Self‐refocused spatial‐spectral pulse for positive contrast imaging of cells labeled with SPIO nanoparticles
Bibliographic record
Abstract
MRI has been used extensively to noninvasively track the location of cells labeled with superparamagnetic iron-oxide nanoparticles (SPIOs) in vivo. Typically, SPIOs are employed as a negative contrast agent which makes it difficult to differentiate labeled cells from extraneous sources of inhomogeneity and actual voids in the image. As a result, several novel approaches have been put forth to obtain positive contrast from SPIOs. One technique proposed by Cunningham et al. utilizes spectrally selective pulses to excite and refocus spins in the vicinity of the SPIOs. Although the frequency selectivity of this technique provides effective positive contrast, the lack of slice selectivity results in interfering signal from sources of off-resonance outside the slice of interest. We have developed a self-refocused spatial-spectral (SR-SPSP) pulse to achieve slice-selective spin-echo imaging of off-resonant spins. Using a self-refocused pulse affords flexibility in echo-time selection since the spin echo may be placed at any time after the end of the pulse. The spatial selectivity achieved by the SR-SPSP RF pulse eliminates background signal from out-of-slice regions and reduces the on-resonant water suppression requirements. Phantom and in vivo data demonstrate that positive contrast and slice-selectivity are achieved using this novel RF pulse.
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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".