Using hyperpolarized <sup>3</sup>He MRI to evaluate treatment efficacy in cystic fibrosis patients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To use hyperpolarized (HP) (3)He MR imaging to assess functional lung ventilation in subjects with cystic fibrosis (CF) before and after treatment. MATERIALS AND METHODS: We performed HP (3)He static ventilation MRI scans on three subjects, using a Philips 3.0 Tesla (T) Achieva MRI scanner, before and after 11 days of in-patient treatment with combined intravenous and inhaled therapies for pulmonary exacerbations of CF. We also collected spirometry data. We quantified pulmonary ventilation volume measured with HP (3)He MRI using an advanced semi-automated analysis technique. RESULTS: Following 11 days of treatment with intravenous antibiotics, hypertonic saline, and rhDNase, HP (3)He MR images in one subject displayed a 25% increase in total ventilation volume. Total ventilation volume in the other two subjects slightly decreased. All three subjects showed increases in FEV(1) and FVC following treatment. CONCLUSION: In all subjects, the HP (3)He MR images provided detailed information on precisely where in the lungs gas was reaching. These data provide additional support for the conclusion that HP noble gas MRI can be a powerful tool for evaluating lung ventilation in patients with cystic fibrosis, but also raise important questions about the correlation between spirometry and HP gas MRI measurements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it