<i>In vivo</i> magnetic resonance imaging of glucose – initial experience
Bibliographic record
Abstract
A new noninvasive, nonradioactive approach for glucose imaging using spin hyperpolarization technology and stable isotope labeling is presented. A glucose analog labeled with (13)C at all six positions increased the overall hyperpolarized imaging signal; deuteration at all seven directly bonded proton positions prolonged the spin-lattice relaxation time. High-bandwidth (13)C imaging overcame the large glucose carbon chemical shift dispersion. Hyperpolarized glucose images in the live rat showed time-dependent organ distribution patterns. At 8 s after the start of bolus injection, the inferior vena cava was demonstrated at angiographic quality. Distribution of hyperpolarized glucose in the kidneys, vasculature, and heart was demonstrated at 12 and 20 s. The heart-to-vasculature intensity ratio at 20 s suggests myocardial uptake. Cancer imaging, currently performed with (18)F-deoxyglucose positron emission tomography (FDG-PET), warrants further investigation, and glucose imaging could be useful in a vast range of clinical conditions and research fields where the radiation associated with the FDG-PET examination limits its use.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".