Application of low-dose FDG-PET/MRI for quantification of lung changes in pediatric patients with cystic fibrosis: a new inflammatory index
Bibliographic record
Abstract
Background: Clinical severity and progression of lung disease in cystic fibrosis (CF) are significantly influenced by the degree of lung inflammation. Non-invasive quantitative diagnostic tools are desirable to differentiate structural and inflammatory lung changes in order to help prevent chronic airway disease. This might also be helpful for the evaluation of longitudinal effects of novel therapeutics. Therefore, the present study assesses the quantification of inflammatory lung changes using positron emission tomography/magnetic resonance imaging (PET/MRI) of the lung in children and adolescents with CF and evaluates the possible impact of PET/MRI on individualized therapy management. Methods: F-FDG) of 1 MBq/kgBW (mean effective dose, 1.3±0.4 mSv). Lesions of increased uptake were quantified based on standardized uptake values (SUV) and compared to background activity, liver and blood pool. Pulmonary changes were assessed using the established magnetic resonance imaging-CF (MR-CF) score and correlated to inflammatory lesions. Results were correlated to changes in therapy (initiation, modification or discontinuation of therapy after baseline-PET/MRI) based on the electronic medical records. Results: Uptake was highly increased in 5 cases, moderate in 4 cases, low in 7 cases, no uptake in 3 cases. Most MR-CF score points were assigned to peribronchitis (23%) and air trapping (23%). Metabolically increased lesions were mainly interpreted as consolidations (59%; P<0.001) and mucus plugging (19%, P=0.024). There was a decrease in mean number and volumes of inflammatory lesions (P=0.016 each) and MR-CF score (P=0.047) between baseline and follow-up. After PET/MRI, therapy changed in 18 cases (95%; new medication: 58%, n=11; termination of therapy: 16%, n=3; modification of therapy: 21%, n=4). Conclusions: In selected cases, pulmonary FDG-PET/MRI can help guide therapeutic decision-making and provide complementary information on CF-related lung changes to conventional MRI at a low radiation exposure.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".