Cerebral and myocardial kinetics of [11C]acetoacetate and [11C]β-hydroxybutyrate: A comparative crossover study in healthy rats
Bibliographic record
Abstract
Ketone metabolism has been studied using positron emission tomography (PET) with the radiotracers [ 11 C]acetoacetate and [ 11 C]β-hydroxybutyrate. However, whether these two radiotracers actually yield equivalent estimates of cerebral and myocardial ketone metabolism has not yet been investigated. This study aimed to investigate and compare the kinetics of both tracers in the brain and heart of healthy rats under varying levels of circulating ketones at baseline and after a single-dose exogenous ketone ester (KE) supplement. Six healthy Sprague-Dawley rats each underwent two scans with each tracer: one following oral KE administration and one with a placebo. Cerebral kinetic parameters ( K i , V T , and cerebral metabolic rate (CMR)) were obtained using the Patlak method, whereas myocardial kinetic parameters ( K 1 , k 2 , and V T ) were derived using a 1-tissue compartment model. Parameters were compared through mixed-effects, correlation, and Bland-Altman analyses. Global CMR increased 3–4-fold in the KE group versus placebo, with strong positive correlations between CMR and plasma ketone levels for both tracers. Correlations between [ 11 C]acetoacetate and [ 11 C]β-hydroxybutyrate were moderate and non-significant for relative cerebral uptake expressed as K i (ρ = 0.40) and for V T (ρ = 0.38) but strongly positive for absolute uptake, CMR ( r = 0.84), with a non-significant mean bias of −0.03. In contrast, myocardial kinetics showed only non-significant weak to moderate correlations between the radiotracers ( K 1 ( r = 0.04), k 2 ( r = −0.27), and V T (ρ = 0.43)), with no systematic biases. [ 11 C]acetoacetate and [ 11 C]β-hydroxybutyrate can be used interchangeably for measuring global CMR in healthy rats but differ in certain cerebral and myocardial kinetics. Whether these findings are generalizable to pathological conditions warrants further studies to explore the kinetics of these tracers in disease models.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".