Altered White Matter Integrity in the Corpus Callosum in Fibromyalgia Patients Identified by Tract‐Based Spatial Statistical Analysis
Bibliographic record
Abstract
OBJECTIVE: Although recent imaging studies of fibromyalgia (FM) have converged on a dysfunction of central pain processing as the primary pathophysiologic cause of the disorder, microstructural changes of the white matter (WM) suggestive of abnormalities in the anatomic connectivity of the brain have not been extensively examined. The aim of this study was to investigate WM integrity and its possible relationship to pain symptoms in women with FM. METHODS: Nineteen FM patients and 21 age-, sex-, and education-matched healthy control subjects were included in the study and underwent diffusion-weighted imaging. Group differences in WM integrity, which were assessed via fractional anisotropy (FA), was investigated by applying tract-based spatial statistics. RESULTS: As compared with the healthy control group, the FM group showed a single cluster with lower FA in the left body of the corpus callosum, which was found to be connected to the bilateral sensorimotor cortices (P < 0.05, corrected for multiple comparisons). Furthermore, FA values in the cluster were negatively associated with sensory pain, as measured by the Short-Form McGill Pain Questionnaire, as well as with the relative magnitude of sensory pain versus affective pain (calculated by dividing the sensory score by the affective score). CONCLUSION: Findings of the current study demonstrated that patients with FM had disrupted WM microstructure in the body of the corpus callosum, which was associated with clinical pain intensity. Our results suggest that abnormal interhemispheric transfer might contribute to the heightened pain perception. Our findings further strengthen the hypothesis of centrally augmented pain processing in patients with FM.
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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 | 0.001 |
| 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".