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Diffusion MRI acquisition for tractography : Diffusion encoding

Campbell, Jennifer S.W. ; Baete, Steven H. ; Cohen-Adad, Julien ; Tournier, J. Donald ; Szczepankiewicz, Filip LU orcid ; Beaulieu, Christian ; Baron, Corey A. ; Mani, Merry ; Setsompop, Kawin and Liao, Congyu , et al. (2024) p.103-121
Abstract

This is the first of three chapters (this chapter and Chapters 7 and 8) on diffusion MRI acquisition for tractography. For tractography, the acquisition is optimized for the estimation of fiber orientation. This chapter covers the creation of diffusion contrast. This is largely independent of the image encoding part of the MRI sequence, which is covered in Chapter 7. Unless explicitly stated, this chapter is focused on tractography of in vivo adult human brain. Considerations for tractography acquisition outside the in vivo adult human brain are covered in Chapters 8 and 32. This chapter first describes the creation of diffusion contrast by spin dephasing. It introduces the parameters that describe diffusion encoding: q, diffusion time,... (More)

This is the first of three chapters (this chapter and Chapters 7 and 8) on diffusion MRI acquisition for tractography. For tractography, the acquisition is optimized for the estimation of fiber orientation. This chapter covers the creation of diffusion contrast. This is largely independent of the image encoding part of the MRI sequence, which is covered in Chapter 7. Unless explicitly stated, this chapter is focused on tractography of in vivo adult human brain. Considerations for tractography acquisition outside the in vivo adult human brain are covered in Chapters 8 and 32. This chapter first describes the creation of diffusion contrast by spin dephasing. It introduces the parameters that describe diffusion encoding: q, diffusion time, and b, and describes signal representations for the diffusion encoded signal. Next, MRI hardware, including field strength, gradient coils, shim coils, and RF coils, is discussed in the context of diffusion encoding. Considerations for the choice of diffusion encoding parameters (b-values, diffusion encoding directions) for tractography are then detailed. The chapter then covers artifacts that can be mitigated by changes to the diffusion encoding itself, including artifacts caused by eddy currents, concomitant field gradients, gradient nonlinearity, system drift, incoherent motion, and vibration. Artifacts related to the rest of the sequence and postprocessing artifact reduction are covered later in Chapters 7 and 9. This chapter concludes with a brief introduction to diffusion sequence variations that can be achieved by varying the q-sampling and/or diffusion time, including nonlinear diffusion encoding.

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organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Diffusion contrast, Diffusion encoding, Diffusion MRI, Pulsed field gradient, Tractography
host publication
Handbook of Diffusion MR Tractography : Imaging Methods, Biophysical Models, Algorithms and Applications - Imaging Methods, Biophysical Models, Algorithms and Applications
pages
19 pages
publisher
Elsevier
external identifiers
  • scopus:85218370995
ISBN
9780128188958
9780128188941
DOI
10.1016/B978-0-12-818894-1.00001-X
language
English
LU publication?
yes
id
fa17bc2a-028a-4cde-957f-ca685e419766
date added to LUP
2025-06-05 10:26:00
date last changed
2025-07-03 13:59:05
@inbook{fa17bc2a-028a-4cde-957f-ca685e419766,
  abstract     = {{<p>This is the first of three chapters (this chapter and Chapters 7 and 8) on diffusion MRI acquisition for tractography. For tractography, the acquisition is optimized for the estimation of fiber orientation. This chapter covers the creation of diffusion contrast. This is largely independent of the image encoding part of the MRI sequence, which is covered in Chapter 7. Unless explicitly stated, this chapter is focused on tractography of in vivo adult human brain. Considerations for tractography acquisition outside the in vivo adult human brain are covered in Chapters 8 and 32. This chapter first describes the creation of diffusion contrast by spin dephasing. It introduces the parameters that describe diffusion encoding: q, diffusion time, and b, and describes signal representations for the diffusion encoded signal. Next, MRI hardware, including field strength, gradient coils, shim coils, and RF coils, is discussed in the context of diffusion encoding. Considerations for the choice of diffusion encoding parameters (b-values, diffusion encoding directions) for tractography are then detailed. The chapter then covers artifacts that can be mitigated by changes to the diffusion encoding itself, including artifacts caused by eddy currents, concomitant field gradients, gradient nonlinearity, system drift, incoherent motion, and vibration. Artifacts related to the rest of the sequence and postprocessing artifact reduction are covered later in Chapters 7 and 9. This chapter concludes with a brief introduction to diffusion sequence variations that can be achieved by varying the q-sampling and/or diffusion time, including nonlinear diffusion encoding.</p>}},
  author       = {{Campbell, Jennifer S.W. and Baete, Steven H. and Cohen-Adad, Julien and Tournier, J. Donald and Szczepankiewicz, Filip and Beaulieu, Christian and Baron, Corey A. and Mani, Merry and Setsompop, Kawin and Liao, Congyu and Tardif, Christine L. and Vos, Sjoerd B. and Yendiki, Anastasia and Leppert, Ilana R. and Fieremans, Els and Pike, G. Bruce}},
  booktitle    = {{Handbook of Diffusion MR Tractography : Imaging Methods, Biophysical Models, Algorithms and Applications}},
  isbn         = {{9780128188958}},
  keywords     = {{Diffusion contrast; Diffusion encoding; Diffusion MRI; Pulsed field gradient; Tractography}},
  language     = {{eng}},
  pages        = {{103--121}},
  publisher    = {{Elsevier}},
  title        = {{Diffusion MRI acquisition for tractography : Diffusion encoding}},
  url          = {{http://dx.doi.org/10.1016/B978-0-12-818894-1.00001-X}},
  doi          = {{10.1016/B978-0-12-818894-1.00001-X}},
  year         = {{2024}},
}