Multimodal Imaging in Alcohol Use Disorder
Poster No:
440
Submission Type:
Abstract Submission
Authors:
William Hoffman1, Laura Dennis1, Holly McCready1, Daniel Smith2, Jazryn Nagum1, Esteban Rigales1, Meghan Oswald3, Milky Kohno1
Institutions:
1VA Portland Health Care System, Portland, OR, 2Oregon Health & Science University, Portland, OR, 3Northwell Health Mather Hospital, Port Jefferson, NY
First Author:
Co-Author(s):
Introduction:
Alcohol Use Disorder (AUD) causes widespread loss of cortical brain volume (Li, 2021) and damage to white matter tracts connecting affected cortical regions (Voon, 2020). We investigated the relationship of cortical volume loss to disturbances in white matter integrity in 71 adult subjects with AUD and 89 healthy controls. We hypothesized that deficits in cortical thickness and white matter integrity would primarily affect regions in the executive control and salience attribution networks.
Methods:
MRI data was acquired on either a 3 Tesla (T) Siemens Magnetom Prisma scanner and a 32-channel phased array head coil. T1-weighted anatomical images were obtained from MPRAGE-- 176 slices, 1 mm isovoxels, TR/TE/TI/α = 2500 ms/2.88 ms/1060 ms/8°, FOV = 256x256 mm, 2x Parallel Imaging, duration 7.3 min). Two HARDI scans were acquired (66 axial slices, 2.2 mm thick, TR/TE/α = 4300 ms/96 ms/90°, FOV= 25.6 cm2, PAT mode /Accel factor = GRAPPA/2) consisting of six non-diffusion weighted (B0) images followed by 32 non-collinear directions at B0 = 1000 s mm-2 and at B0 = 2000 s mm-2. We extracted cortical thickness and measures of sub-cortical volumes using FreeSurfer and the Desikan-Killiany atlas using a standard pipeline. We ran a Random Forest with Recursive Features Elimination to identify the cortical regions that best differentiated AUD and CS and tested the multivariate significance of volumetric differences. We used Tract-Based Spatial Statistics (TBSS) to investigate whole brain fractional anisotropy differences between the groups and Multi-Shell Multi-Tissue Constrained Spherical Deconvolution (MSMT CSD) to calculate probabilistic tractography between a set of 13 nodes pre-selected to represent regions with known white matter connections that were predicted to differ between groups.
Results:
The RF-RFE classifier identified 29 regions that appeared in > 70% of the classification trees. Comparison of these regions with a multivariate general linear model with age as a covariate was significant (Wilks' Λ = 0.7912, p < 0.001). Regions in the ECN and SAN, as well as the Default Mode Network, differed between the two groups (Figure 1). TBSS found higher mean FA values (corrected for multiple comparisons) in control subjects compared to AUD primarily along the following white matter tracts: left/right anterior thalamic radiation, left/right inferior fronto-occipital fasciculus, temporal part of the left superior longitudinal fasciculus, left corticospinal, left inferior longitudinal fasciculus, left uncinate fasciculus, and the forceps minor (Figure 2). Probabilistic tractography calculated for the a priori node pairs found 8/13 showed significantly less connectivity in CS relative to AUD, 4 pairs showed trend differences and two pairs were not different (Figure 2).
Conclusions:
These results re-inforce the concept that chronic alcohol abuse results in loss of cortical thickness and the associated white matter integrity between regions suffering volume loss. These findings likely result from a combination of cortical neuronal loss, loss of cortical synapses or loss or damage of projection axons. Our finding of correlation between tractographic deficits in AUD coupled with regional cortical volume loss strongly suggests damage to projection axons and their cortical cell bodies.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Anatomy and Brain Mapping 2
Keywords:
STRUCTURAL MRI
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
Other - alcohol
1|2Indicates the priority used for review
Abstract Information
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Was this research conducted in the United States?
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Provide references using APA citation style.
Voon, V. (2020). Addictions NeuroImaging Assessment (ANIA): Towards an integrative framework for alcohol use disorder. Neuroscience & Biobehavioral Reviews, 113, 492-506.