Brain Iron Alteration in Pediatric Tourette Syndrome: A Quantitative Susceptibility Mapping Study
Bibliographic record
Abstract
BACKGROUND: The cortico-striato-thalamo-cortical circuits play a crucial role in the pathogenesis of Tourette syndrome (TS). While iron deficiency has been reported in adult TS, the iron content in pediatric TS remains poorly understood. This study aims to quantitatively assess whole-brain iron deposition in pediatric TS compared to typically developing (TD) children using quantitative susceptibility mapping (QSM). METHODS: In this prospective study, we recruited 50 children with a clinical diagnosis of TS and 50 age- and gender-matched TD controls. Whole-brain images were acquired using 3D T1 and multi-echo gradient-recalled echo sequences. QSM maps were generated using the STISuite toolbox. After normalizing the QSM maps to Montreal Neurological Institute space, voxel-based analysis was applied to compare between-group differences in iron content. Additionally, we evaluated the relationship between iron content and tic severity in TS children using the Pearson's correlation test. RESULTS: < 0.001). Notably, QSM values in the left putamen showed a significant negative correlation with tic severity (p = 0.044). CONCLUSIONS: Our findings suggest that disturbed brain iron homeostasis in specific regions is associated with pediatric TS. These results reinforce the importance of the cortico-striato-thalamo-cortical circuits in TS pathogenesis and highlight the potential role of iron dysregulation. Furthermore, our study demonstrates that QSM could serve as a valuable auxiliary biomarker for diagnosing and potentially monitoring pediatric TS.
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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".