New <sup>133</sup>Xe Gas Trapping Index for Quantifying Severe Emphysema Before Partial Lung Volume Reduction
Bibliographic record
Abstract
UNLABELLED: Lung volume reduction (LVR) is an effective therapy for end-stage emphysema. Preliminary and postprocedure imaging is usually limited to CT for anatomic delineation of the location and severity of the most acutely affected lung zones. The purpose of this study was to investigate the potential of using a new quantitative gas trapping index (GTI) derived from a (133)Xe ventilation scan to assess the severity of emphysema. METHODS: Using the equilibration and washout phases of a (133)Xe ventilation study, a GTI was compared with visual National Emphysema Treatment Trial (NETT) CT scoring, semiautomated CT densitometry, and (99m)Tc perfusion scintigraphy in 28 patients being evaluated for LVR. The GTI was calculated as the percentage of (133)Xe gas retention in a 3-min washout image compared with the peak equilibrium image for 6 lung zones. RESULTS: The GTI correlated best with the percentage of perfusion (-0.39, P<0.0001) and the CT density scoring with the percentage of severe emphysema (0.36, P<0.0001). There was less correlation with visual NETT CT scores (0.25, P<0.001). CONCLUSION: This GTI, based on widely available (133)Xe imaging, shows good correlation with other quantitative measures of emphysema that are anatomically based. Because this GTI provides a more functional assessment of gas trapping and airway disease, these results suggest that additional study is warranted to investigate its use as a functional measure of emphysema before and after LVR.
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.
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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".