Temperature dependence and histological correlation of inhomogeneous magnetization transfer and myelin water imaging in ex vivo brain
Bibliographic record
Abstract
The promise of inhomogeneous magnetization transfer (ihMT) as a new myelin imaging method was studied in ex vivo human brain tissue and in relation to myelin water fraction (MWF). The temperature dependence of both methods was characterized, as well as their correspondence with a histological measure of myelin content. Unfiltered and filtered ihMT protocols were studied by adjusting the saturation scheme to preserve or attenuate signal from tissue with short dipolar relaxation time T1D. ihMT ratio (ihMTR) and MWF maps were acquired at 7 T from formalin-fixed human brain samples at 22.5 °C, 30 °C and 37 °C. The impact of temperature on unfiltered ihMTR, filtered ihMTR and MWF was investigated and compared to myelin basic protein staining. Unfiltered ihMTR exhibited no temperature dependence, whereas filtered ihMTR increased with increasing temperature. MWF decreased at higher temperature, with an increasing prevalence of areas where the myelin water signal was unreliably determined, likely related to a reduction in T2 peak separability at higher temperatures ex vivo. MWF and ihMTR showed similar per-sample correlation with myelin staining at room temperature. At 37 °C, filtered ihMTR was more strongly correlated with myelin staining and had increased dynamic range compared to unfiltered ihMTR. Given the temperature dependence of filtered ihMT, increased dynamic range, and strong myelin specificity that persists at higher temperatures, we recommend carefully controlled temperatures close to 37 °C for filtered ihMT acquisitions. Unfiltered ihMT may also be useful, due to its independence from temperature, higher amplitude values, and sensitivity to short T1D components. Ex vivo myelin water imaging should be performed at room temperature, to avoid fitting issues found at higher temperatures.
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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 | 0.000 |
| 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".