Retrospective head motion correction approaches for diffusion tensor imaging: Effects of preprocessing choices on biases and reproducibility of scalar diffusion metrics

Journal of Magnetic Resonance Imaging

Volumn 43, Issue 1, 2016, Pages 99-106

  Kreilkamp, Barbara A K ^a,b   Zacà, Domenico ^a   Papinutto, Nico ^c   Jovicich, Jorge ^a  

^a UNIVERSITY OF TRENTO   (Italy)

^b UNIVERSITY OF LIVERPOOL   (United Kingdom)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Diffusion magnetic resonance imaging; Diffusion tensor; DTIPrep; FSL; Head motion correction; Reproducibility

Indexed keywords

ARCUATE FASCICULUS; ARTICLE; ARTIFACT REDUCTION; AXIAL DIFFUSIVITY; CINGULATE GYRUS; CORPUS CALLOSUM; DIFFUSION TENSOR IMAGING; FRACTIONAL ANISOTROPY; HEAD MOVEMENT; HUMAN; MEAN DIFFUSIVITY; NEUROIMAGING; NORMAL HUMAN; NUCLEAR MAGNETIC RESONANCE SCANNER; PHYSICAL PARAMETERS; PRIORITY JOURNAL; RADIAL DIFFUSIVITY; REPRODUCIBILITY; TEST RETEST RELIABILITY; WHITE MATTER; ADULT; ALGORITHM; ANATOMY AND HISTOLOGY; ARTIFACT; BRAIN; COMPUTER ASSISTED DIAGNOSIS; IMAGE ENHANCEMENT; MALE; MOTION; PROCEDURES; RETROSPECTIVE STUDY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ADULT; ALGORITHMS; ARTIFACTS; BRAIN; DIFFUSION TENSOR IMAGING; HEAD MOVEMENTS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MALE; MOTION; REPRODUCIBILITY OF RESULTS; RETROSPECTIVE STUDIES; SENSITIVITY AND SPECIFICITY;

EID: 84955727320     PISSN: 10531807     EISSN: 15222586     Source Type: Journal    
DOI: 10.1002/jmri.24965     Document Type: Article

References (23)

1. Aksoy M, Liu C, Moseley ME, Bammer R,. Single-step nonlinear diffusion tensor estimation in the presence of microscopic and macroscopic motion. Magn Reson Med 2008; 59: 1138-1150.
2. Yendiki A, Koldewyn K, Kakunoori S, Kanwisher N, Fischl B,. Spurious group differences due to head motion in a diffusion MRI study. NeuroImage 2014; 88: 79-90.
3. Jovicich J, Marizzoni M, Bosch B, et al., Multisite longitudinal reliability of tract-based spatial statistics in diffusion tensor imaging of healthy elderly subjects. NeuroImage 2014; 12.
4. Maclaren J, Herbst M, Speck O, Zaitsev M,. Prospective motion correction in brain imaging: a review. Magn Reson Med. 2013; 69: 621-636.
5. Alhamud A, Taylor PA, Laughton B, van der Kouwe AJ, Meintjes EM,. Motion artifact reduction in pediatric diffusion tensor imaging using fast prospective correction. J Magn Reson Imaging 2015; 41: 1353-1341.
6. Rohde GK, Barnett AS, Basser PJ, Marenco S, Pierpaoli C,. Comprehensive approach for correction of motion and distortion in diffusion-weighted MRI. Magn Reson Med 2004; 51: 103-114.
7. Leemans A, Jones DK,. The B-matrix must be rotated when correcting for subject motion in DTI data. Magn Reson Med 2009; 61: 1336-1349.
8. Pfefferbaum A, Sullivan E, Hedehus M, Lim KO, Adalsteinsson E, Moseley M,. Age-related decline in brain white matter anisotropy measured with spatially corrected echo-planar diffusion tensor imaging. Magn Reson Med 2000; 44: 259-268.
9. Rohde G, Barnett AS, Basser PJ, Pierpaoli C,. Estimating intensity variance due to noise in registered images-applications to DTI MRI. NeuroImaging 2005; 26.
10. Chao T, Chou M, Yang P, Chung H, Wu M,. Effects of interpolation methods in spatial normalization of diffusion tensor imaging data on group comparison of fractional anisotropy. Magn Reson Med 2009; 27: 5.
11. Basser J, Pierpaoli C,. Microstructural and physiological features of tissues elucidated by quantitative diffusion tensor MRI. J Magn Reson B 1996; 111: 209-219.
12. Song SK, Sun SW, Ramsbottom MJ, Chang C, Russell J, Cross AH,. Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. NeuroImage 2002; 17: 1429-1436.
13. Wheeler-Kingshott C, Cercignani M,. About »axial» and »radial» diffusivities. Magn Reson Med 2009; 61: 1255-1260.
14. Liu X, Yang Y, Sun J, et al., Reproducibility of diffusion tensor imaging in normal subjects: an evaluation of different gradient sampling schemes and registration algorithm. Neuroradiology 2014; 56: 497-510.
15. Ersoz A, Arpinar VE, Dreyer S, Muftuler LT,. Quantitative analysis of the efficacy of gradient table correction on improving the accuracy of fiber tractography. Magn Reson Med 2014; 72: 227-236.
16. Papinutto ND, Maule F, Jovicich J,. Reproducibility and biases in high field brain diffusion MRI An evaluation of acquisition and analysis variables. Magn Reson Imaging 2013; 31: 827-839.
17. Oguz I, Farzinfar M, Matsui J, et al., DTIPrep: quality control of diffusion-weighted images. Front Neuroinform 2014; 8: 4.
18. Liu Z, Wang Y, Gerig G, et al., Quality control of diffusion weighted images. Proc SPIE 2010; 7628.
19. Smith SM, Jenkinson M, Johansen-Berg H, et al., Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. NeuroImage 2006; 31: 1487-1505.
20. Mori S, Wakana S, Nagae-Poetscher LM, van Zijl PCM,. MRI atlas of human white matter. Amsterdam: Elsevier; 2005.
21. Cox R,. AFNI: Software for analysis and visualisation of functional magnetic resonance neuroimages. Comput Biomed Res 1996; 29: 162-173.
22. Farrher E, Kaffanke J, Celik AA, Stöcker T, Grinberg F, Shah NJ,. Novel multisection design of anisotropic diffusion phantoms. Magn Reson Imaging 2012; 30: 518-526.
23. Hubbard PL, Zhou F-L, Eichhorn SJ, Parker GJM,. Biomimetic phantom for the validation of diffusion magnetic resonance imaging. Magn Reson Med 2014 [Epub ahead of print].