Morphometrics of the Entire Human Spinal Cord and Spinal Canal Measured From In Vivo High-Resolution Anatomical Magnetic Resonance Imaging
Bibliographic record
Abstract
STUDY DESIGN: Measurements of cervical and thoracolumbar human spinal cord (SC) geometry based on in vivo magnetic resonance imaging and investigation of morphological "invariants." OBJECTIVE: The current work aims at providing morphological features of the complete in vivo human normal SC and at investigating possible "invariant" parameters that may serve as normative data for individualized study of SC injuries. SUMMARY OF BACKGROUND DATA: Few in vivo magnetic resonance image-based studies have described human SC morphology at the cervical level, and similar description of the entire SC only relies on postmortem studies, which may be prone to atrophy biases. Moreover, large interindividual variations currently limit the use of morphological metrics as reference for clinical applications or as modeling inputs. METHODS: Absolute metrics of SC (transverse and anteroposterior diameters, width of anterior and posterior horns, cross-sectional SC area, and white matter percentage) were measured using semiautomatic segmentation of high resolution in vivo T2*-weighted transverse images acquired at 3 T, at each SC level, on healthy young (N = 15) and older (N = 8) volunteers. Robustness of measurements, effects of subject, age, or sex, as well as comparison with previously published postmortem data were investigated using statistical analyses (separate analysis of variance, Tukey-HSD, Bland-Altman). Normalized-to-C3 parameters were evaluated as invariants using a leave-one-out analysis. Spinal canal parameters were measured and occupation ratio border values were determined. RESULTS: Metrics of SC morphology showed large intra- and interindividual variations, up to 30% and 13%, respectively, on average. Sex had no influence except on posterior horn width (P < 0.01). Age-related differences were observed for anteroposterior diameter and white matter percentage (P < 0.05) and all postmortem metrics were significantly lower than in vivo values (P < 0.001). In vivo normalized SC area and diameters seemed to be invariants (R > 0.74, root-mean-square deviation < 10%). Finally, minimal and maximal occupation ratio were 0.2 and 0.6, respectively. CONCLUSION: This study presented morphological characteristics of the complete in vivo human SC. Significant differences linked to age and postmortem state have been identified. Morphological "invariants" that could be used to calculate the normally expected morphology accurately, were also identified. These observations should benefit to biomechanical and SC pathology studies. LEVEL OF EVIDENCE: N/A.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".