Vantage Galan 3T, MRT-3020, V8.0 with AiCE Reconstruction Processing Unit for MR
Canon Medical Systems Corporation • Radiology • 04/08/2022
Device Purpose
The Vantage Galan 3T, MRT-3020, V8.0, is a 3 Tesla Magnetic Resonance Imaging system designed to acquire high-resolution diagnostic images of the head and body by utilizing nuclear magnetic resonance principles and advanced image processing via its AiCE Reconstruction Processing Unit. This updated system introduces a suite of software innovations including novel artifact suppression techniques (mART EXP, RDC DWI), non-contrast arterial spin labeling (pCASL) for perfusion imaging, iterative motion correction (IMC), and machine learning-driven automated scan planning tools to enhance image quality, streamline workflows, and expand clinical applications.
Summary
The Canon Vantage Galan 3T, MRT-3020, V8.0, is a 3 Tesla Magnetic Resonance Imaging (MRI) system designed for diagnostic imaging. It produces cross-sectional, transaxial, coronal, sagittal, and oblique images of anatomical structures throughout the head and body by leveraging nuclear magnetic resonance (NMR) principles, specifically detecting signals from proton density, T1 and T2 relaxation times, flow dynamics, and chemical shifts. The system is capable of both non-contrast enhanced imaging, such as Magnetic Resonance Angiography (MRA), and imaging with contrast agents, providing physicians with critical information for diagnosis. This V8.0 iteration builds upon previous versions, incorporating the AiCE Reconstruction Processing Unit for enhanced image processing. The V8.0 software introduces significant advancements aimed at improving image quality and workflow efficiency. These include new artifact suppression techniques such as mART EXP, a 3D method to reduce susceptibility-induced distortion, and RDC DWI, which minimizes distortion in diffusion-weighted imaging. For non-contrast perfusion imaging, pseudo-continuous Arterial Spin Labeling (pCASL) is implemented. Iterative Motion Correction (IMC) reduces motion artifacts in brain and C-spine imaging. Furthermore, a suite of machine learning-based automated scan planning tools (SureVOI Liver, LiverLine+, ProstateLine+, W-SpineLine+) streamlines exam setup for liver, prostate, and whole spine imaging. Testing confirmed these features perform as intended, with mART EXP showing improved distortion reduction, IMC effectively reducing motion artifacts, RDC DWI reducing DWI distortion, pCASL yielding acceptable CBF values, and automated planning tools providing diagnostic quality images and meeting acceptance criteria. Accessory enhancements include a ceiling camera for patient positioning and tablet applications for remote exam management.
AI Regulatory Concerns
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Keywords
Device Metadata
Relevant Clinical Questions
- Q1. How does the AiCE Reconstruction Processing Unit in V8.0 specifically enhance image quality (e.g., SNR, spatial resolution, contrast-to-noise ratio) for the newly introduced sequences like pCASL and those utilizing mART EXP, compared to reconstructions without AiCE?; What are the quantitative improvements in scan time reduction when mART EXP is combined with Compressed SPEEDER, and how does this combination impact image quality and diagnostic confidence across various anatomies?; For the machine learning-based automated scan planning tools (SureVOI Liver, LiverLine+, ProstateLine+, W-SpineLine+), what is their performance robustness across diverse patient demographics, body habitus, and in the presence of significant anatomical pathologies or prior surgical alterations?; What is the comparative efficacy of Iterative Motion Correction (IMC) for rigid versus non-rigid motion, particularly its limits in correcting complex non-rigid motion in anatomical regions beyond the C-spine where it's explicitly validated for such?; How do the cerebral blood flow (CBF) values obtained using pCASL on this system correlate with established quantitative perfusion techniques (e.g., DSC-MRI or Xenon CT) in healthy volunteers and patient populations with cerebrovascular disease?
Risk Classification
ESL AnalysisFDA Class II via 510(k) pathway; IEC 62304 Class B (software safety classification); Authorized before §524B enforcement
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Powered by SBOMator™Based on AI-generated device summaries, not the full FDA submission. Items not detected here may still be present in the complete submission package.
Supply Chain BOM Evidence
Based on the CycloneDX / OWASP ECMA-424 xBOM ecosystem. Detection is from the AI-generated summary.
Analysis:
• Analysis is based on the AI-generated device summary, not the full FDA submission package. Click "Analyze Full FDA PDF" below to scan the actual submission document.
• Evidence of ML-BOM, SaaSBOM, HBOM detected in AI-generated device summary.
• This device was authorized before §524B took effect. Cybersecurity evidence requirements were less prescriptive at the time.
• Postmarket cybersecurity monitoring plan not clearly documented in AI-generated device summary.
• Not detected in AI-generated device summary: SBOM, CBOM, VDR/VEX, OBOM. These may be present in the full FDA submission.
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