XA31A software, and it does not describe an AI device. The information provided is a 510(k) summary for a Magnetic Resonance Diagnostic Device (MRDD). The "Deep Resolve Sharp" and "Deep Resolve Gain" features are mentioned as using "trained convolutional neuronal networks" but the document does not provide details on acceptance criteria or studies specific to the AI components as requested.

Therefore, many of the requested items (e.g., sample sizes for training/test sets for AI, expert consensus for ground truth, MRMC studies) cannot be extracted from this document because it is primarily focused on the substantial equivalence of the overall MR system and its general technological characteristics, not a specific AI algorithm requiring detailed performance studies against a clinical ground truth.

However, I can extract the available information, especially concerning the "Deep Resolve Sharp" and "Deep Resolve Gain" features, and note where the requested information is not present.

Here's the breakdown of available information, with specific answers to your questions where possible:

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

The document does not specify quantitative acceptance criteria for the "Deep Resolve Sharp" or "Deep Resolve Gain" features, nor does it present a table of reported device performance metrics for these features in the context of clinical accuracy or diagnostic improvement specifically. The performance testing mentioned is general for the entire system ("Image quality assessments," "Performance bench test," "Software verification and validation"), concluding that devices "perform as intended and are thus substantially equivalent."

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

• Test Set Sample Size: Not explicitly stated for specific features like "Deep Resolve Sharp" or "Deep Resolve Gain." The document broadly mentions "Sample clinical images" were used for "Image quality assessments."
• Data Provenance (Country/Retrospective/Prospective): Not specified in the document.

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 specified. The document states "Image quality assessments by sample clinical images" and that the "images...when interpreted by a trained physician yield information that may assist in diagnosis," but it does not detail the number or qualifications of experts involved in these assessments for specific software features or for establishing ground truth for any AI component.

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

Not specified.

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

An MRMC study was not described for the "Deep Resolve Sharp" or "Deep Resolve Gain" features or any other AI component. The document references clinical publications for some features (e.g., Prostate Dot Engine, GRE_WAVE, SVS_EDIT) but these are general publications related to the underlying clinical concepts or techniques, not comparative effectiveness studies of the system's AI features versus human performance. The statement "No additional clinical tests were conducted to support substantial equivalence for the subject devices" reinforces this.

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

While "Deep Resolve Sharp" and "Deep Resolve Gain" involve "trained convolutional neuronal networks," the document does not describe standalone performance studies for these algorithms. Their inclusion is framed as an enhancement to the overall MR system's image processing capabilities, rather than a separate diagnostic AI tool. The stated purpose of Deep Resolve Sharp is to "increases the perceived sharpness of the interpolated images" and Deep Resolve Gain "improves the SNR of the scanned images," both being image reconstruction/enhancement features.

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

Not specified for any AI-related features. For general image quality assessment, the "trained physician" is mentioned as interpreting images to assist in diagnosis, implying clinical interpretation, but no formal ground truth establishment process is detailed.

8. The sample size for the training set

Not specified for the "trained convolutional neuronal networks" used in "Deep Resolve Sharp" or "Deep Resolve Gain."

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

Not specified.

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