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Vantage Fortian/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 Fortian (Model MRT-1550/ WK, WM, WQ, WQ)/Vantage Orian (Model MRT-1550/ A3, A4, A7, A8) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System. These Vantage Fortian/Orian models use 1.4 m short and 4.1 tons light weight magnet. They include the Canon Pianissimo Zen technology (scan noise reduction technology). The design of the gradient coil and the whole-body coil of these Vantage Fortian/Orian models provide the maximum field of view of 55 x 55 cm and include the standard gradient system.

The Vantage Orian (Model MRT-1550/ UC, UG, UH, UK, UL, UO, UP, AK, AL, AO, AP, Upgrade only: A3, A4, A7, A8, AC, AD, AG, AH) is a 1.5 Tesla Magnetic Resonance Imaging (MRI) System. The Vantage Orian models MRT-1550/ UC, UG, UH, UK, UL, UO, UP, Upgrade only: A3, A4, A7, A8 use 1.4 m short and 4.1 tons light weight magnet while the Vantage Orian models MRT-1550/ AK, AL, AO, AP, Upgrade only: AC, AD, AG, AH use 1.4 m short and 3.8 tons light weight magnet. All of the aforementioned models include the Canon Pianissimo™ and Pianissimo Zen technology (scan noise reduction technology). The design of the gradient coil and the whole-body coil of these Vantage Orian models provide the maximum field of view of 55 x 50 cm. The Model MRT-1550/ UC, UD, UG, UH, UK, UL, UO, UP, AK, AL, AO, AP includes the XGO gradient system. The Model MRT-1550/ A3, A4, A7, A8, AC, AD, AG, AH include 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 Fortian/Orian MRI System is comparable to the current 1.5T Vantage Fortian MRI System (K213305), cleared December 1, 2021 with the following modifications.

The provided text discusses changes to the Vantage Fortian/Orian 1.5T, MRT-1550, V8.0 with AiCE Reconstruction Processing Unit for MR and cites testing related to these changes. However, it does not provide a detailed study with specific acceptance criteria, reported performance, or comprehensive methodology (like sample sizes, ground truth establishment, or expert qualifications) that would typically be found in a standalone clinical validation study for an AI-powered device.

The document states that the submission is for "Modification of a cleared device" (K213305) and discusses "Risk Management activities for new software functionalities and pulse sequences." The testing mentioned is primarily verification and validation of these new features, confirming their intended function and not a full clinical efficacy study with specific performance metrics against a defined standard of care.

Here's an attempt to extract and describe what is available regarding acceptance criteria and studies, while highlighting the missing information based on your request:

Acceptance Criteria and Device Performance Study for Vantage Fortian/Orian 1.5T, MRT-1550, V8.0 with AiCE Reconstruction Processing Unit for MR

The document describes a 510(k) submission for modifications to an existing MRI system. The primary testing mentioned focuses on verification of new software functionalities: Iterative Motion Correction (IMC) and a Ceiling Camera feature.

1. Table of Acceptance Criteria and Reported Device Performance

The document provides very limited, high-level information regarding acceptance criteria and performance for the newly added features. It does not present a table with specific quantitative acceptance criteria or detailed performance metrics against those criteria for the diagnostic capability of the MRI system as a whole, or even for the specific features in a clinical context.

Important Note: The document explicitly states: "No change from the previous predicate submission, K213305" for Imaging Performance Parameters. This suggests that the core diagnostic imaging performance of the MRI system, including any benefits from AiCE reconstruction, was established in the predicate device's clearance and is not re-evaluated with new acceptance criteria in this submission. This current submission focuses on modifications.

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

• Iterative Motion Correction (IMC): "volunteer images."
  • Sample Size: Not specified.
  • Data Provenance: Not specified (e.g., country of origin, retrospective/prospective).
• Ceiling Camera: "volunteers."
  • Sample Size: Not specified.
  • Data Provenance: Not specified.

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

• Not specified. The testing described appears to be technical verification and validation rather than expert-reviewed clinical evaluation.

4. Adjudication Method for the Test Set

• Not specified. Given the nature of the described testing (technical confirmation of functionality rather than diagnostic performance against clinical ground truth), a formal adjudication method by experts is not mentioned or implied.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done

• No, an MRMC study is not described in this document. The document states that the imaging performance parameters for the device are "No change from the previous predicate submission, K213305." This implies that any studies relevant to diagnostic performance or improvements with AiCE would have been conducted and documented for the predicate device. This submission focuses on software and accessory changes.

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

• The testing described for IMC and the Ceiling Camera appears to be a form of standalone verification of the algorithm's functional output (e.g., reduction of motion artifacts, correct detection of patient position). However, no specific "standalone" performance metrics in a clinical diagnostic context (e.g., sensitivity, specificity for a particular pathology) are presented. The "AiCE Reconstruction Processing Unit" itself likely has standalone performance aspects, but these are not detailed in this document, as it refers back to the predicate device for imaging performance.

7. The Type of Ground Truth Used

• Iterative Motion Correction (IMC): The "ground truth" seems to be the visual assessment of "motion artifacts" in volunteer images. This is an implicit evaluation of image quality rather than a clinical truth like pathology.
• Ceiling Camera: The "ground truth" for patient orientation and anatomy position detection would be the actual patient orientation and anatomy position, likely determined by direct observation or other measurement methods during the volunteer testing, to confirm the accuracy of the camera's detection.

8. The Sample Size for the Training Set

• Not specified. The document describes changes to an existing system, including "Iterative Motion Correction (IMC)" which is a software functionality for MRI. While AI-based reconstructions like "AiCE" (which is part of the system name) typically involve significant training data, this document does not provide details on the training set for AiCE or for the new IMC feature. The focus is on the modified device and its changed components.

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

• Not specified. As the training set size and details are not provided, neither is information on how its ground truth was established.

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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 4.1 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 55 x 50 cm. The Model MRT-1550/ UC, UD, UG, UH, UK, UL, UO, UP 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 (K202210), cleared September 22, 2020 with the following modifications.

The provided document is a 510(k) Summary for a Magnetic Resonance Imaging (MRI) device, specifically the Vantage Orian 1.5T, MRT-1550, V7.0 with AiCE Reconstruction Processing Unit for MR. This document primarily describes modifications to an existing cleared device and asserts substantial equivalence to a predicate device.

The questions you've posed generally relate to the rigorous evaluation of a new AI-powered diagnostic device, particularly in terms of its clinical performance. This type of detailed clinical study information (e.g., sample size for test sets, data provenance, expert qualifications, HRMR studies, standalone performance with ground truth establishment) is typically found in the clinical validation section of a 510(k) submission for a novel AI/ML device that claims to provide diagnostic information or improve human reader performance.

However, in this specific 510(k) summary, the AiCE (Advanced Intelligent Clear-IQ Engine) is presented as a reconstruction processing unit and its update primarily involves "anatomical region expansion" and "noise estimation improvement." The summary emphasizes that the modifications do not change the indications for use or the intended use of the device. This suggests that the AiCE component, while employing advanced techniques (likely AI-based given the name), functions within the established performance parameters of an MRI reconstruction system and is not being submitted as a standalone diagnostic AI tool requiring a separate, extensive clinical performance study against specific diagnostic criteria.

Given this context, the document focuses on demonstrating that the modified MRI system as a whole remains safe and effective, and substantially equivalent to its predicate. The "acceptance criteria" and "study that proves the device meets the acceptance criteria" are therefore primarily framed around the performance of the MRI system itself and not a new diagnostic AI capability being validated against clinical outcomes or expert consensus on a disease.

Therefore, for many of your specific questions, the information is either not present in this type of 510(k) summary, or the question's premise (e.g., "effect size of how much human readers improve with AI vs without AI assistance") doesn't directly apply to the nature of this submission (a modification to a reconstruction engine for an MRI).

Let's break down what can be extracted or inferred from the provided text against your questions:

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

The document doesn't provide a clear, explicit table of acceptance criteria for diagnostic performance specific to the AiCE component's impact on diagnostic accuracy, because it's framed as an improvement to image reconstruction, not a new diagnostic AI tool.

Instead, the "performance parameters" mentioned are for the overall MRI system:

2. Sample size 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 in terms of patient cases for clinical performance evaluation. The "testing" section mentions "phantom images" and "volunteer clinical imaging," but does not specify the number of phantoms or volunteers, nor if these were used for a formal test set with ground truth. This is typical for a device primarily undergoing engineering/system validation rather than a clinical diagnostic study.
• Data Provenance: Not specified for any "volunteer clinical imaging." Phantom images are laboratory-based. The device manufacturer is Canon Medical Systems Corporation, Japan, with a U.S. agent.

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 applicable to this submission as it focuses on system performance and image reconstruction quality rather than a diagnostic AI algorithm requiring expert ground truth for clinical diagnostic accuracy studies. The document states, "When interpreted by a trained physician, these images yield information that can be useful in diagnosis," which points to the human reader's role in interpretation of the output, not the AI providing a diagnosis itself.

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

Not applicable, as no multi-reader adjudication process for diagnostic performance is described or implied.

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. This type of study would be performed for a new AI algorithm cleared for diagnostic assistance. The AiCE here is described as a "reconstruction processing unit" aiming to improve image quality characteristics (noise, homogeneity, distortion), which would indirectly benefit interpretation but isn't claimed to be a direct diagnostic aid that would undergo an MRMC study.

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

No standalone performance study for the AiCE as a diagnostic algorithm is mentioned. Its function is described as improving image quality, which is intrinsically tied to the overall MRI system.

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

Not applicable for a typical "ground truth" used in AI diagnostic performance studies. The "ground truth" for the reconstruction performance would be physical properties of phantoms or established MR physics principles for noise, homogeneity, and distortion measurements.

8. The sample size for the training set

Not present. As a component described as a "reconstruction processing unit" that likely employs AI/ML for image enhancement (implied by "AiCE," "noise estimation improvement"), it's reasonable to assume it has been developed using training data. However, for this type of 510(k) submission for a modification to an existing MRI system's reconstruction software, the details of the training data used for the AiCE component are not disclosed in the summary. The focus is on the safety and effectiveness of the modified system, not the isolated validation of a new AI diagnostic algorithm.

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

Not present. Similar to #8, these details are not provided in this regulatory summary.

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