Locus Coeruleus <scp>MR</scp> Measured Signal Intensity in Fibromyalgia Relative to Healthy Controls
Bibliographic record
Abstract
BACKGROUND: Fibromyalgia is a chronic pain condition without an established aetiology. However, noradrenergic dysfunction is a possible mechanism to explain the constellation of symptoms associated with fibromyalgia. Noradrenaline synthesis in the locus coeruleus (LC) results in a paramagnetic by-product, neuromelanin. Recently, a magnetic resonance imaging sequence sensitive to neuromelanin has been used to assay LC signal intensity, a proxy for noradrenergic system function. Here, we use MR imaging to investigate the noradrenergic-locus coeruleus system in participants with fibromyalgia and healthy controls. METHODS: Forty-six participants with fibromyalgia and 41 healthy controls were recruited for a cross-sectional characterisation of LC signal intensity at 3 T, quantified from a 2D gradient echo acquisition. Participants completed the Revised Fibromyalgia Impact Questionnaire, as well as measures of anxiety, depression, sleep and the THINC-it cognitive battery. RESULTS: An independent groups t-test revealed no differences in LC signal intensity between participants with fibromyalgia and healthy controls. For the participants with fibromyalgia, partial correlations accounting for age showed no association between LC signal intensity and fibromyalgia history, fibromyalgia symptom severity, anxiety, depression, insomnia or cognitive performance. Almost 90% of participants with fibromyalgia had been exposed to medications targeting noradrenergic function complicating the interpretation of these findings. CONCLUSIONS: LC signal intensity as measured by MR did not distinguish participants with fibromyalgia and healthy controls, nor was it associated with core fibromyalgia pain symptoms or associated symptoms. Dynamic measures of noradrenergic function may be required to understand noradrenergic contributions to fibromyalgia. SIGNIFICANCE STATEMENT: This study is the first report using MR measured signal intensity of the LC to examine noradrenergic function in participants with fibromyalgia. There was no difference in signal intensity when comparing patients to controls, nor did it associate with any symptoms or associated features of fibromyalgia. This suggests that lifetime noradrenergic function may not distinguish fibromyalgia.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".