In vivo single scan detection of both iron‐labeled cells and breast cancer metastases in the mouse brain using balanced steady‐state free precession imaging at 1.5 T
Bibliographic record
Abstract
PURPOSE: To simultaneously detect iron-labeled cancer cells and brain tumors in vivo in one scan, the balanced steady-state free precession (b-SSFP) imaging sequence was optimized at 1.5 T on mice developing brain metastases subsequent to the injection of micron-sized iron oxide particle-labeled human breast cancer cells. MATERIALS AND METHODS: b-SSFP sequence parameters (repetition time, flip angle, and receiver bandwidth) were varied and the signal-to-noise ratio, contrast between the brain and tumors, and the number of detected iron-labeled cells were evaluated. RESULTS: Optimal b-SSFP images were acquired with a 26 msec repetition time, 35° flip angle, and bandwidth of ±21 kHz. b-SSFP images were compared with T(2) -weighted 2D fast spin echo (FSE) and 3D spoiled gradient recalled echo (SPGR) images. The mean tumor-brain contrast-to-noise ratio and the ability to detect iron-labeled cells were the highest in the b-SSFP images. CONCLUSION: A single b-SSFP scan can be used to visualize both iron-labeled cells and brain metastases.
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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 | 0.000 |
| 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".