Pulmonary magnetic resonance imaging biomarkers of lung structure and function in adult survivors of bronchopulmonary dysplasia with COPD
Bibliographic record
Abstract
Bronchopulmonary dysplasia (BPD) is an emerging risk factor for chronic obstructive pulmonary disease. For BPD survivors, there are no guidelines for the management of lung disease that is often misdiagnosed as asthma. Pulmonary magnetic resonsance imaging (MRI) provides clinically-relevant lung biomarkers of ventilation abnormalities and emphysema. Here our objective was to quantify lung MRI biomarkers in adults with BPD to understand the underlying pathophysiologies responsible for their symptoms and abnormal pulmonary-function. We hypothesized that MRI measurements would be abnormal and reflect emphysema, not airways disease. Patients aged 20–29 year and born ≤32 weeks gestational age were included and those with MRI contraindications were excluded. A 25-year-old female never-smoker born <28 weeks gestation (S1) and a 27-year-old male ex-smoker born ~30 weeks gestation (S2) provided written-informed-consent and underwent pulmonary-function-tests and MRI. Lung abnormalities were quantified using ventilation defect percent (VDP), apparent diffusion coefficients (ADC) and mean linear intercept (Lm). Forced expiratory volume-in 1 sec (S1 = 46%pred/S2 = 33%pred), residual-volume (S1 = 192%pred/S2 = 267%pred) and diffusing-capacity-of-the-lung-for-carbon-monoxide (S1 = 73%pred/S2 = 72%pred) were abnormal. Chest–X-ray and computed tomography (CT) revealed mild structural abnormalities, while MRI VDP (S1 = 6%/S2 = 10%), ADC (S1 = 0.36 cm2/s/S2 = 0.37 cm2/s) and Lm (S1 = 400 μm/S2 = 430 μm) were markedly abnormal with ventilation defects spatially concordant with regions of low MRI signal-intensity and greater Lm, reflecting emphysema and/or gas-trapping. In BPD survivors, MRI biomarkers have the potential to serve as intermediate endpoints and help evaluate therapy.
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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".