Pulmonary Imaging Biomarkers of Gas Trapping and Emphysema in COPD:<sup>3</sup>He MR Imaging and CT Parametric Response Maps
Notice bibliographique
Résumé
PURPOSE: To directly compare magnetic resonance (MR) imaging and computed tomography (CT) parametric response map (PRM) measurements of gas trapping and emphysema in ex-smokers both with and without chronic obstructive pulmonary disease (COPD). MATERIALS AND METHODS: Participants provided written informed consent to a protocol that was approved by a local research ethics board and Health Canada and was compliant with the HIPAA (Institutional Review Board Reg. #00000940). The prospectively planned study was performed from March 2014 to December 2014 and included 58 ex-smokers (mean age, 73 years ± 9) with (n = 32; mean age, 74 years ± 7) and without (n = 26; mean age, 70 years ± 11) COPD. MR imaging (at functional residual capacity plus 1 L), CT (at full inspiration and expiration), and spirometry or plethysmography were performed during a 2-hour visit to generate ventilation defect percent (VDP), apparent diffusion coefficient (ADC), and PRM gas trapping and emphysema measurements. The relationships between pulmonary function and imaging measurements were determined with analysis of variance (ANOVA), Holm-Bonferroni corrected Pearson correlations, multivariate regression modeling, and the spatial overlap coefficient (SOC). RESULTS: VDP, ADC, and PRM gas trapping and emphysema (ANOVA, P < .001) measurements were significantly different in healthy ex-smokers than they were in ex-smokers with COPD. In all ex-smokers, VDP was correlated with PRM gas trapping (r = 0.58, P < .001) and with PRM emphysema (r = 0.68, P < .001). VDP was also significantly correlated with PRM in ex-smokers with COPD (gas trapping: r = 0.47 and P = .03; emphysema: r = 0.62 and P < .001) but not in healthy ex-smokers. In a multivariate model that predicted PRM gas trapping, the forced expiratory volume in 1 second normalized to the forced vital capacity (standardized coefficients [βS] = -0.69, P = .001) and airway wall area percent (βS = -0.22, P = .02) were significant predictors. PRM emphysema was predicted by the diffusing capacity for carbon monoxide (βS = -0.29, P = .03) and VDP (βS = 0.41, P = .001). Helium 3 ADC values were significantly elevated in PRM gas-trapping regions (P < .001). The spatial relationship for ventilation defects was significantly greater with PRM gas trapping than with PRM emphysema in patients with mild (for gas trapping, SOC = 36% ± 28; for emphysema, SOC = 1% ± 2; P = .001) and moderate (for gas trapping, SOC = 34% ± 28; for emphysema, SOC = 7% ± 15; P = .006) COPD. For severe COPD, the spatial relationship for ventilation defects with PRM emphysema (SOC = 64% ± 30) was significantly greater than that for PRM gas trapping (SOC = 36% ± 18; P = .01). CONCLUSION: In all ex-smokers, ADC values were significantly elevated in regions of PRM gas trapping, and VDP was quantitatively and spatially related to both PRM gas trapping and PRM emphysema. In patients with mild to moderate COPD, VDP was related to PRM gas trapping, whereas in patients with severe COPD, VDP correlated with both PRM gas trapping and PRM emphysema.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| 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) | 0,001 | 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 ».