The role of biomechanical anatomical modeling via computed tomography for identification of restrictive allograft syndrome
Bibliographic record
Abstract
Chronic lung allograft dysfunction (CLAD) reduces long-term graft survival. It is important to distinguish CLAD subtypes: bronchiolitis obliterans syndrome (BOS) and restrictive allograft syndrome (RAS) as RAS has a worse prognosis and accurate subtyping could facilitate targeted treatments. However, the current diagnosis of CLAD subtypes is based on pulmonary function test (PFT) results that reflect global estimates of lung function; anatomical modeling based on computed tomography (CT) has the potential to provide detailed analysis of global and regional lung function. The purpose of this study is to evaluate the utility of CT-based anatomical modeling for the identification of RAS. This retrospective study included 51 patients (CLAD: 17 BOS and 17 RAS, control: 17 No-CLAD). CT data were assessed using a biomechanical model-based platform (MORFEUS) to characterize changes in lung deformation between baseline and disease onset. Lung deformation demonstrated high sensitivity and specificity (>80%) in differentiating RAS from BOS (P<.0001) and No-CLAD (P<.0001). There were matching radiological reading and inward deformation abnormalities in 79% of lung sections in patients with RAS. Anatomical modeling is complementary to conventional assessment in the diagnosis of RAS and potentially provides quantitative data that can help in the characterization and detailed assessment of heterogeneous lung parenchymal disease.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".