On the parameters affecting the sensitivity of MR measures of pressure with microbubbles
Bibliographic record
Abstract
Recently, it has been suggested that gas encapsulated distensible microbubbles may serve as pressure probes in the MR field through the relationship between bubble size and 1/T(2) or 1/T(*)(2). Currently, in vivo application of this technique is hindered by the ability of T(2) or T(*)(2) to detect pressure changes that are clinically relevant. This work identifies and characterizes, through numerical simulations, the set of parameters which optimize the ability of this technique to detect small pressure changes. Results show that when the bubbles do not interact magnetically, the T(2)- and T(*)(2)-based measurements of pressure are strongly influenced by the bubble size at atmospheric pressure, static magnetic field strength, magnitude of the susceptibility difference between the encapsulated gas and plasma, bubble volume fraction, and the refocusing interval. In particular, to detect clinically relevant pressure changes, microbubbles need to be approximately 2-3 microm in radius, distributed at a volume fraction of 0.15%, and have a volumetric magnetic susceptibility difference of at least 34 ppm.
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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 | 0.001 |
| 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".