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Vantage Galan 3T systems are indicated for use as a diagnostic imaging modality that produces crosssectional transaxial, coronal, sagittal, and oblique images that display anatomic structures of the head or body. Additionally, this system is capable of non-contrast enhanced imaging, such as MRA.

MRI (magnetic resonance imaging) images correspond to the spatial distribution of protons (hydrogen nuclei) that exhibit nuclear magnetic resonance (NMR). The NMR properties of body tissues and fluids are:

• Proton density (PD) (also called hydrogen density)
• Spin-lattice relaxation time (T1)
• Spin-spin relaxation time (T2)
• Flow dynamics
• Chemical Shift

Depending on the region of interest, contrast agents may be used. When interpreted by a trained physician, these images yield information that can be useful in diagnosis.

The Vantage Galan (Model MRT-3020) is a 3 Tesla Magnetic Resonance Imaging (MRI) System, previously cleared under K181593. This system is based upon the technology and materials of previously marketed Canon Medical Systems and is intended to acquire and display crosssectional transaxial, coronal, sagittal, and oblique images of anatomic structures of the head or body.

The provided text is a 510(k) summary for the Canon Medical Systems Corporation's Vantage Galan 3T, MRT-3020, V6.0 MRI System. This document focuses on demonstrating substantial equivalence to a predicate device, rather than providing a detailed study report with specific acceptance criteria and performance metrics for a novel AI device.

Therefore, the requested information elements (1, 2, 3, 4, 5, 7, 8, 9) regarding acceptance criteria, sample sizes, expert qualifications, ground truth establishment, and MRMC effectiveness studies cannot be fully extracted from this document as it is not a study report for an AI device.

However, based on the information provided regarding the "Compressed SPEEDER" feature, which is a new software functionality, I can deduce some aspects related to its evaluation.

Here's a breakdown of what can be extracted or inferred, and what cannot:

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

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

• Sample Size:
  • For technical image quality metrics (SNR, unfolding error, phase encode performance): Phantoms and volunteer images were used. The exact number of phantoms or volunteers is not specified.
  • For clinical image quality assessment by radiologists: Representative images were obtained using the subject device. The exact number of images or cases is not specified.
• Data Provenance: Not explicitly stated, but given it's a medical device submission by a Japanese company with a U.S. agent, the volunteer imaging likely occurred either in Japan or the US. This was a prospective evaluation of the new software feature.

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

• Number of experts: Not explicitly stated, but referred to as "American Board Certified Radiologists" (plural), indicating at least two.
• Qualifications of experts: "American Board Certified Radiologists." No specific experience level (e.g., "10 years of experience") is provided.

4. Adjudication method for the test set

• The document states that reviewers (radiologists) "provided detailed assessments." It does not specify an adjudication method (e.g., 2+1, 3+1, none) for reaching a consensus on the diagnostic quality or other assessments if multiple radiologists were involved. It simply says "reviewed by American Board Certified Radiologists."

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 explicitly mentioned or performed in the context of human reader improvement with AI assistance. The evaluation focused on the diagnostic quality of images produced by the device's new "Compressed SPEEDER" and "T2 Map" features, reviewed by radiologists, rather than comparing human reader performance with and without AI assistance from these features. The device's features (Compressed SPEEDER) are about image acceleration and quality, not necessarily AI for diagnostic assistance to humans.

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

• Yes, a standalone evaluation of the "Compressed SPEEDER" algorithm's technical performance was done using phantoms and volunteer images to assess SNR, unfolding error artifacts, and performance in all phase encode directions. The algorithm's output (images) was then assessed for diagnostic quality by radiologists. This refers to the algorithm generating the images, which are then interpreted.

7. The type of ground truth used

• For the technical image quality metrics (SNR, unfolding error, phase encode performance), the ground truth was based on known phantom dimensions and electromagnetic properties, along with expected image characteristics from volunteer scans.
• For the clinical assessment by radiologists, the ground truth was expert consensus (implied, as radiologists reviewed and confirmed diagnostic quality). No mention of pathology or outcomes data as ground truth is made.

8. The sample size for the training set

• The document does not specify a training set size or methodology. It is a 510(k) summary for a software update to an MRI system, not a detailed algorithm development report. It is likely that the Compressed SPEEDER algorithm was developed and trained internally by Canon Medical Systems, but details are not provided here.

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

• As the training set itself is not mentioned, the method for establishing its ground truth is not provided in this document.

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Vantage Orian 1.5T systems are indicated for use as a diagnostic imaging modality that produces cross-sectional transaxial, coronal, sagittal, and oblique images that display anatomic structures of the head or body. Additionally, this system is capable of non-contrast enhanced imaging, such as MRA.

MRI (magnetic resonance imaging) images correspond to the spatial distribution of protons (hydrogen nuclei) that exhibit nuclear magnetic resonance (NMR). The NMR properties of body tissues and fluids are:

·Proton density (PD) (also called hydrogen density)

• ·Spin-lattice relaxation time (T1)
  ·Spin-spin relaxation time (T2)

·Flow dynamics

·Chemical Shift

Depending on the region of interest, contrast agents may be used. When interpreted by a trained physician, these images yield information that can be useful in diagnosis.

The Vantage Orian (Model MRT-1550) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System. The Vantage Orian uses 1.4 m short and 4.0 tons light weight magnet. It includes the Canon Pianissimo™ and Pianissimo Zen technology (scan noise reduction technology). The design of the gradient coil and the whole body coil of the Vantage Orian provides the maximum field of view of 55 x 50 cm. The Model MRT-1550/AS, AT, AW, AX includes the standard gradient system. This system is based upon the technology and materials of previously marketed Canon Medical Systems MRI systems and is intended to acquire and display cross-sectional transaxial, coronal, sagittal, and oblique images of anatomic structures of the head or body. The Vantage Orian MRI System is comparable to the current 1.5T Vantage Orian MRI System (K182282), cleared October 19, 2018 with the following modifications.

This document is a 510(k) summary for a Magnetic Resonance Diagnostic Device (MRDD), specifically the Vantage Orian 1.5T, MRT-1550, V4.5. The submission is a "Special 510(k) Premarket Notification" for a modification of a cleared device. As such, the information provided focuses on demonstrating substantial equivalence to the predicate device rather than presenting a de novo study on a novel AI algorithm.

Therefore, many of the typical acceptance criteria and study details for an AI-powered diagnostic device, such as those related to reader studies, standalone performance, and extensive ground truth establishment for a new algorithm, are NOT present in this document. The document primarily focuses on hardware modifications (reusing an older magnet type in a new system configuration) and ensuring the new configuration performs equivalently to the already cleared system.

However, based on the information provided, here's what can be extracted and inferred:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria in a table format for imaging performance. Instead, it relies on the concept of "No change from the previous predicate submission" (K182282) for imaging performance. This implies that the acceptance criterion for imaging performance is equivalent performance to the predicate device.

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

The document does not specify a separate "test set" in the context of an algorithm's performance study with a specific sample size. The testing mentioned appears to be system-level verification and validation, including "bench testing" and "image quality testing."

• Sample Size: Not explicitly stated in terms of patient cases or images for performance evaluation. It refers to "image quality testing" without quantifying the number of images or patients.
• Data Provenance: Not specified. Given it's a hardware modification verification, the testing likely involved internal Canon Medical Systems data or phantoms. There is no mention of specific countries of origin or retrospective/prospective data collection for a performance study on an AI algorithm.

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

Not applicable in the context of this 510(k) submission. This is a hardware modification for an MRI system, not an AI diagnostic algorithm requiring expert-established ground truth for a clinical performance study. The ground truth for MRI system performance typically involves phantom studies, engineering specifications, and established image quality metrics.

4. Adjudication Method for the Test Set

Not applicable. There's no mention of a human reader study or expert adjudication for performance assessment in this submission.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

No. An MRMC study is not mentioned as this submission is for an MRI system hardware modification, not an AI-assisted diagnostic device.

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

No. This submission does not pertain to a standalone AI algorithm.

7. The Type of Ground Truth Used

For this type of device (an MRI system), the "ground truth" for performance is established through:

• Engineering specifications and measurements (e.g., static field strength, SAR, dB/dt).
• Phantom studies for image quality (e.g., resolution, signal-to-noise ratio, uniformity).
• Compliance with recognized consensus standards (IEC, NEMA).
• Clinical images (likely for qualitative assessment, but not explicitly stated as "ground truth" from pathology or outcomes).

8. The Sample Size for the Training Set

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

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

Not applicable.

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