Vantage Galan 3T, MRT-3020, V8.0 with AiCE Reconstruction Processing Unit for MR
K220192Canon Medical Systems Corporation · cleared 2022-04-08 · product code LNH · Radiology
Premarket evidence — what FDA accepted
source quote (p.5)
“The Vantage Galan (Model MRT-3020) is a 3 Tesla Magnetic Resonance Imaging (MRI) System, previously cleared under K212056. 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. LiverLine+: Machine Learning based detection technology for liver plane. Using 2D images as the input, two kind of MRCP scan plan (MRCP 3D and MRCP 2D) are automatically detected and set for the scan positioning ROIs. ProstateLine+: Machine Learning based detection technology for prostate plane. Using 3D images as the input, five planes (axial, coronal, sagittal, oblique axial, and oblique coronal) of the prostate are automatically detected and set for the scan positioning ROIs. W-SpineLine+: Machine Learning based detection technology for spine plane. Using 3D images of multiple stations covered whole spine region as the input, three planes (sagittal, coronal, and spinal disc planes) conforming to the curvature of the spine are automatically detected and set for the scan positioning ROIs.”
source quote (p.6)
“mART EXP: mART EXP is 3D method to reduce in-plane and through plane distortion artifact induced by susceptibility. Each slice is 3D phase-encoded to reduce distortion artifact induced by susceptibility in slice dimension. In addition, this application combines with VAT (View Angle Tilting) method for reducing in-plane distortion artifact induced by susceptibility. In the reconstruction, the data of each slice which is encoded in the slice direction is combined and corrected, and finally the images are registered as 2D multislice images like normal FSE2D. In addition, this application can be used in combination with Compressed SPEEDER application to reduce scan time. RDC DWI: RDC DWI is the method to reduce distortion in phase encoding direction for SEEPI2D sequence. The direction of distortion described above can be reversed by reversing the phase encoding polarity. Hence, the pair of the data that have reversed phase encoding polarity each other is acquired, and then the distortion in reconstructed images can be reduced by estimating displacements between them. In addition, this application can be used in combination with SPEEDER or Exsper. LiverLine+: Machine Learning based detection technology for liver plane. Using 2D images as the input, two kind of MRCP scan plan (MRCP 3D and MRCP 2D) are automatically detected and set for the scan positioning ROIs. The orientations and positions of the detected basic planes can be adjusted using functions provided in the Scan Plan window. ProstateLine+: Machine Learning based detection technology for prostate plane. Using 3D images as the input, five planes (axial, coronal, sagittal, oblique axial, and oblique coronal) of the prostate are automatically detected and set for the scan positioning ROIs. The orientations and positions of the detected planes can be adjusted using functions provided in the Scan Plan window. W-SpineLine+: Machine Learning based detection technology for spine plane. Using 3D images of multiple stations covered whole spine region as the input, three planes (sagittal, coronal, and spinal disc planes) conforming to the curvature of the spine are automatically detected and set for the scan positioning ROIs. The orientations and positions of the detected basic planes can be adjusted using functions provided in the Scan Plane window. It is also possible to label to detected spinal discs and can be adjusted using functions provided in the W-SpineLine window.”
Validation studies (8)
Standalone
sample size not stated
endpoints: worked as intended; images were of diagnostic quality; met predetermined acceptance criteria
standards: ANSI AAMI ES60601-1:2005 / (R)2012 and A1:2012, IEC60601-1-2 (2014), IEC60601-1-6 (2010), Amd.1 (2013), IEC60601-2-33 (2010), Amd.1 (2013), Amd.2 (2015), IEC60825-1 (2007, 2014), IEC62304 (2006), Amd.1 (2015), IEC62366-1 (2020), NEMA MS 1 (2008), NEMA MS 2 (2008), NEMA MS 3 (2008), NEMA MS 4 (2010), NEMA MS 5 (2010)
Bench
sample size not stated
endpoints: reduces artifacts caused by unfolding errors; scanning in those sequences can be conducted without problems
standards: ANSI AAMI ES60601-1:2005 / (R)2012 and A1:2012, IEC60601-1-2 (2014), IEC60601-1-6 (2010), Amd.1 (2013), IEC60601-2-33 (2010), Amd.1 (2013), Amd.2 (2015), IEC60825-1 (2007, 2014), IEC62304 (2006), Amd.1 (2015), IEC62366-1 (2020), NEMA MS 1 (2008), NEMA MS 2 (2008), NEMA MS 3 (2008), NEMA MS 4 (2010), NEMA MS 5 (2010)
Bench
sample size not stated
endpoints: scanning in those sequences can be conducted without problems
standards: ANSI AAMI ES60601-1:2005 / (R)2012 and A1:2012, IEC60601-1-2 (2014), IEC60601-1-6 (2010), Amd.1 (2013), IEC60601-2-33 (2010), Amd.1 (2013), Amd.2 (2015), IEC60825-1 (2007, 2014), IEC62304 (2006), Amd.1 (2015), IEC62366-1 (2020), NEMA MS 1 (2008), NEMA MS 2 (2008), NEMA MS 3 (2008), NEMA MS 4 (2010), NEMA MS 5 (2010)
Bench
sample size not stated
endpoints: reduce distortion artifacts
standards: ANSI AAMI ES60601-1:2005 / (R)2012 and A1:2012, IEC60601-1-2 (2014), IEC60601-1-6 (2010), Amd.1 (2013), IEC60601-2-33 (2010), Amd.1 (2013), Amd.2 (2015), IEC60825-1 (2007, 2014), IEC62304 (2006), Amd.1 (2015), IEC62366-1 (2020), NEMA MS 1 (2008), NEMA MS 2 (2008), NEMA MS 3 (2008), NEMA MS 4 (2010), NEMA MS 5 (2010)
Standalone
sample size not stated
endpoints: effective in reducing motion artifacts
standards: ANSI AAMI ES60601-1:2005 / (R)2012 and A1:2012, IEC60601-1-2 (2014), IEC60601-1-6 (2010), Amd.1 (2013), IEC60601-2-33 (2010), Amd.1 (2013), Amd.2 (2015), IEC60825-1 (2007, 2014), IEC62304 (2006), Amd.1 (2015), IEC62366-1 (2020), NEMA MS 1 (2008), NEMA MS 2 (2008), NEMA MS 3 (2008), NEMA MS 4 (2010), NEMA MS 5 (2010)
Bench
sample size not stated
endpoints: distortion in phase encoding direction was reduced
standards: ANSI AAMI ES60601-1:2005 / (R)2012 and A1:2012, IEC60601-1-2 (2014), IEC60601-1-6 (2010), Amd.1 (2013), IEC60601-2-33 (2010), Amd.1 (2013), Amd.2 (2015), IEC60825-1 (2007, 2014), IEC62304 (2006), Amd.1 (2015), IEC62366-1 (2020), NEMA MS 1 (2008), NEMA MS 2 (2008), NEMA MS 3 (2008), NEMA MS 4 (2010), NEMA MS 5 (2010)
Standalone
sample size not stated
endpoints: CBF values via pCASL met predetermined acceptance criteria
standards: ANSI AAMI ES60601-1:2005 / (R)2012 and A1:2012, IEC60601-1-2 (2014), IEC60601-1-6 (2010), Amd.1 (2013), IEC60601-2-33 (2010), Amd.1 (2013), Amd.2 (2015), IEC60825-1 (2007, 2014), IEC62304 (2006), Amd.1 (2015), IEC62366-1 (2020), NEMA MS 1 (2008), NEMA MS 2 (2008), NEMA MS 3 (2008), NEMA MS 4 (2010), NEMA MS 5 (2010)
Standalone
sample size not stated
endpoints: percentage of successful patient orientation detection and cases requiring no correction for successful patient anatomy position detection met predetermined acceptance criteria
standards: ANSI AAMI ES60601-1:2005 / (R)2012 and A1:2012, IEC60601-1-2 (2014), IEC60601-1-6 (2010), Amd.1 (2013), IEC60601-2-33 (2010), Amd.1 (2013), Amd.2 (2015), IEC60825-1 (2007, 2014), IEC62304 (2006), Amd.1 (2015), IEC62366-1 (2020), NEMA MS 1 (2008), NEMA MS 2 (2008), NEMA MS 3 (2008), NEMA MS 4 (2010), NEMA MS 5 (2010)
Reported performance (0 observations)
FDA source did not state a quantitative performance metric — non-reporting is itself the signal.
Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.
Predicate network
Postmarket — what happened after clearance
- re_clearance
The FDA AI/ML device list shows a newer 510(k) K243335 (decision 2025-01-07) from Canon Medical Systems Corporation for a matching device line ("Vantage Galan 3T, MRT-3020, V10.0 with AiCE Reconstruction Processing Unit for MR") — a new clearance for the same line is a change event.
first seen 2026-07-08 · k_number:K243335
- re_clearance
The FDA AI/ML device list shows a newer 510(k) K241496 (decision 2024-08-20) from Canon Medical Systems Corporation for a matching device line ("Vantage Galan 3T, MRT-3020, V10.0 with AiCE Reconstruction Processing Unit for MR") — a new clearance for the same line is a change event.
first seen 2026-07-08 · k_number:K241496
- re_clearance
The FDA AI/ML device list shows a newer 510(k) K230355 (decision 2023-08-30) from Canon Medical Systems Corporation for a matching device line ("Vantage Galan 3T, MRT-3020, V9.0 with AiCE Reconstruction Processing Unit for MR") — a new clearance for the same line is a change event.
first seen 2026-07-08 · k_number:K230355
- recall_reason_pattern
Software/algorithm-related recall in product code LNH (Philips North America, initiated 2026-04-14): "The potential for stiffness value errors when a specific range of image reconstruction parameters is used in combination with Resoundant's algorithm, leading to the reconstruction " Recalling firm is another firm in the same product code.
first seen 2026-07-08 · recall res_event_number:98779
- recall_reason_pattern
Software/algorithm-related recall in product code LNH (Philips North America, initiated 2025-12-03): "The potential for stiffness value errors when viewing exported MR Elastography (MRE) stiffness maps to viewer Picture Archiving and Communication System (PACS)." Recalling firm is another firm in the same product code.
first seen 2026-07-08 · recall res_event_number:98111
Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device). Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.
Reimbursement — how devices like this got paid
Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).