Cited by 18Advanced Neuroimaging Techniques and ApplicationsAdvanced MRI Techniques and ApplicationsFunctional Brain Connectivity Studies

Choosing the polarity of the phase-encoding direction in diffusion MRI: does it matter for group analysis?

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Kennis, M., van Rooij, S.J.H., Kahn, R.S., Geuze, E., Leemans, A.·2016·NeuroImage: Clinical

Abstract

Notorious for degrading diffusion MRI data quality are so-called susceptibility-induced off-resonance fields, which cause non-linear geometric image deformations. While acquiring additional data to correct for these distortions alleviates the adverse effects of this artifact drastically - e.g., by reversing the polarity of the phase-encoding (PE) direction - this strategy is often not an option due to scan time constraints. Especially in a clinical context, where patient comfort and safety are of paramount importance, acquisition specifications are preferred that minimize scan time, typically resulting in data obtained with only one PE direction. In this work, we investigated whether choosing a different polarity of the PE direction would affect the outcome of a specific clinical research study. To address this methodological question, fractional anisotropy (FA) estimates of FreeSurfer brain regions were obtained in civilian and combat controls, remitted posttraumatic stress disorder (PTSD) patients, and persistent PTSD patients before and after trauma-focused therapy and were compared between diffusion MRI data sets acquired with different polarities of the PE direction (posterior-to-anterior, PA and anterior-to-posterior, AP). Our results demonstrate that regional FA estimates differ on average in the order of 5% between AP and PA PE data. In addition, when comparing FA estimates between different subject groups for specific cingulum subdivisions, the conclusions for AP and PA PE data were not in agreement. These findings increase our understanding of how one of the most pronounced data artifacts in diffusion MRI can impact group analyses and should encourage users to be more cautious when interpreting and reporting study outcomes derived from data acquired along a single PE direction.

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  • Some dMRI studies have added additional cingulum subdivisions.

    “Furthermore, some dMRI studies have added additional cingulum subdivisions (Kennis et al., 2016; Metzler-Baddeley et al., 2012b; Whitford et al., 2014).”

    From The cingulum bundle: Anatomy, function, and dysfunction (2018) · cites this paper as Kennis et al., 2016

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Research works printed but not linked: 40

  1. Abe O. Yamasue H. Kasai K. Yamada H. Aoki S. Iwanami A. Ohtani T. Masutani Y. Kato N. Ohtomo K. Voxel-based diffusion tensor analysis reveals aberrant anterior cingulum integrity in posttraumatic stress disorder due to terrorism Psychiatry Res. Neuroimaging 146 3 2006 231 242 16545552
  2. Andersson J.L.R. Sotiropoulos S.N. An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging NeuroImage 2015 PMC4692656 26481672
  3. Andersson J.L.R. Skare S. Ashburner J. How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging NeuroImage 20 2 2003 870 888 14568458
  4. Basser P.J. Mattiello J. LeBihan D. MR diffusion tensor spectroscopy and imaging Biophys. J. 66 1 1994 259 267 8130344 PMC1275686
  5. Bhushan C. Joshi A.A. Leahy R.M. Haldar J.P. Improved B0-distortion correction in diffusion MRI using interlaced q-space sampling and constrained reconstruction Magn. Reson. Med. 72 5 2013 1218 1232 24464424 PMC4017008
  6. Büchel C. Raedler T. Sommer M. Sach M. Weiller C. Koch M.A. White matter asymmetry in the human brain: a diffusion tensor MRI study Cereb. Cortex 14 9 2004 945 951 15115737
  7. Chang L.C. Koay C.G. Pierpaoli C. Basser P.J. Variance of estimated DTI-derived parameters via first-order perturbation methods Magn. Reson. Med. 57 1 2007 141 149 17191228
  8. Chen B. Guo H. Song A.W. Correction for direction-dependent distortions in diffusion tensor imaging using matched magnetic field maps NeuroImage 30 1 2006 121 129 16242966
  9. Daniels J.K. Lamke J. Gaebler M. Walter H. Scheel M. White matter integrity and its relationship to PTSD and childhood trauma — a systematic review and meta-analysis Depress. Anxiety 30 3 2013 207 216 23319445
  10. Fischl B. FreeSurfer NeuroImage 62 2 2012 774 781 22248573 PMC3685476
  11. Fischl B. Salat D.H. Busa E. Albert M. Dieterich M. Haselgrove C. Van Der Kouwe A. Killiany R. Kennedy D. Klaveness S. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain Neuron 33 3 2002 341 355 11832223
  12. Gallichan D. Andersson J.L.R. Jenkinson M. Robson M.D. Miller K.L. Reducing distortions in diffusion-weighted echo planar imaging with a dual-echo blip-reversed sequence Magn. Reson. Med. 64 2 2010 382 390 20665782
  13. Glover G.H. Mueller B.A. Turner J.A. Van Erp T.G.M. Liu T.T. Greve D.N. Voyvodic J.T. Rasmussen J. Brown G.G. Keator D.B. Function biomedical informatics research network recommendations for prospective multicenter functional MRI studies J. Magn. Reson. Imaging 36 1 2012 39 54 22314879 PMC3349791
  14. Irfanoglu M.O. Walker L. Sarlls J. Marenco S. Pierpaoli C. Effects of image distortions originating from susceptibility variations and concomitant fields on diffusion MRI tractography results NeuroImage 61 1 2012 275 288 22401760 PMC3653420
  15. Irfanoglu M.O. Modi P. Nayak A. Hutchinson E.B. Sarlls J. Pierpaoli C. DR-BUDDI (diffeomorphic registration for blip-up blip-down diffusion imaging) method for correcting echo planar imaging distortions NeuroImage 106 0 2015 284 299 25433212 PMC4286283
  16. Jezzard P. Balaban R.S. Correction for geometric distortion in echo planar images from B(o) field variations Magn. Reson. Med. 34 1 1995 65 73 7674900
  17. Jones D.K. The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: a Monte Carlo study Magn. Reson. Med. 51 4 2004 807 815 15065255
  18. Jones D.K. Leemans A. Diffusion tensor imaging Methods Mol. Biol. 711 2011 127 144 21279600
  19. Koay C.G. Chang L.-C. Pierpaoli C. Basser P.J. Error propagation framework for diffusion tensor imaging via diffusion tensor representations IEEE Trans. Med. Imaging 26 8 2007 1017 1034 17695123
  20. Leemans A. Jones D.K. The B-matrix must be rotated when correcting for subject motion in DTI data Magn. Reson. Med. 61 6 2009 1336 1349 19319973
  21. Leemans A. Jeurissen B. Sijbers J. Jones D. ExploreDTI: a graphical toolbox for processing, analyzing, and visualizing diffusion MRI data Proceedings of the 17th Annual Meeting of International Society for Magnetic Resonance in Medicine 2009 3537
  22. Menon V. Large-scale brain networks and psychopathology: a unifying triple network model Trends Cogn. Sci. 15 10 2011 483 506 21908230
  23. Morgan P.S. Bowtell R.W. McIntyre D.J.O. Worthington B.S. Correction of spatial distortion in EPI due to inhomogeneous static magnetic fields using the reversed gradient method J. Magn. Reson. Imaging 19 4 2004 499 507 15065175
  24. O'Hanlon E. Leemans A. Kelleher I. Clarke M.C. Roddy S. Coughlan H. Harley M. Amico F. Hoscheit M.J. Tiedt L. White matter differences among adolescents reporting psychotic experiences: a population-based diffusion magnetic resonance imaging study JAMA Psychiatry 72 7 2015 668 677 25923212
  25. Pajevic S. Basser P.J. Parametric and non-parametric statistical analysis of DT-MRI data J. Magn. Reson. 161 1 2003 1 14 12660106
  26. Pierpaoli C. Jezzard P. Basser P.J. Barnett A. Di Chiro G. Diffusion tensor MR imaging of the human brain Radiology 201 3 1996 637 648 8939209
  27. Reijmer Y.D. Fotiadis P. Martinez-Ramirez S. Salat D.H. Schultz A. Shoamanesh A. Ayres A.M. Vashkevich A. Rosas D. Schwab K. Structural network alterations and neurological dysfunction in cerebral amyloid angiopathy Brain J. Neurol. 138 Pt 1 2015 179 188 PMC4285191 25367025
  28. Ruthotto L. Kugel H. Olesch J. Fischer B. Modersitzki J. Burger M. Wolters C.H. Diffeomorphic susceptibility artifact correction of diffusion-weighted magnetic resonance images Phys. Med. Biol. 57 18 2012 5715 5731 22941943
  29. Smith S.M. Jenkinson M. Johansen-Berg H. Rueckert D. Nichols T.E. Mackay C.E. Watkins K.E. Ciccarelli O. Cader M.Z. Matthews P.M. Behrens T.E. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data NeuroImage 31 4 2006 1487 1505 16624579
  30. Tax C.M. Otte W.M. Viergever M.A. Dijkhuizen R.M. Leemans A. REKINDLE: robust extraction of kurtosis INDices with linear estimation Magn. Reson. Med. 73 2 2015 794 808 24687400
  31. Thiebaut de Schotten M. Ffytche D.H. Bizzi A. Dell'Acqu F. Alli M. Walshe M. Murray R. Williams S.C. Murphy D.G.M. Catani M. Atlasing location, asymmetry and inter-subject variability of white matter tracts in the human brain with MR diffusion tractography NeuroImage 54 1 2011 49 59 20682348
  32. Truong T. Chen N. Song A.W. Dynamic correction of artifacts due to susceptibility effects and time-varying eddy currents in diffusion tensor imaging NeuroImage 57 4 2011 1343 1347 21689763 PMC3138839
  33. Veraart J. Sijbers J. Sunaert S. Leemans A. Jeurissen B. Weighted linear least squares estimation of diffusion MRI parameters: strengths, limitations, and pitfalls NeuroImage 81 2013 335 346 23684865
  34. Verhoeven J.S. Rommel N. Prodi E. Leemans A. Zink I. Vandewalle E. Noens I. Wagemans J. Steyaert J. Boets B. Is there a common neuroanatomical substrate of language deficit between autism spectrum disorder and specific language impairment? Cereb. Cortex 22 10 2012 2263 2271 22047968
  35. Vos S.B. Tax C.M.W. Visser F. Luijten P.R. Leemans A. Froeling M. Importance of correcting for B0-drift-induced global signal decrease in diffusion MRI Int. Soc. Magn. Reson. Med. 2014 4460 26822700
  36. Wang H.C. Hsu J.L. Leemans A. Diffusion tensor imaging of vascular Parkinsonism: structural changes in cerebral white matter and the association with clinical severity Arch. Neurol. 69 10 2012 1340 1348 22825428
  37. Whitcher B. Tuch D.S. Wisco J.J. Sorensen A.G. Wang L. Using the wild bootstrap to quantify uncertainty in diffusion tensor imaging Hum. Brain Mapp. 29 3 2008 346 362 17455199 PMC6870960
  38. World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects JAMA - J. Am. Med. Assoc. 310 20 2013 2191 2194 24141714
  39. Wu M. Chang L.C. Walker L. Lemaitre H. Barnett A.S. Marenco S. Pierpaoli C. Comparison of EPI distortion correction methods in diffusion tensor MRI using a novel framework Med. Image Comput. Comput. Assisted Interv. 11 Pt 2 2008 321 329 PMC4819327 18982621
  40. Zhang L. Zhang Y. Li L. Li Z. Li W. Ma N. Hou C. Zhang Z. Zhang Z. Wang L. Different white matter abnormalities between the first-episode, treatment-naive patients with posttraumatic stress disorder and generalized anxiety disorder without comorbid conditions J. Affect. Disord. 133 1–2 2011 294 299 21497403

Cited by

Sorted by citations

Authors
Kennis, M., van Rooij, S. J. H., Kahn, R. S., Geuze, E., & Leemans, A.
Affiliations
University Medical Center Utrecht (NL)
Corresponding author
Kennis, M.
Venue
NeuroImage: Clinical
Publisher
Elsevier BV
Published
2016
Volume
11
Pages
539-547
ISSN
2213-1582 (ISSN-L)
OpenAlex
W2340730483
Cited by
18
References
5
Citations by year
2025: 2 · 2024: 3 · 2023: 2 · 2021: 5 · 2020: 2 · 2019: 1 · 2018: 2 · 2017: 1
FWCI
1.16
Type
journal article
Language
en
Open access
Locations
  • NeuroImage Clinical (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
Funders
  • Dutch Ministry of Defence
  • VIDI (639.072.411)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Keywords
phase-encoding direction, polarity, fractional anisotropy, post-traumatic stress disorder, cingulum, group analysis, trauma-focused psychotherapy
MeSH terms
Adult, Brain, Brain Mapping, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Stress Disorders, Post-Traumatic, Veterans, Trauma Severity Indices, Artifacts, Anisotropy, Diffusion Magnetic Resonance Imaging, Young Adult, White Matter

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