Dual‐temporal resolution dynamic contrast‐enhanced MRI protocol for blood–brain barrier permeability measurement in enhancing multiple sclerosis lesions
Bibliographic record
Abstract
PURPOSE: To design a more accurate and reproducible technique for the measurement of blood-brain barrier (BBB) permeability in gadolinium-enhancing multiple sclerosis (MS) lesions. MATERIALS AND METHODS: Four MS patients were scanned using a new dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) protocol based on an uninterrupted two-part acquisition consisting of an initial part at high temporal and low spatial resolutions and a second part at low temporal and high spatial resolutions. The method preserves both the high spatial resolution needed for the often small size of lesions and the high temporal resolution required during the first minute after injection to sufficiently sample the first-pass bolus. Simulations compared the performance of this new protocol with the conventional one at low temporal and high spatial resolutions throughout. RESULTS: The BBB permeability estimates changed by up to 33% between the two protocols. The new protocol led to simulated error on K(trans) of 7%-10%, versus 7%-30% with the conventional protocol, and was more robust with respect to offsets between acquisition and injection start times, differences in shape of the first-pass peak, and permeability values. CONCLUSION: The dual-temporal resolution protocol produces improved BBB permeability estimates and provides a more complete view of active inflammatory MS lesion pathology.
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 | 0.003 | 0.002 |
| 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 | 0.001 |
| 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 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".