<i>In vivo</i> MRI Structural and PET Metabolic Connectivity Study of Dopamine Pathways in Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease (AD) is characterized by an involvement of brain dopamine (DA) circuitry, the presence of which has been associated with emergence of both neuropsychiatric symptoms and cognitive deficits. OBJECTIVE: In order to investigate whether and how the DA pathways are involved in the pathophysiology of AD, we assessed by in vivo neuroimaging the structural and metabolic alterations of subcortical and cortical DA pathways and targets. METHODS: We included 54 healthy control participants, 53 amyloid-positive subjects with mild cognitive impairment due to AD (MCI-AD), and 60 amyloid-positive patients with probable dementia due to AD (ADD), all with structural 3T MRI and 18F-FDG-PET scans. We assessed MRI-based gray matter reductions in the MCI-AD and ADD groups within an anatomical a priori-defined Nigrostriatal and Mesocorticolimbic DA pathways, followed by 18F-FDG-PET metabolic connectivity analyses to evaluate network-level metabolic connectivity changes. RESULTS: We found significant tissue loss in the Mesocorticolimbic over the Nigrostriatal pathway. Atrophy was evident in the ventral striatum, orbitofrontal cortex, and medial temporal lobe structures, and already plateaued in the MCI-AD stage. Degree of atrophy in Mesocorticolimbic regions positively correlated with the severity of depression, anxiety, and apathy in MCI-AD and ADD subgroups. Additionally, we observed significant alterations of metabolic connectivity between the ventral striatum and fronto-cingulate regions in ADD, but not in MCI-AD. There were no metabolic connectivity changes within the Nigrostriatal pathway. CONCLUSION: Our cross-sectional data support a clinically-meaningful, yet stage-dependent, involvement of the Mesocorticolimbic system in AD. Longitudinal and clinical correlation studies are needed to further establish the relevance of DA system involvement in AD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".