Myelin Water Fraction and Intra/Extracellular Water Geometric Mean T<sub>2</sub>Normative Atlases for the Cervical Spinal Cord from 3T MRI
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT BACKGROUND AND PURPOSE Acquiring and interpreting quantitative myelin‐specific MRI data at an individual level is challenging because of technical difficulties and natural myelin variation in the population. To overcome these challenges, we used multiecho T 2 myelin water imaging (MWI) to create T 2 metric healthy population atlases that depict the mean and variation of myelin water fraction (MWF), and intra‐ and extracellular water mobility as described by geometric mean T 2 (IEGMT 2 ). METHODS Cervical cord MWI was performed at 3T on 20 healthy individuals (10M/10F, mean age: 36 years) and 3 relapsing remitting multiple sclerosis (RRMS) participants (1M/2F, age: 39/42/37 years). Anatomical data were collected for the purpose of image segmentation and registration. Atlases were created by coregistering and averaging T 2 metrics from all controls. Voxel‐wise z ‐score maps from 3 RRMS participants were produced to demonstrate the preliminary utility of the MWF and IEGMT 2 atlases. RESULTS The average MWF atlas provides a representation of myelin in the spinal cord consistent with well‐known spinal cord anatomical characteristics. The IEGMT 2 atlas also depicted structural variations in the spinal cord. Z ‐score analysis illustrated distinct abnormalities in MWF and IEGMT 2 in the 3 RRMS cases. CONCLUSIONS Our findings highlight the potential for using a quantitative T 2 relaxation metric atlas to visualize and detect pathology in spinal cord. Our MWF and IEGMT 2 atlases (URL: https://sourceforge.net/projects/mwi-spinal-cord-atlases/ ) can serve as normative references in the cervical spinal cord for other studies.
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.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it