Repeatable Noninvasive Measurement of Mouse Myocardial Glucose Uptake with <sup>18</sup>F-FDG: Evaluation of Tracer Kinetics in a Type 1 Diabetes Model
Bibliographic record
Abstract
UNLABELLED: A noninvasive and repeatable method for assessing mouse myocardial glucose uptake with (18)F-FDG PET and Patlak kinetic analysis was systematically assessed using the vena cava image-derived blood input function (IDIF). METHODS: Contrast CT and computer modeling was used to determine the vena cava recovery coefficient. Vena cava IDIF (n = 7) was compared with the left ventricular cavity IDIF, with blood and liver activity measured ex vivo at 60 min. The test-retest repeatability (n = 9) of Patlak influx constant K(i) at 10-40 min was assessed quantitatively using Bland-Altman analysis. Myocardial glucose uptake rates (rMGU) using the vena cava IDIF were calculated at baseline (n = 8), after induction of type 1 diabetes (streptozotocin [50 mg/kg] intraperitoneally, 5 d), and after acute insulin stimulation (0.08 mU/kg of body weight intraperitoneally). These changes were analyzed with a standardized uptake value calculation at 20 and 40 min after injection to correlate to the Patlak time interval. RESULTS: The proximal mouse vena cava diameter was 2.54 ± 0.30 mm. The estimated recovery coefficient, calculated using nonlinear image reconstruction, decreased from 0.76 initially (time 0 to peak activity) to 0.61 for the duration of the scan. There was a 17% difference in the image-derived vena cava blood activity at 60 min, compared with the ex vivo blood activity measured in the γ-counter. The coefficient of variability for Patlak K(i) values between mice was found to be 23% with the proposed method, compared with 51% when using the left ventricular cavity IDIF (P < 0.05). No significant bias in K(i) was found between repeated scans with a coefficient of repeatability of 0.16 mL/min/g. Calculated rMGU values were reduced by 60% in type 1 diabetic mice from baseline scans (P < 0.03, ANOVA), with a subsequent increase of 40% to a level not significantly different from baseline after acute insulin treatment. These results were confirmed with a standardized uptake value measured at 20 and 40 min. CONCLUSION: The mouse vena cava IDIF provides repeatable assessment of the blood time-activity curve for Patlak kinetic modeling of rMGU. An expected significant reduction in myocardial glucose uptake was demonstrated in a type 1 diabetic mouse model, with significant recovery after acute insulin treatment, using a mouse vena cava IDIF approach.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".