Evaluation of Diffusion Tensor Imaging and Fiber Tractography of the Median Nerve: Preliminary Results on Intrasubject Variability and Precision of Measurements
Bibliographic record
Abstract
OBJECTIVE: The purposes of this study were to determine the intrasubject side-to-side variability of quantitative and qualitative measures of diffusion tensor imaging (DTI) and fiber tractography of the median nerves and to determine the precision of quantitative measurements and fiber tractography. SUBJECTS AND METHODS: Fifteen healthy volunteers (seven men, eight women; mean age, 31.2 years) underwent DTI of both wrists with a single-shot spin-echo-based echo-planar imaging sequence (TR/TE, 7,000/103; b value 1,025 s/mm2). Postprocessing included fiber tractography and quantitative analysis of fiber length, fiber density index, fractional anisotropy, apparent diffusion coefficient, and signal-to-noise ratio. Two readers in consensus graded the quality of fiber tract images of the two wrists as equal, slightly different, or very different. Fiber tractography and all analyses were repeated after 3 weeks, and the images from the two sessions were compared. RESULTS: No statistically significant side-to-side differences in quantitative data were found (p=0.054-0.999). In all subjects, the quality of fiber tract images of the right and left median nerves was either slightly or very different. Between the initial and the second quantitative analyses, no statistically significant differences (p=0.086-0.898) were found, and the quality of fiber tract images was rated equal for nine of 15 subjects (60%) and slightly different for six of 15 subjects (40%). CONCLUSION: Preliminary results indicate that quantitative evaluation of DTI of the median nerve is precise. The absence of statistically significant intrasubject side-to-side variability in quantitative data suggests that the healthy contralateral nerve can be used as an internal control. Observed side-to-side variability in the quality of fiber tract images, however, rules out side-to-side comparisons in fiber tractography.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".