Hyperpolarized <sup>13</sup> C Metabolic MRI of the Human Heart
Bibliographic record
Abstract
Rationale: Altered cardiac energetics is known to play an important role in the progression toward heart failure. A noninvasive method for imaging metabolic markers that could be used in longitudinal studies would be useful for understanding therapeutic approaches that target metabolism. Objective: To demonstrate the first hyperpolarized 13 C metabolic magnetic resonance imaging of the human heart. Methods and Results: Four healthy subjects underwent conventional proton cardiac magnetic resonance imaging followed by 13 C imaging and spectroscopic acquisition immediately after intravenous administration of a 0.1 mmol/kg dose of hyperpolarized [1- 13 C]pyruvate. All subjects tolerated the procedure well with no adverse effects reported ≤1 month post procedure. The [1- 13 C]pyruvate signal appeared within the chambers but not within the muscle. Imaging of the downstream metabolites showed 13 C-bicarbonate signal mainly confined to the left ventricular myocardium, whereas the [1- 13 C]lactate signal appeared both within the chambers and in the myocardium. The mean 13 C image signal:noise ratio was 115 for [1- 13 C]pyruvate, 56 for 13 C-bicarbonate, and 53 for [1- 13 C]lactate. Conclusions: These results represent the first 13 C images of the human heart. The appearance of 13 C-bicarbonate signal after administration of hyperpolarized [1- 13 C]pyruvate was readily detected in this healthy cohort (n=4). This shows that assessment of pyruvate metabolism in vivo in humans is feasible using current technology. Clinical Trial Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT02648009.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".