Molecular imaging of the human pulmonary vascular endothelium in pulmonary hypertension: a phase II safety and proof of principle trial
Bibliographic record
Abstract
PURPOSE: The adrenomedullin receptor is densely expressed in the pulmonary vascular endothelium. PulmoBind, an adrenomedullin receptor ligand, was developed for molecular diagnosis of pulmonary vascular disease. We evaluated the safety of PulmoBind SPECT imaging and its capacity to detect pulmonary vascular disease associated with pulmonary hypertension (PH) in a human phase II study. METHODS: Tc-PulmoBind in supine position. Qualitative and semi-quantitative analyses of lung uptake were performed. Reproducibility of repeated testing was evaluated in controls after 1 month. RESULTS: PulmoBind injection was well tolerated without any serious adverse event. Imaging was markedly abnormal in PH with ∼50% of subjects showing moderate to severe heterogeneity of moderate to severe extent. The abnormalities were unevenly distributed between the right and left lungs as well as within each lung. Segmental defects compatible with pulmonary embolism were present in 7/7 subjects with CTEPH and in 2/23 subjects with PAH. There were no segmental defects in controls. The PulmoBind activity distribution index, a parameter indicative of heterogeneity, was elevated in PH (65% ± 28%) vs. controls (41% ± 13%, p = 0.0003). In the only subject with vasodilator-responsive idiopathic PAH, PulmoBind lung SPECT was completely normal. Repeated testing 1 month later in healthy controls was well tolerated and showed no significant variability of PulmoBind distribution. CONCLUSIONS: Tc-PulmoBind was safe. PulmoBind showed potential to detect both pulmonary embolism and abnormalities indicative of pulmonary vascular disease in PAH. Phase III studies with this novel tracer and direct comparisons to lung perfusion agents such as labeled macro-aggregates of albumin are needed. CLINICAL TRIAL: ClinicalTrials.gov, NCT02216279.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".