Relaxometry model of strong dipolar perturbers for balanced‐SSFP: Application to quantification of SPIO loaded cells
Bibliographic record
Abstract
Magnetic resonance microscopy using magnetically labeled cells is an emerging discipline offering the potential for non-destructive studies targeting numerous cellular events in medical research. The present work develops a technique to quantify superparamagnetic iron-oxide (SPIO) loaded cells using fully balanced steady state free precession (b-SSFP) imaging. An analytic model based on phase cancellation was derived for a single particle and extended to predict mono-exponential decay versus echo time in the presence of multiple randomly distributed particles. Numerical models verified phase incoherence as the dominant contrast mechanism and evaluated the model using a full range of tissue decay rates, repetition times, and flip angles. Numerical simulations indicated a relaxation rate enhancement (DeltaR(2b)=0.412 gamma . LMD) proportional to LMD, the local magnetic dose (the additional sample magnetization due to the SPIO particles), a quantity related to the concentration of contrast agent. A phantom model of SPIO loaded cells showed excellent agreement with simulations, demonstrated comparable sensitivity to gradient echo DeltaR(*) (2) enhancements, and 14 times the sensitivity of spin echo DeltaR(2) measurements. We believe this model can be used to facilitate the generation of quantitative maps of targeted cell populations.
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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 | 0.001 |
| 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".