Myelin water imaging : development at 3.0T, application to the study of multiple sclerosis, and comparison to diffusion tensor imaging
Bibliographic record
Abstract
T2 relaxation imaging can be used to measure signal from water trapped between myelin bilayers; the ratio of myelin water signal to total water is termed the myelin water fraction (MWF). First, results from multi-component T2 relaxation and diffusion tensor imaging (DTI) were compared for 19 multiple sclerosis (MS) subjects at 1.5 T to better understand how each measure is affected by pathology. In particular, it was determined that the detection of a long-T2 signal within an MS lesion may be indicative of a different underlying pathology than is present in lesions without long-T2 signal. Next, the single-slice T2 relaxation measurement was implemented, refined, and validated at 3.0 T. Scan parameters were varied for phantoms and in-vivo brain, and changes in multi-exponential fit residuals and T2 distribution-derived parameters such as MWF were monitored to determine which scan parameters minimized artifacts. Measurements were compared between 1.5 T and 3.0 T for 10 healthy volunteers. MWF maps were qualitatively similar between field strengths. MWFs were significantly higher at 3.0 T than at 1.5 T, but with a strong correlation between measurements at the different field strengths. Due to long acquisition times, multi-component T2 relaxation has thus far been clinically infeasible. The next study aimed to validate a new 3D multi-component T2 relaxation imaging technique against the 2D single-slice technique most commonly used. Ten healthy volunteers were scanned with both the 2D single-slice and 3D techniques. MWF maps were qualitatively similar between scans. MWF values were highly correlated between the acquisition methods. Although MWF values were generally lower using the 3D technique, they were only significantly so for peripheral brain structures, likely due to increased sensitivity of slab-selective refocusing pulses used for the 3D approach. The 3D T2 relaxation sequence was then applied to the study of MS to take advantage of the increased brain coverage. Thirteen MS subjects and 11 controls underwent T2 relaxation and DTI examinations to produce histograms of MWF and several DTI-derived metrics. MS MWF histograms differed considerably from those of controls, and differences in MS MWF histograms did not mirror differences in DTI histograms relative to matched controls.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".