Conventional High-resolution CT Versus Contiguous Multidetector CT in the Detection of Bronchiolitis Obliterans Syndrome in Lung Transplant Recipients
Bibliographic record
Abstract
OBJECTIVE: To compare the detection rate of pulmonary abnormalities between conventional high-resolution computed tomography (HRCT) and high-resolution multidetector computed tomography (MDCT) in lung transplant recipients and to correlate a composite computed tomography (CT) score with bronchiolitis obliterans syndrome (BOS) stage. METHODS: Twenty-four lung transplant recipients (12 single/12 double lung transplants, 13 males/11 females, mean age: 53 y, range: 28 to 71) underwent contiguous 16-slice high-resolution MDCT of the lungs at maximal inspiration and maximal expiration. Eight reformatted image sets were reconstructed: (i) contiguous 1-mm slice MDCT image set in the transverse, sagittal, and coronal image planes at maximal inspiration; (ii) contiguous 1-mm slice MDCT image set in the transverse, sagittal, and coronal image planes at maximal expiration; (iii) conventional HRCT image set of 1-mm slices every 10 mm at maximal inspiration; and (iv) conventional expiratory HRCT of 1-mm slices at 3 selected levels at maximal expiration. Individual pulmonary abnormalities were added to give a composite CT score. Individual abnormalities and the composite CT score were correlated with BOS stage, as based on functional testing of airflow obstruction, for each of the 8 image sets. RESULTS: Transverse, sagittal, and coronal MDCT correlated significantly with BOS stage (R=0.46, 0.49, 0.52, respectively), whereas conventional HRCT did not. Multiple regression analysis demonstrated that transverse MDCT was the only independent predictor of BOS stage (R=0.33, P<0.01). Interobserver agreement for composite CT scores for HRCT, transverse, sagittal, and coronal MDCT were R2=0.89, 0.87, 0.83 and 0.80, respectively. Interobserver agreement for individual abnormalities was better with MDCT than with conventional HRCT. CONCLUSIONS: In lung transplant recipients, high-resolution MDCT detects significantly more pulmonary abnormalities and has better interobserver agreement than conventional HRCT and is an independent predictor of BOS stage.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".