The computed tomographic “tree‐in‐bud” pattern: Characterization and comparison with radiographic and clinical findings in 36 cats
Bibliographic record
Abstract
In humans, a CT "tree-in-bud" pattern has been described as a characteristic of centrilobular bronchiolar dilation, with bronchiolar plugging by mucus, pus, or fluid. Aims of this retrospective, descriptive, multi-center study were to characterize the CT appearance of a "tree-in-bud" pattern in a group of cats, and compare this pattern with radiographic and clinical findings. Databases from four hospitals were searched during the period of January 2012 to September 2015 and cats with thoracic radiographs, thoracic CT scans and CT reports describing findings consistent with a "tree-in-bud" pattern were included. Images were reviewed by two veterinary radiologists and characteristics were recorded based on consensus. Clinical findings were recorded by one observer from each center. Thirty-six cats met inclusion criteria. Six cats were asymptomatic, 12 were diagnosed with bronchial disease and 23 were suspected to have bronchial disease. Right cranial and right caudal lung lobes were most commonly affected on both imaging modalities. Localization of the "tree-in-bud" pattern was most often peripheral. On radiographs, the CT "tree-in-bud" pattern often appeared as soft-tissue opacity nodules; their number and affected pulmonary segments were often underestimated compared with CT. In conclusion, the "tree-in-bud" pattern should be considered as a differential diagnosis for radiographic soft tissue opaque nodules in feline lungs. Based on lesion localization and presence or suspicion of a concomitant bronchial disease for cats in this sample, authors propose that the CT "tree-in-bud" pattern described in humans is also a characteristic of bronchial or bronchiolar plugging and bronchial disease in cats.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".