Multimodal Brain MRI of Deep Gray Matter Changes Associated With Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND: Behavioral symptoms, including mood disorders, substantially impact the quality of life of patients with inflammatory bowel disease (IBD), even when clinical remission is achieved. Here, we used multimodal magnetic resonance imaging (MRI) to determine if IBD is associated with changes in the structure and function of deep gray matter brain regions that regulate and integrate emotional, cognitive, and stress responses. METHODS: Thirty-five patients with ulcerative colitis (UC) or Crohn's disease (CD) and 32 healthy controls underwent 3 Tesla MRIs to assess volume, neural activity, functional connection strength (connectivity), inflammation, and neurodegeneration of key deep gray matter brain regions (thalamus, caudate, pallidum, putamen, amygdala, hippocampus, and hypothalamus) involved in emotional, cognitive and stress processing. Associations with sex, presence of pain, disease activity, and C-reactive protein (CRP) concentration were examined. RESULTS: Significantly increased activity and functional connectivity were observed in cognitive and emotional processing brain regions, including parts of the limbic system, basal ganglia, and hypothalamus of IBD patients compared with healthy controls. Inflammatory bowel disease patients exhibited significantly increased volumes of the amygdala and hypothalamus, as well as evidence of neurodegeneration in the putamen and pallidum. Hippocampal neural activity was increased in IBD patients with active disease. The volume of the thalamus was positively correlated with CRP concentration and was increased in females experiencing pain. CONCLUSIONS: Patients with IBD exhibit functional and structural changes in the limbic and striatal systems. These changes may be targets for assessing or predicting the response to therapeutic interventions aimed at improving comorbid emotional and cognitive symptoms.
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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 | 0.000 |
| 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".