scholarly journals EPI Distortion Correction is Easy and Useful, and You Should Use It: A case study with toddler data

2020 ◽  
Author(s):  
Vinai Roopchansingh ◽  
Jerry J. French ◽  
Dylan M. Nielson ◽  
Richard C. Reynolds ◽  
Daniel R. Glen ◽  
...  

AbstractTask, resting state, and diffusion MRI data are usually acquired from subjects using echo-planar based imaging techniques. These techniques are highly susceptible to B0 homogeneity effects that result in geometric distortions in the reconstructed images. As researchers work to link the information from these scans back to various developmental stages, or to conditions and diseases in specific regions or structures of the brain, it becomes critical to have accurate correspondence between more geometrically distorted echo-planar images and less geometrically distorted anatomical images. A variety of techniques and tools have been developed to improve this correspondence. The basic premise behind most techniques used to mitigate geometric distortion is to acquire enough information to inform software tools how echo-planar images are warped, then have them undo that warping. Here, we investigate the application of two common methods: B0 correction, and reverse-polarity phase-encoding (or reverse blip) correction. We implement each of these in two separate, widely used software packages in the field: AFNI and FSL. We find that using either technique in either software package results in reduced geometric distortions in the EPI images. We discuss the practical implementations of these methods (e.g., increased scan and processing time). In general, however, both methods possess readily available data acquisition schemes, and are highly efficient to include in processing streams. Due to the overall data improvement, we strongly recommend that researchers include one of these methods in their standard protocols.

2016 ◽  
Vol 34 (6) ◽  
pp. 832-838 ◽  
Author(s):  
Andrew D. Davis ◽  
Michael D. Noseworthy

2009 ◽  
Vol 61 (4) ◽  
pp. 994-1000 ◽  
Author(s):  
Iulius Dragonu ◽  
Baudouin Denis de Senneville ◽  
Bruno Quesson ◽  
Chrit Moonen ◽  
Mario Ries

Author(s):  
Renaud Hedouin ◽  
Olivier Commowick ◽  
Maxime Taquet ◽  
Elise Bannier ◽  
Benoit Scherrer ◽  
...  

2014 ◽  
Vol 32 (5) ◽  
pp. 590-593 ◽  
Author(s):  
Neil Gelman ◽  
Ally Silavi ◽  
Udunna Anazodo

2021 ◽  
Author(s):  
Nuwan D. Nanayakkara ◽  
Stephen R. Arnott ◽  
Christopher J.M. Scott ◽  
Igor Solovey ◽  
Shuai Liang ◽  
...  

Magnetic resonance imaging (MRI) scanner-specific geometric distortions may contribute to scanner induced variability and decrease volumetric measurement precision for multi-site studies. The purpose of this study was to determine whether geometric distortion correction increases the precision of brain volumetric measurements in a multi-site multi-scanner study. Geometric distortion variation was quantified over a one-year period at 10 sites using the distortion fields estimated from monthly 3D T1-weighted MRI geometrical phantom scans. The variability of volume and distance measurements were quantified using synthetic volumes and a standard quantitative MRI (qMRI) phantom. The effects of geometric distortion corrections on MRI derived volumetric measurements of the human brain were assessed in two subjects scanned on each of the 10 MRI scanners and in 150 subjects with cerebrovascaular disease (CVD) acquired across imaging sites. Geometric distortions were found to vary substantially between different MRI scanners but were relatively stable on each scanner over a one-year interval. Geometric distortions varied spatially, increasing in severity with distance from the magnet isocenter. In measurements made with the qMRI phantom, the geometric distortion correction decreased the standard deviation of volumetric assessments by 35% and distance measurements by 42%. The average coefficient of variance decreased by 16% in gray matter and white matter volume estimates in the two subjects scanned on the 10 MRI scanners. Geometric distortion correction using an up-to-date correction field is recommended to increase precision in volumetric measurements made from MRI images.


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