Evaluation of Lung Glucose Uptake with Fluorine-18 Fluorodeoxyglucose Positron Emission Tomography/CT in Patients with Pulmonary Arterial Hypertension and Pulmonary Hypertension Due to Left Heart Disease
Bibliographic record
Abstract
Aim: Previous studies have demonstrated increased glucose uptake by 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) in lung parenchyma in animal models or small pulmonary arterial hypertension (PAH) cohorts. However, it is not well known whether increased FDG uptake in the lung is a unique phenomenon in PAH or whether elevated pulmonary artery pressure (PAP) induces FDG uptake.Methods and results: Nineteen patients with PAH, 8 patients with pulmonary hypertension due to left heart disease (PH-LHD), and 14 age matched control subjects were included. All PH patients underwent right heart catheterization and FDG-PET. The mean standard uptake value (SUV g/mL) of FDG in each lung was obtained and average values of both lungs were calculated as mean lung FDG SUV. The correlation between hemodynamics and mean lung FDG SUV was also analyzed in PH patients. Mean PAP (mPAP) was not significantly different between PAH and PH-LHD (45 ± 11 vs 43 ± 5 mmHg, p=0.51). PAH patients demonstrated significantly increased mean lung FDG SUV compared with PH-LHD and controls (PAH: 0.76 ± 0.26 vs PH-LHD: 0.51 ± 0.12 vs controls: 0.53 ± 0.16, p=0.0025). The mean lung FDG SUV did not correlate with mPAP either in PAH or PH-LHD.Conclusion: PAH is associated with increased lung FDG uptake indicating increased glucose utilization in the lung. This may represent metabolic shift to glycolysis and/or active inflammation in the remodeled pulmonary vasculature, and is observed to a greater extent in PAH than in patients with PH secondary to LHD and control subjects without PH.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".