Investigating exchange and multicomponent relaxation in fully‐balanced steady‐state free precession imaging
Bibliographic record
Abstract
PURPOSE: To investigate the effect of chemical exchange and multicomponent relaxation on the rapid T(2) mapping method, DESPOT2 (driven equilibrium single pulse observation of T(2)) and the steady-state free precession (SSFP) sequence upon which it is based. Although capable of rapid T(2) determination, an assumption implicit of the method is single-component relaxation. In many biological tissues (such as white and gray matter), it is well established that the T(2) decay curve is more accurately described by the summation of more than one relaxation species. MATERIALS AND METHODS: The effects of exchange were first incorporated into the general SSFP magnetization expressions and its effect on the measured SSFP signal investigated using Bloch-McConnell simulations. Corresponding imaging experiments were performed to support the presented theory. RESULTS: Simulations show the measured multicomponent SSFP signal may be expressed as a linear summation of signal from each species under usual imaging conditions where the repetition time is much less than T(2). Imaging experiments performed using dairy cream demonstrate strong agreement with the presented theory. Finally, using a dairy cream model, we demonstrate quantification of multicomponent relaxation from multiangle SSFP data for the first time, showing good agreement with reference spin-echo values. CONCLUSION: SSFP and DESPOT2 may provide a new method for investigating multicomponent systems, such as human brain, and disease processes, such as multiple sclerosis.
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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".