Neuroimaging Changes during Early Recovery from Alcohol Use Disorder
Bibliographic record
Abstract
Alcohol use disorder (AUD) is one of the most prevalent, harmful, and costly preventable disorders in the world. AUD is associated with wide-spread structural and functional brain deficits, which are at least partially reversible with sustained abstinence. The most rapid recovery is thought to occur within the initial weeks of sobriety. The mechanism and progression of structural and functional AUD-related brain damage and subsequent recovery during remission remain not fully understood. The objective of this exploratory project was to better characterize the macroscopic and microscopic structural and functional brain changes in recovering AUD patients between approximately two weeks and one month of abstinence, using multi-modal magnetic resonance imaging (MRI) techniques. The data was acquired at two clinical sites in Edmonton, Canada and Mannheim, Germany and together represent one of the largest and most clinically homogeneous, longitudinal, multimodal AUD neuroimaging datasets analyzed to this date. We have conducted six sets of analyses examining: 1) voxel and surface-based morphometry of structural brain changes; 2) region-based morphometry of structural brain changes; 3) white matter microstructure brain changes; 4) regional resting state functional connectivity brain changes; 5) brain changes in large-scale resting state functional network connectivity; and 6) AUD-related brain iron accumulation. The results of these studies have revealed a rich set of complex results across all of the tested modalities. 1) The first analysis revealed a broad high single digit decrease in global gray and white matter densities in AUD at the first time point, which persisted in mid-single digit at the second time point, exhibiting a positive but non-significant structural integrity improvement with sustained abstinence. The AUD group has also exhibited a persistent low single digit decrease in global cortical thickness that persisted through both time points. Clinical severity scales were weakly-to-moderately correlated to the magnitude of the structural atrophy. 2) The second analysis revealed broad high single digit decrease in region-specific cortical, subcortical, and cerebellar regions which showed significant correlation to the clinical severity, especially in the most affected regions. Longitudinal interscan differences associated with sustained abstinence did not survive multiple comparison correction but indicated a positive recovery trend. 3) The third analysis revealed aberrant diffusion tensor imaging (DTI) scalar pattern consistent with wide-spread neuronal and/or myelin injury in AUD at both time points. Magnitude of the scalar’s impairment was in most cases correlated to the clinical severity measures. The longitudinal differences were not significant but alluded to a pattern of microstructural healing during the early AUD recovery. 4) The fourth analysis revealed persistent AUD-related decrease in regional functional connectivity indices in basal ganglia that persisted during both time points, as well as aberrant increase in functional connectivity in the frontal cortex in the AUD patients. Longitudinal differences were mostly not significant. Magnitude of most of the functional deficits was correlated to the AUD clinical severity measures. The longitudinal changes should be considered with caution but might potentially provide evidence of over-compensatory adaptation in the abstinent AUD. 5) The fifth analysis revealed a largely inconsistent complex set of differences in the resting state functional networks derived from an independent component analysis (ICA). Together with hierarchical network analysis, these results suggest a pattern of global hypoconnectivity in the AUD with encouraging functional connectivity convergence across plurality of the networks. Most of the significant changes were correlated with at least one measure of AUD severity. 6) The sixth analysis demonstrated use of a novel quantitative susceptibility technique in a clinical cohort to retrospectively measure brain iron accumulation. This analysis revealed significant high single-digit to low teen percentage increase in iron accumulation in deep brain gray matter in AUD. Altogether, the six sets of analyses completed in this project succeeded in characterizing AUD-related structural and functional deficits in recently detoxified AUD patients but largely failed to detect significant longitudinal differences during the approximately two week to one month interscan remission period. Several of the above analyses were first of their kind and provide unique evidence characterizing early brain recovery dynamics during successful remission from AUD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".