Pulmonary Artery Remodeling and Advanced Hemodynamics: Magnetic Resonance Imaging Biomarkers of Pulmonary Hypertension
Bibliographic record
Abstract
Poorly characterized by non-invasive diagnostic imaging techniques, pulmonary hypertension (PHT) is commonly associated with changes in vascular hemodynamics and remodeling of pulmonary artery architecture. These disease phenotypes represent potential biomarkers of interest in clinical environment. In this retrospective clinical study, 33 patients with pulmonary hypertension and seventeen controls were recruited. Architectural remodeling was characterized using 3D-contrast enhanced angiogram via the measurement of pulmonary artery diameters, bifurcation distances, and angles. Hemodynamics were characterized using 4D-flow magnetic resonance imaging (MRI) via wall shear stress, kinetic energy, vorticity, and directional flow dynamics. Parameters were compared using independent samples student’s t-tests. Correlational analysis was performed using Pearson’s correlation. PHT patients demonstrated dilation in the main and right branch of the pulmonary artery (p < 0.05). Furthermore, these patients also exhibited increases in bifurcation distances in the left and right pulmonary arteries (p < 0.05). Wall shear stress, maximum kinetic energy, and energy loss were decreased in the pulmonary artery (p < 0.001). Correlations were observed between peak velocities and right ventricle ejection fraction (r = 0.527, p < 0.05). These findings suggest that pulmonary artery remodeling and hemodynamic changes may possess clinical utility as MRI biomarkers for PHT.
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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 | 0.000 | 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".