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Major Depressive Disorder and White Matter Abnormalities: A Diffusion Tensor Imaging Study with Tract-Based Spatial Statistics, by Kieseppä et al.

01/01/2009 (Aprox)


In the field of depression, white matter hyperintensities have been found consistently in elderly unipolar patients. A DTI study of 2009 established that, in comparison with controls, patients with major depressive disorder tend to show lower FA values in the left sagittal stratum; the implied structural changes “may contribute” to the previously detected dysfunction in the limbic-cortical network in depressive patients (Kieseppä et al. 2009, 5).


Vidal, Fernando and Ortega, Francisco. Being Brains: Making the Cerebral Subject (Forms of Living)....

Tuula Kieseppä is a researcher at Helsinki University.

Source of image

tuhat.helsinki.fi/portal/en/person/kiestuu

Abstract

Background: A few diffusion tensor imaging (DTI) studies have shown abnormalities in areas of white matter tracts involved in mood regulation in geriatric depressive patients, using a region-of-interest technique. A voxel-based morphometry DTI study of young depressive patients reported similar results. In this study, we explored the structure of the white matter of the whole brain with DTI in middle-aged major depressive disorder (MDD) patients, using novel tract-based spatial statistics.

Methods: Sixteen MDD patients and 20 controls underwent DTI. An automated tract-based spatial method (TBSS) was used to analyze the scans.

Results: Compared with controls, the MDD patients showed a trend for lower values of fractional anisotropy (FA) in the left sagittal stratum, and suggestive decreased FA in the right cingulate cortex and posterior body of corpus callosum. Regressing out the duration and severity of disorder in the model did not change the finding in the sagittal stratum, but dissipated the decrease of FA in latter regions.

Limitations: Possibly by reason of a relatively small study sample for a TBSS, the results are suggestive, and should be replicated in further studies.

Conclusions: A novel observer-independent DTI method showed decreased FA in the middle-aged MDD patients in white matter regions that have previously connected to the emotional regulation. Lower FA might imply underlying structural abnormalities that contribute to the dysfunction detected in the limbic-cortical network of depressive patients.

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Kieseppä, Tuula, et al. 2009. “Major Depressive Disorder and White Matter Abnormalities: A Diffusion...

Tractographic reconstruction of neural connections via DTI. Image by Thomas Schultz.

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What is DTI?

The same language that is used when neurobiological interactions and associations are inferred from statistical covariance characterizes a more recent application in psychiatric imaging research, namely diffusion tensor imaging (DTI) studies of white matter hyperintensities. White matter hyperintensities appear on magnetic resonance images as ultrawhite patches that indicate injury to axons. DTI produces neural tract images on the basis of the diffusion of water in tissue (such as the axons in white matter). The variation of diffusion along different spatial directions provides information about diffusion anisotropy (the direction preference of the diffusion process); the results are couched in terms of “fractional anisotropy” (FA), that is to say in degrees of anisotropy (from 0 for isotropic, or homogenous in all directions, to 1 for fully anisotropic). The technique is used to investigate tissue structure and connectivity between regions or points in the brain. While DTI is different from fMRI and other imaging technologies, its basic goal—to correlate pathologies with cerebral locations and circuits— continues to illustrate the assumptions, promises, and limitations of the neurocorrelational logic.

Vidal, Fernando and Ortega, Francisco. Being Brains: Making the Cerebral Subject (Forms of Living)....

Brain Scanning and Imaging Techniques (Intro Psych Tutorial #31)
fMRI and DTI: Revealing learning processes in the brain
Introducing MRI: Diffusion Tensor Imaging (50 of 56)
Diffusion Tensor Imaging
Diffusion Tensor Imaging (DTI)

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Published in 6/02/2019

Updated in 19/02/2021

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