Cited by 1,537Advanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity StudiesAdvanced MRI Techniques and Applications

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Diffusion Tensor Imaging (DTI)-based White Matter Mapping in Brain Research: A Review

Assaf, Yaniv, Pasternak, Ofer·2008·Journal of Molecular Neuroscience

DOI 10.1007/s12031-007-0029-0

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Abstract

Diffusion tensor imaging (DTI) has become one of the most popular MRI techniques in brain research, as well as in clinical practice. The number of brain studies with DTI is growing steadily and, over the last decade, has produced more than 700 publications. Diffusion tensor imaging enables visualization and characterization of white matter fascicli in two and three dimensions. Since the introduction of this methodology in 1994, it has been used to study the white matter architecture and integrity of the normal and diseased brains (multiple sclerosis, stroke, aging, dementia, schizophrenia, etc.). Although it provided image contrast that was not available with routine MR techniques, unique information on white matter and 3D visualization of neuronal pathways, many questions were raised regarding the origin of the DTI signal. Diffusion tensor imaging is constantly validated, challenged, and developed in terms of acquisition scheme, image processing, analysis, and interpretation. While DTI offers a powerful tool to study and visualize white matter, it suffers from inherent artifacts and limitations. The partial volume effect and the inability of the model to cope with non-Gaussian diffusion are its two main drawbacks. Nevertheless, when combined with functional brain mapping, DTI provides an efficient tool for comprehensive, noninvasive, functional anatomy mapping of the human brain. This review summarizes the development of DTI in the last decade with respect to the specificity…

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MR diffusion tensor spectroscopy and imaging
Basser, P. J., Mattiello, J., & LeBihan, D. (1994) · Biophysical Journal · doi:10.1016/s0006-3495(94)80775-1 · Cited by 5,970
The basis of anisotropic water diffusion in the nervous system—A technical review.
Beaulieu, C. (2002) · NMR in Biomedicine · doi:10.1002/nbm.782 · Cited by 4,628
Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI
Basser, P. J., & Pierpaoli, C. (1996) · Journal of Magnetic Resonance, Series B · doi:10.1006/jmrb.1996.0086 · Cited by 4,306
Principles of Nuclear Magnetic Resonance Microscopy
Callaghan, P. T. (1991) · doi:10.1093/oso/9780198539445.001.0001 · Cited by 3,614
Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging
Mori, S., Crain, B. J., Chacko, V. P., & van Zijl, P. C. M. (1999) · Annals of Neurology · doi:10.1002/1531-8249(199902)45:2 · Cited by 3,513
Diffusion tensor MR imaging of the human brain
Pierpaoli, C., Jezzard, P., Basser, P. J., Barnett, A., & Di Chiro, G. (1996) · Radiology · doi:10.1148/radiology.201.3.8939209 · Cited by 2,664
Diffusional kurtosis imaging: the quantification of non‐gaussian water diffusion by means of magnetic resonance imaging
Jensen, J. H., Helpern, J. A., Ramani, A., Lu, H., & Kaczynski, K. (2005) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20508 · Cited by 2,488
American Journal of Neuroradiology
(2020) · American Journal of Neuroradiology · doi:10.3174/ajnr · Cited by 2,468
Toward a quantitative assessment of diffusion anisotropy
Pierpaoli, C. M., & Basser, P. J. (1996) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910360612 · Cited by 2,392
Q-ball imaging
Tuch, D. S. (2004) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20279 · Cited by 1,880

Show all 96 references

Research works printed but not linked: 3

Basser, P. J., Pajevic, S., Pierpaoli, C., Duda, J., & Aldroubi, A. (2000). In vivo fiber tractography using DT-MRI data. Magnetic Resonance in Medicine, 44, 625–632. · DOI
Pasternak, O., Sochen, N., & Assaf, Y. (2004). Separation of white matter fascicles from diffusion MRI using -functional regularization. Proceedings of the International Society for Magnetic Resonance in Medicine, 12, 1227.
Pasternak, O., Sochen, N., & Assaf, Y. (2006). PDE based estimation and regularization of multiple diffusion tensor fields. In J. Weickert & H. Hagen (Eds.), Visualization and image processing of tensor fields. Berlin: Springer.

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Authors: Assaf, Y., & Pasternak, O.
Affiliations: Tel Aviv University (IL)
Corresponding author: Assaf, Yaniv
ORCID: Assaf, Yaniv
Pasternak, Ofer
Venue: Journal of Molecular Neuroscience
Publisher: Springer Science and Business Media LLC
Published: 2007-09-27
Volume: 34
Issue: 1
Pages: 51-61
ISSN: 0895-8696 (ISSN-L)
1559-1166
DOI: 10.1007/s12031-007-0029-0
OpenAlex: W1997222702
Cited by: 1,537
References: 96
Citations by year: 2026: 50 · 2025: 113 · 2024: 94 · 2023: 93 · 2022: 96 · 2021: 138 · 2020: 101 · 2019: 102 · 2018: 85 · 2017: 95 · 2016: 86 · 2015: 90 · 2014: 91 · 2013: 71 · 2012: 64
FWCI: 3.82
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Journal of Molecular Neuroscience (publishedVersion)
PubMed (publishedVersion)
ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
Topics: Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Keywords: diffusion tensor imaging, partial volume effect, non-Gaussian diffusion, functional brain mapping, white matter integrity, multiple sclerosis, stroke, dementia, schizophrenia, brain aging
MeSH terms: Brain, Brain Diseases, Brain Mapping, Humans, Image Processing, Computer-Assisted, Nerve Fibers, Myelinated, Neural Pathways, Predictive Value of Tests, Reproducibility of Results, Artifacts, Diffusion Magnetic Resonance Imaging

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Diffusion Tensor Imaging (DTI)-based White Matter Mapping in Brain Research: A Review

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