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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".