The role of edema and demyelination in chronic T<sub>1</sub> black holes: A quantitative magnetization transfer study
Bibliographic record
Abstract
PURPOSE: To use quantitative magnetization transfer imaging (qMTI) in an investigation of T1-weighted hypointensity observed in clinical magnetic resonance imaging (MRI) scans of multiple sclerosis (MS) patients, which has previously been proposed as a more specific indicator of tissue damage than the more commonly detected T2 hyperintensity. MATERIALS AND METHODS: A cross-sectional study of 10 MS patients was performed using qMTI. A total of 60 MTI measurements were collected in each patient at a resolution of 2 x 2 x 7 mm, over a range of saturation pulses. The observed T1 and T2 were also measured. qMT model parameters were estimated using a voxel-by-voxel fit. RESULTS: A total of 65 T2-hyperintense lesions were identified; 53 were also T1 hypointense. In these black holes, the qMTI-derived semisolid pool fraction F correlated negatively with T(1,obs) (r2 = 0.76; P < 0.0001). The water pool absolute size (PDf) showed a weaker correlation with T(1,obs) (positive, r2 = 0.53; P < 0.0001). The magnetization transfer ratio (MTR) showed a similarly strong correlation with F and a weaker correlation with PDf (r2 = 0.18; P < 0.04). CONCLUSION: T1 increases in chronic black holes strongly correlated with the decline in semisolid pool size, and somewhat less to the confounding effect of edema. MTR was less sensitive than T(1,obs) to liquid pool changes associated with edema.
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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 | 0.001 | 0.001 |
| 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".