Investigating the Relationship Between Central Computer Tomography Airway Tree Features and Small Airways Disease in Chronic Obstructive Pulmonary Disease
Notice bibliographique
Résumé
Rationale: Chronic Obstructive Pulmonary Disease (COPD) results in remodeling of both the large and small airways. Computed tomography (CT) imaging allows quantification of morphometric features from the central airways to be measured directly from a single full-inspiration acquisition, and small airway disease (SAD) features indirectly by registering full-inspiration to full-expiration images, known as Disease Probability Measure (DPM SAD ). Our objective is to investigate the relationship between CT central airway tree and DPM SAD features in COPD. Methods: Full-inspiration and full-expiration CT images were obtained from the Canadian Cohort of Obstructive Lung Disease (CanCOLD) study. Image registration and airway segmentation was performed (VIDA Diagnostics Inc.). Central CT airway tree features were generated in each of the 19 bronchopulmonary segments, including measurements reflecting the airway dimensions (lumen diameter, wall area, total airway count, airway tapering), the direction (branch angle, directional cosines) and statistical features (mean, min, max of a given feature). CT DPM SAD measurements were generated by co-registration of full-inspiration to full-expiration CT images. Each voxel was classified as either normal, emphysema or SAD and expressed as the percentage of the total lung volume. DPM SAD was generated in each bronchopulmonary segment to be spatially matched with the regional airway features. For statistical analysis, airway features with high collinearity (r>0.70) were removed. The remaining features were inputted into a mixed effects beta regression model treating participants and bronchopulmonary segments as random effects and the airway features as fixed effects. A null model without airway tree features was generated to compare the AIC and BIC values to assess model fit and a likelihood ratio test was performed. Results: A total of 318 participants were evaluated: n=17 Healthy, n=92 At-Risk, n=114 mild COPD, and n=95 with moderate-severe COPD. A total of 79 features were extracted from central airways; after adjusting for collinearity 16 features remained. Of the remaining features, 8/16 were significantly associated with DPM SAD measurements in the mixed effects beta regression model (P<0.05). There was a significant difference (P<0.0001) between the null model (AIC=-8859.8, BIC=-8827.0) and the airway tree model (AIC=-9967.9, BIC=-9830.1). Significant airway features included: average wall thickness (=0.039), max and min wall thickness using the major diameter (=0.017, =-0.031, respectively), total airway count (=-0.020), airway tapering (=0.019), and directional cosines of the airway in each direction (X: =-0.032,Y: =-0.175, Z: =-0.164). Conclusion: Central airway tree features were associated with measurements reflecting small airway disease.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».