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Vantage Galan 3T, MRT-3020, V10.0 with AiCE Reconstruction Processing Unit for MR

Canon Medical Systems Corporation • Radiology • 08/20/2024

510(k)IEC 62304 Class B
FDA Summary PDF

Device Purpose

The Vantage Galan 3T, MRT-3020, V10.0 is a 3 Tesla MRI system that generates diagnostic images of human anatomy by detecting NMR signals, with this version introducing hardware enhancements such as a new magnet, gradient coil, and a real-time processing platform. Key software advancements include 4D Flow for blood flow visualization and quantification, Zoom DWI for reduced-FOV diffusion imaging with artifact suppression, and 3D-QALAS for quantitative multi-parametric mapping, all aimed at enhancing diagnostic capabilities and image quality.

Summary

The Vantage Galan 3T (Model MRT-3020) is a 3 Tesla Magnetic Resonance Imaging (MRI) system designed for diagnostic imaging. Its fundamental purpose is to acquire and display cross-sectional (transaxial, coronal, sagittal) and oblique images of anatomical structures within the head or body, utilizing the principles of nuclear magnetic resonance (NMR). The system detects signals based on proton density, T1 and T2 relaxation times, flow dynamics, and chemical shift to generate images that, when interpreted by a physician, aid in diagnosis. It also supports non-contrast enhanced imaging techniques like Magnetic Resonance Angiography (MRA), and contrast agents may be used depending on the region of interest. This V10.0 version introduces several key hardware and software enhancements, building upon its AiCE Reconstruction Processing Unit. Hardware updates include a new in-house magnet, a new gradient coil, and a 'Real-time Platform' architecture with a Real-time Manager (RTM) for improved system stability and high-speed processing. Software modifications bring new functionalities: '4D Flow' for visualizing blood flow conditions and enabling quantitative analysis (streamline, path line, velocity), which requires external analytical software; 'Zoom DWI' for diffusion-weighted imaging with a smaller field of view achieved through selective excitation and outer volume suppression (OVS) to reduce distortion and aliasing artifacts; and '3D-QALAS,' a scan technique using an interleaved Look-Locker acquisition sequence with T2 preparation and IR pulses (FFE3D) for quantitative analysis, also requiring external analytical software. An uninterruptible power supply kit has been added as an accessory to protect system storage, and testing confirmed the effectiveness of these new features in phantom and volunteer studies.

AI Regulatory Concerns

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Keywords

MRI3 Tesla4D FlowZoom DWI3D-QALASGradient CoilReal-time PlatformQuantitative AnalysisOuter Volume SuppressionBlood Flow Visualization

Device Metadata

Submission Number
K241496
Company
Canon Medical Systems Corporation
Panel
Radiology
Product Code
N/A
Data Type
Images
Clinical Function
Assessment
AI Function
Generation
AI Subclass
acquisition guidance|image enhancement

Relevant Clinical Questions

  • Q1. How does the new 'Real-time Platform' architecture specifically improve processing speed and system stability compared to the V9.0 system, and what are the quantifiable metrics for these improvements?; For the '4D Flow' application, what are the specific requirements and compatibility considerations for the 'external analytical software' needed for quantitative analysis, and how validated is the data transfer process?; Regarding 'Zoom DWI,' what is the typical reduction in field of view (FOV) achievable, and how significantly are distortion and aliasing artifacts mitigated in challenging anatomical regions?; With '3D-QALAS,' what range of T1 and T2 values can be accurately quantified, and how does its performance (accuracy, precision, scan time) compare to established single-parameter quantitative MRI techniques?; What are the specific design changes in the new in-house magnet and gradient coil, and how do these changes contribute to image quality or the capabilities of the new software applications (4D Flow, Zoom DWI, 3D-QALAS)?

Risk Classification

ESL Analysis
FDA Device ClassII

FDA Class II via 510(k) pathway; IEC 62304 Class B (software safety classification); Post-§524B but no clear network capability detected

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Cybersecurity Evidence

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.

Cyber Score10/100
SBOM Evidence⚠ Not in summary - likely in full submission per §524B
Cyber Risk Assessment⚠ Not in summary - likely in full submission per §524B
Postmarket Plan⚠ Not in summary - likely in full submission per §524B
§524B ApplicableYes

Supply Chain BOM Evidence

Based on the CycloneDX / OWASP ECMA-424 xBOM ecosystem. Detection is from the AI-generated summary.

SBOMSoftware Bill of Materials
- Not detected
ML-BOMMachine Learning Bill of Materials
- Not detected
SaaSBOMSoftware-as-a-Service Bill of Materials(platform)
✓ Detected
HBOMHardware Bill of Materials(hardware)
✓ Detected
CBOMCryptography Bill of Materials
- Not detected
VDR/VEXVulnerability Disclosure Report / Vulnerability Exploitability eXchange
- Not detected
OBOMOperations Bill of Materials
- Not detected

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 SaaSBOM, HBOM detected in AI-generated device summary.

• SBOM not mentioned in AI-generated device summary. Under §524B (effective Oct 2023), cyber devices must provide a SBOM.

• Cybersecurity risk assessment not referenced in AI-generated device summary. FDA cybersecurity guidance (2023) expects this for cyber devices.

• Postmarket cybersecurity monitoring plan not clearly documented in AI-generated device summary.

• Not detected in AI-generated device summary: SBOM, ML-BOM, CBOM, VDR/VEX, OBOM. These may be present in the full FDA submission.

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Vantage Galan 3T, MRT-3020, V10.0 with AiCE Reconstruction Processing Unit for MR - Canon Medical Systems Corporation | ESL FDA AI Device Intelligence