Quantitative myelin imaging with MRI and PET: an overview of techniques and their validation status
Bibliographic record
Abstract
Myelin is the protective sheath wrapped around axons, consisting of a phospholipid bilayer with water between the wraps. The measurement of damage to the myelin sheaths, the evaluation of the efficacy of therapies aiming to promote remyelination and monitoring the degree of brain maturation in children all require non-invasive quantitative myelin imaging methods. To date, various myelin imaging techniques have been developed. Five different MRI approaches can be distinguished based on their biophysical principles: (i) imaging of the water between the lipid bilayers directly (e.g. myelin water imaging); (ii) imaging the non-aqueous protons of the phospholipid bilayer directly with ultra-short echo-time techniques; (iii) indirect imaging of the macromolecular content (e.g. magnetization transfer; inhomogeneous magnetization transfer); (iv) mapping of the effects of the myelin sheath's magnetic susceptibility on the MRI signal (e.g. quantitative susceptibility mapping); and (v) mapping of the effects of the myelin sheath on water diffusion. Myelin imaging with PET uses radioactive molecules with high affinity to specific myelin components, in particular myelin basic protein. This review aims to give an overview of the various myelin imaging techniques, their biophysical principles, image acquisition, data analysis and their validation status.
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 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) | 0.001 | 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".