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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 K192574. 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 AiCE Reconstruction Processing Unit for MR is included with this system for the processing of images for various anatomical regions.

1. Acceptance Criteria and Reported Device Performance

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

The human observer study included 60 subjects and a total of 348 scans. The provenance of this data (e.g., country of origin, retrospective or prospective) is not specified in the provided document.

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

The human observer study involved 15 board-certified radiologists/cardiologists. The document does not explicitly state that these experts established "ground truth" for the test set, but rather that they evaluated the images and demonstrated a statistical preference for AiCE. Their qualifications are listed as "board certified radiologists / cardiologists." No further details on their experience (e.g., 10 years of experience) are provided.

4. Adjudication Method for the Test Set

The document does not specify an adjudication method (such as 2+1 or 3+1) for the human observer study. It only states that 15 radiologists/cardiologists provided evaluations leading to a statistical preference.

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

Yes, a multi-reader multi-case (MRMC) comparative effectiveness study was conducted. The study involved 15 board-certified radiologists/cardiologists evaluating images from 60 subjects and 348 scans.

The effect size of how much human readers improve with AI vs. without AI assistance is not explicitly quantified in terms of a specific numerical improvement in accuracy or efficiency. Instead, the study "demonstrated a statistical preference of AiCE when compared to other performance filters," indicating improved perception or diagnostic confidence with AiCE, but without detailing the magnitude of this improvement or the specific metrics used for "preference."

6. Standalone (Algorithm Only) Performance Study

Yes, a standalone performance study was done. The document states that "AiCE deep learning reconstruction underwent performance (bench testing) using a model observer study to determine that image low contrast detectability was maintained or improved, accompanied with other bench testing of SNR and contrast performance." This indicates an assessment of the algorithm's intrinsic image quality improvement without direct human interaction at that stage.

7. Type of Ground Truth Used

For the model observer study and bench testing, the ground truth appears to be based on objective image quality metrics such as "low contrast detectability," "SNR," and "contrast performance." These are inherent properties of the reconstructed images.

For the human observer study, the "ground truth" or reference for comparison was the performance of "other performance filters" (implicitly, the images reconstructed with these filters). The observers then indicated a "statistical preference" for AiCE, which served as the outcome measure. It isn't explicitly stated that the cases had a confirmatory diagnostic "ground truth" (e.g., pathology or outcomes data) that the radiologists were evaluating for accuracy. Rather, it focuses on the radiologists' perception and preference for the AiCE reconstructed images.

8. Sample Size for the Training Set

The document does not provide any information about the sample size used for the training set of the AiCE deep learning model.

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

The document does not provide any information on how the ground truth for the training set was established for the AiCE deep learning model.

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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 3.8 tons light weight magnet. It includes the Pianissimo™ technology (scan noise reduction technology). The design of the gradient coil and the WB coil of the Vantage Orian 1.5T provides the maximum field of view of 55 x 50 cm. The Model MRT-1550/AC, AD, AG, AH includes the standard gradient system and Model MRT-1550/AK, AL, AO, AP includes the XGO 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 19th, 2018 with the following modifications.

The provided text is a 510(k) summary for the Canon Medical Systems Vantage Orian 1.5T MR system (Model MRT-1550, V6.0). It outlines modifications made to a previously cleared device, specifically the addition of "Compressed SPEEDER" (compressed sensing) and "T2 Map Using Pre-Contrast Pulses" features, and an operating system upgrade (Windows 10).

Based on the provided text, the study focuses on evaluating the imaging performance of the new features, particularly "Compressed SPEEDER". The acceptance criteria and the study that proves the device meets them can be extracted as follows:

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

• Image degradation
• Diagnostic performance
• Lesion conspicuity
• Clinical utility | "It was confirmed that Compressed SPEEDER images were of diagnostic quality." |
  | T2 Map Using Pre-Contrast Pulses Functionality | Ability to generate T2 maps using data acquired with pre-contrast pulses. | "It was concluded that T2 maps can be generated using the data acquired using pre-contrast pulses." |

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

• Sample Size:
  • For Compressed SPEEDER and T2 Map: "utilizing phantoms and volunteer images". No specific number of phantoms or volunteers is mentioned.
  • For diagnostic review of Compressed SPEEDER: "representative images" were reviewed. No specific number of images is given.
• Data Provenance: Not explicitly stated, but it's implied to be internal testing by Canon Medical Systems, likely in Japan (where the manufacturer is located) or the US (where Canon Medical Systems USA is located). The text does not specify if the data was retrospective or prospective. Given the nature of a 510(k) submission for device modification, it's highly probable these were prospective tests specifically conducted for the submission.

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. The text mentions "American Board Certified Radiologists" (plural).
• Qualifications of Experts: "American Board Certified Radiologists". No specific years of experience are mentioned.

4. Adjudication method for the test set

• The text states, "Reviewers provided detailed assessments of image degradation, diagnostic performance, lesion conspicuity, and clinical utility." It does not mention a specific adjudication method (e.g., 2+1, 3+1) if multiple radiologists were involved, or whether they reached a consensus.

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 claim of AI assistance improving human reader performance. The "Compressed SPEEDER" feature is described as an accelerated fast scan technique, not an AI-assisted diagnostic tool for interpretation. This submission is for a conventional MRI system with new scan sequences, not an AI/ML-driven diagnostic device.

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

• The device is an MRI system. The "performance" being evaluated is the quality of the images generated by the system's new sequences. While the system operates "standalone" in generating images, the evaluation of "diagnostic quality" inherently involves human interpretation. The text describes "image quality testing" (presumably objective metrics using phantoms) and "review by American Board Certified Radiologists" (human-in-the-loop assessment of diagnostic utility).

7. The type of ground truth used

• Phantom Data: For technical image quality metrics (SNR, unfolding error, etc.), phantoms were used, which provide a known, controlled ground truth.
• Volunteer Images: For assessing the functionality and appearance of T2 maps and general image quality with Compressed SPEEDER. In this context, the "ground truth" for assessment would likely be the expected normal anatomy and the visual assessment of correct image formation by experts.
• Expert Consensus (Implicit/Assumed): For the "diagnostic quality" assessment by American Board Certified Radiologists, their collective judgment and experience serve as the de-facto ground truth for evaluating image utility in a clinical context. There's no mention of external pathology or outcomes data being used as ground truth for this specific 510(k) amendment, as the changes are to image acquisition methods, not a new diagnostic indication or algorithm.

8. The sample size for the training set

• This information is not provided in the 510(k) summary. The "Compressed SPEEDER" feature uses "compressed sensing," which is typically an image reconstruction algorithm, not a deep learning model that requires a "training set" in the common sense of AI/ML. If there were any machine learning components, details about training data would likely be separate from the performance evaluation of the final product. The text describes it as combining "parallel imaging... and compressed sensing," implying algorithmic rather than data-driven training.

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

• As a "training set" for an AI/ML model is not explicitly mentioned or implied to be part of this submission's new features, the method for establishing its ground truth is not provided. Compressed sensing is a mathematical reconstruction technique, not an AI model that learns from a labeled dataset.

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