CT of the Bronchopulmonary Veins in Patients With Superior Vena Cava or Left Brachiocephalic Vein Obstruction
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to show the arrangement and connections of the bronchopulmonary veins (i.e., vessels draining the bronchi, bronchioles, and pleura in patients with chronic superior vena cava (SVC) or left brachiocephalic vein (LBCV) obstruction using CT. MATERIALS AND METHODS: Contrast-enhanced CT scans of the chest of 16 patients with chronic SVC or LBCV obstruction were analyzed retrospectively. Scans were acquired using various standard protocols. The mean age of the patients (10 men and six women) was 63 years (range, 41-86 years). The causes of obstruction were malignancy (7/16, 44%), catheter-related thrombosis (7/16, 44%), chronic fibrosing mediastinitis (1/16, 6%), and unknown (1/16, 6%). RESULTS: The following sites were obstructed: SVC (9/16, 56%), SVC below the azygos vein (4/16, 25%), and lower LBCV (3/16, 19%). The bronchopulmonary veins were opacified via the brachiocephalic, azygos, or accessory hemiazygos veins or their branches. We observed long vessels that could be traced along the lateral mediastinum or alongside the trachea and central bronchi to their termination in the central pulmonary veins from the level of the ostia to segmental divisions. These vessels intercommunicated and gave rise to smaller veins contiguous with the walls of the bronchi and pulmonary arteries. The pulmonary venous connections of the bronchopulmonary veins were more frequent with the lower lobe pulmonary veins. Pericardial and esophageal veins were also opacified through the brachiocephalic or azygos veins and anastomosed commonly with the bronchopulmonary veins. CONCLUSION: The arrangement and connections of the bronchopulmonary veins in patients with chronic SVC or LBCV obstruction can be depicted by CT; these vessels form an intricate network connecting the systemic and pulmonary venous circulations and can act as systemic-pulmonary shunts.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".