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Rigid‐body motion correction of the liver in image reconstruction for golden‐angle stack‐of‐stars DCE MRI
Author(s) -
Johansson Adam,
Balter James,
Cao Yue
Publication year - 2018
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.26782
Subject(s) - artificial intelligence , computer vision , magnetic resonance imaging , motion (physics) , image registration , contrast (vision) , computer science , dynamic contrast enhanced mri , nuclear medicine , image (mathematics) , medicine , radiology
Purpose Respiratory motion can affect pharmacokinetic perfusion parameters quantified from liver dynamic contrast‐enhanced MRI. Image registration can be used to align dynamic images after reconstruction. However, intra‐image motion blur remains after alignment and can alter the shape of contrast‐agent uptake curves. We introduce a method to correct for inter‐ and intra‐image motion during image reconstruction. Methods Sixteen liver dynamic contrast‐enhanced MRI examinations of nine subjects were performed using a golden‐angle stack‐of‐stars sequence. For each examination, an image time series with high temporal resolution but severe streak artifacts was reconstructed. Images were aligned using region‐limited rigid image registration within a region of interest covering the liver. The transformations resulting from alignment were used to correct raw data for motion by modulating and rotating acquired lines in k‐space. The corrected data were then reconstructed using view sharing. Results Portal‐venous input functions extracted from motion‐corrected images had significantly greater peak signal enhancements (mean increase: 16%, t‐test, P < 0.001) than those from images aligned using image registration after reconstruction. In addition, portal‐venous perfusion maps estimated from motion‐corrected images showed fewer artifacts close to the edge of the liver. Conclusions Motion‐corrected image reconstruction restores uptake curves distorted by motion. Motion correction also reduces motion artifacts in estimated perfusion parameter maps. Magn Reson Med 79:1345–1353, 2018. © 2017 International Society for Magnetic Resonance in Medicine.