Quantifying lung morphology with respiratory-gated micro-CT in a murine model of emphysema
Bibliographic record
Abstract
Non-invasive micro-CT imaging techniques have been developed to investigate lung structure in free-breathing rodents. In this study, we investigate the utility of retrospectively respiratory-gated micro-CT imaging in an emphysema model to determine if anatomical changes could be observed in the image-derived quantitative analysis at two respiratory phases. The emphysema model chosen was a well-characterized, genetically altered model (TIMP-3 knockout mice) that exhibits a homogeneous phenotype. Micro-CT scans of the free-breathing, anaesthetized mice were obtained in 50 s and retrospectively respiratory sorted and reconstructed, providing 3D images representing peak inspiration and end expiration with 0.15 mm isotropic voxel spacing. Anatomical measurements included the volume and CT density of the lungs and the volume of the major airways, along with the diameters of the trachea, left bronchus and right bronchus. From these measurements, functional parameters such as functional residual capacity and tidal volume were calculated. Significant differences between the wild-type and TIMP-3 knockout groups were observed for measurements of CT density over the entire lung, indicating increased air content in the lungs of TIMP-3 knockout mice. These results demonstrate retrospective respiratory-gated micro-CT, providing images at multiple respiratory phases that can be analyzed quantitatively to investigate anatomical changes in murine models of emphysema.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".