2313 Quantitative analysis of neck muscle T2 relaxation times in cervical dystonia
Bibliographic record
Abstract
Objectives T2 relaxation times (T2RT) of muscles increase with physical exercise, however T2RT has not been studied in dystonic muscles with are in a state of constant activity. Major muscles involved in cervical dystonia (CD) include splenius capitis, semispinalis capitis, levator scapulae, sternocleidomastoid and trapezius which are also prime targets for botulinum toxin treatment. This study analysed the T2RTs in key neck muscles in CD, and compared them with normal subjects. Methods 23 CD subjects underwent MRI and clinical assessment just prior to their next cycle of botulinum toxin treatment. 3 patients were excluded from data analysis due to significant muscle atrophy. Using T2 images, two circular regions of interest (ROIs) were drawn in two mutually exclusive regions within neck muscle fibres at two different levels and the values averaged. ROI values were translated into T2RTs. T2RTs were compared with the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) and EMG activity score. Results CD subjects showed higher T2RTs in different neck muscles compared to normal subjects. T2RTs correlated with TWSTRS scores, but not EMG scores. When clinically separated into simple torticollis and complex CD, there were no significant differences in neck muscle T2RTs. Conclusion T2RT may be helpful in distinguishing dystonic vs normal neck muscles, allowing more accurate targeting of muscle groups for botulinum toxin treatment. T2RT may be supportive in the diagnosis of cervical dystonia. Future studies could compare qualitative EMG scoring and vs quantitative T2RTs in the identification and assessment of dystonic neck muscles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.003 | 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".