Diffusion tensor imaging of the brain

Alexander, Andrew L.; Lee, Jee Eun; Lazar, Mariana; Field, Aaron S.

doi:10.1016/j.nurt.2007.05.011

Cited by 2,747Advanced Neuroimaging Techniques and ApplicationsAdvanced MRI Techniques and ApplicationsFunctional Brain Connectivity Studies

Diffusion tensor imaging of the brain

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Alexander, Andrew L., Lee, Jee Eun, Lazar, Mariana, Field, Aaron S.·2007·Neurotherapeutics

DOI 10.1016/j.nurt.2007.05.011PMC PMC2041910

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Abstract

Diffusion tensor imaging (DTI) is a promising method for characterizing microstructural changes or differences with neuropathology and treatment. The diffusion tensor may be used to characterize the magnitude, the degree of anisotropy, and the orientation of directional diffusion. This review addresses the biological mechanisms, acquisition, and analysis of DTI measurements. The relationships between DTI measures and white matter pathologic features (e.g., ischemia, myelination, axonal damage, inflammation, and edema) are summarized. Applications of DTI to tissue characterization in neurotherapeutic applications are reviewed. The interpretations of common DTI measures (mean diffusivity, MD; fractional anisotropy, FA; radial diffusivity, D(r); and axial diffusivity, D(a)) are discussed. In particular, FA is highly sensitive to microstructural changes, but not very specific to the type of changes (e.g., radial or axial). To maximize the specificity and better characterize the tissue microstructure, future studies should use multiple diffusion tensor measures (e.g., MD and FA, or D(a) and D(r)).

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Long data acquisitions possible in ex vivo DTI allow high spatial resolution without image corruption due to motion or breathing that are common in in vivo DTI.
“We leveraged the ability of long data acquisitions that are possible in ex vivo DTI to achieve a high spatial resolution, without suffering from image corruption due to motion or breathing that are common in in vivo DTI [12,13].”
From Diffusion tensor imaging reveals whole-brain microstructural changes in the P301L mouse model of tauopathy. (2020) · cites this paper as [13]
The Diffusion-Weighted Image Acquisition section says subject motion can corrupt diffusion-weighted images, and Protocol Considerations discusses scan-time and spatial-resolution constraints. But the paper does not state that ex vivo DTI permits long acquisitions without motion or breathing artifacts, so it supports only the general imaging considerations, not the ex vivo comparison. (LLM, conf=0.83)
Experimental — accuracy not yet measured
White matter alterations can be detected in vivo by diffusion tensor imaging (DTI).
“White matter alterations can be detected in vivo by diffusion tensor imaging (DTI) (Alexander et al., 2007).”
From White matter diffusion alterations precede symptom onset in autosomal dominant Alzheimer’s disease (2018) · cites this paper as Alexander et al., 2007
Diffusion-weighted imaging probes the directional diffusivity of water molecules and can yield information about the microstructural properties of brain tissue.
“Diffusion-weighted imaging is a MRI technique that probes the directional diffusivity of water molecules and can, thus, yield information about the microstructural properties of brain tissue [11][12][13].”
From Diffusion tensor imaging reveals whole-brain microstructural changes in the P301L mouse model of tauopathy. (2020) · cites this paper as [13]
Increased MD in these regions suggests reduced white matter density and potential myelin breakdown associated with an adult ADHD diagnosis.
“More specifically, increased MD in the left middle temporal gyrus, right internal capsule, and right midbrain suggests reduced white matter density and potential myelin breakdown associated with an adult ADHD diagnosis [4], which is in agreement with in increased MD found in previous studies in children and adolescents with ADHD [47].”
From The brain anatomy of attention-deficit/hyperactivity disorder in young adults—a magnetic resonance imaging study (2017) · cites this paper as [4]

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Diffusion-tensor imaging for the detection and quantification of treatment-induced white matter injury in children with medulloblastoma: a pilot study.
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Fractional anisotropy value by diffusion tensor magnetic resonance imaging as a predictor of cell density and proliferation activity of glioblastomas
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Measurement of fractional anisotropy using diffusion tensor MRI in supratentorial astrocytic tumors
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Diffusion Tensor Imaging of Frontal White Matter Microstructure in Early Alzheimer’s Disease: A Preliminary Study
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MRI detects white matter reorganization after neural progenitor cell treatment of stroke
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Orientation-independent diffusion imaging without tensor diagonalization: Anisotropy definitions based on physical attributes of the diffusion ellipsoid
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Diffusion tensor imaging in hydrocephalus: initial experience.
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Diagnostic utility of hippocampal size and mean diffusivity in amnestic MCI.
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REAL-TIME ECHO-PLANAR IMAGING BY NMR
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White matter reorganization after surgical resection of brain tumors and vascular malformations.
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Diffusion Tensor Imaging of the Corticospinal Tract Following Cerebral Hemispherectomy
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Presurgical and intraoperative mapping of the motor system in congenital truncation of the precentral gyrus.
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Untitled work
Basser (2000) · doi:10.1002/1522-2594(200010)44:4
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Research works printed but not linked: 7

Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE: sensitivity encoding for fast MRI. Magn Reson Med 1999;42:952-962.
Jones DK, Horsfield MA, Simmons A. Optimal strategies for measuring diffusion in anisotropic systems by magnetic reso- nance imaging. Magn Reson Med 1999;42:515-525.
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Basser PJ, Pajevic S. Statistical artifacts in diffusion tensor MRI (DT-MRI) caused by background noise. Magn Reson Med 2000; 44:41-50.
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Authors: Alexander, A. L., Lee, J. E., Lazar, M., & Field, A. S.
Affiliations: University of Wisconsin–Madison (US)
Corresponding author: Alexander, Andrew L.
ORCID: Alexander, Andrew L.
Lee, Jee Eun
Lazar, Mariana
Field, Aaron S.
Venue: Neurotherapeutics
Publisher: Elsevier BV
Published: 2007-07
Volume: 4
Issue: 3
Pages: 316-329
ISSN: 1878-7479 (ISSN-L)
DOI: 10.1016/j.nurt.2007.05.011
PMC: PMC2041910
OpenAlex: W2004006028
Cited by: 2,747
References: 126
Citations by year: 2026: 148 · 2025: 191 · 2024: 177 · 2023: 163 · 2022: 218 · 2021: 259 · 2020: 242 · 2019: 255 · 2018: 199 · 2017: 186 · 2016: 170 · 2015: 137 · 2014: 109 · 2013: 80 · 2012: 49
FWCI: 4.13
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
www.elsevier.com/open-access/userlicense/1.0/ (vor, 5886 d)
Locations: Neurotherapeutics (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Funders: National Multiple Sclerosis Society
Dana Foundation
Multiple Sclerosis Society
National Institutes of Health
National Institute of Mental Health (R01MH062015, MH 62015, P50MH069315)
National Institute on Drug Abuse (R21DA015879)
National Institute of Neurological Disorders and Stroke (NS050466, R01NS050466)
Eunice Kennedy Shriver National Institute of Child Health and Human Development (HD35476)
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: diffusion tensor imaging, white matter microstructure, fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, white matter pathology, ischemia, myelination, axonal injury, neuroinflammation, edema
MeSH terms: Brain, Image Processing, Computer-Assisted, Anisotropy, Diffusion Magnetic Resonance Imaging

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