Quantitative CT Characteristics of Cluster ...
Type de document :
Article dans une revue scientifique
DOI :
PMID :
URL permanente :
Titre :
Quantitative CT Characteristics of Cluster Phenotypes in the Severe Asthma Research Program Cohorts.
Auteur(s) :
Trivedi, Abhaya P [Auteur]
Hall, Chase [Auteur]
Goss, Charles W [Auteur]
Lew, Daphne [Auteur]
Krings, James G [Auteur]
McGregor, Mary Clare [Auteur]
Samant, Maanasi [Auteur]
Sieren, Jered P [Auteur]
Li, Huashi [Auteur]
Schechtman, Ken B [Auteur]
Schirm, Joshua [Auteur]
McEleney, Stephen [Auteur]
Peterson, Sam [Auteur]
Moore, Wendy C [Auteur]
Bleecker, Eugene R [Auteur]
Meyers, Deborah A [Auteur]
Israel, Elliot [Auteur]
Washko, George R [Auteur]
Levy, Bruce D [Auteur]
Leader, Joseph K [Auteur]
Wenzel, Sally E [Auteur]
Fahy, John V [Auteur]
Schiebler, Mark L [Auteur]
Fain, Sean B [Auteur]
Jarjour, Nizar N [Auteur]
Mauger, David T [Auteur]
Reinhardt, Joseph M [Auteur]
Newell, John D [Auteur]
Hoffman, Eric A [Auteur]
Castro, Mario [Auteur]
Sheshadri, Ajay [Auteur]
Esnault, Stéphane [Auteur]
University of Wisconsin-Madison
Hall, Chase [Auteur]
Goss, Charles W [Auteur]
Lew, Daphne [Auteur]
Krings, James G [Auteur]
McGregor, Mary Clare [Auteur]
Samant, Maanasi [Auteur]
Sieren, Jered P [Auteur]
Li, Huashi [Auteur]
Schechtman, Ken B [Auteur]
Schirm, Joshua [Auteur]
McEleney, Stephen [Auteur]
Peterson, Sam [Auteur]
Moore, Wendy C [Auteur]
Bleecker, Eugene R [Auteur]
Meyers, Deborah A [Auteur]
Israel, Elliot [Auteur]
Washko, George R [Auteur]
Levy, Bruce D [Auteur]
Leader, Joseph K [Auteur]
Wenzel, Sally E [Auteur]
Fahy, John V [Auteur]
Schiebler, Mark L [Auteur]
Fain, Sean B [Auteur]
Jarjour, Nizar N [Auteur]
Mauger, David T [Auteur]
Reinhardt, Joseph M [Auteur]
Newell, John D [Auteur]
Hoffman, Eric A [Auteur]
Castro, Mario [Auteur]
Sheshadri, Ajay [Auteur]
Esnault, Stéphane [Auteur]
University of Wisconsin-Madison
Titre de la revue :
Radiology
Nom court de la revue :
Radiology
Numéro :
304
Pagination :
450-459
Date de publication :
2022-08-01
ISSN :
1527-1315
Mot(s)-clé(s) en anglais :
Asthma
Cross-Sectional Studies
Female
Humans
Lung
Phenotype
Pulmonary Disease, Chronic Obstructive
Retrospective Studies
Tomography, X-Ray Computed
Cross-Sectional Studies
Female
Humans
Lung
Phenotype
Pulmonary Disease, Chronic Obstructive
Retrospective Studies
Tomography, X-Ray Computed
Discipline(s) HAL :
Sciences du Vivant [q-bio]
Résumé en anglais : [en]
Background Clustering key clinical characteristics of participants in the Severe Asthma Research Program (SARP), a large, multicenter prospective observational study of patients with asthma and healthy controls, has led ...
Lire la suite >Background Clustering key clinical characteristics of participants in the Severe Asthma Research Program (SARP), a large, multicenter prospective observational study of patients with asthma and healthy controls, has led to the identification of novel asthma phenotypes. Purpose To determine whether quantitative CT (qCT) could help distinguish between clinical asthma phenotypes. Materials and Methods A retrospective cross-sectional analysis was conducted with the use of qCT images (maximal bronchodilation at total lung capacity [TLC], or inspiration, and functional residual capacity [FRC], or expiration) from the cluster phenotypes of SARP participants (cluster 1: minimal disease; cluster 2: mild, reversible; cluster 3: obese asthma; cluster 4: severe, reversible; cluster 5: severe, irreversible) enrolled between September 2001 and December 2015. Airway morphometry was performed along standard paths (RB1, RB4, RB10, LB1, and LB10). Corresponding voxels from TLC and FRC images were mapped with use of deformable image registration to characterize disease probability maps (DPMs) of functional small airway disease (fSAD), voxel-level volume changes (Jacobian), and isotropy (anisotropic deformation index [ADI]). The association between cluster assignment and qCT measures was evaluated using linear mixed models. Results A total of 455 participants were evaluated with cluster assignments and CT (mean age ± SD, 42.1 years ± 14.7; 270 women). Airway morphometry had limited ability to help discern between clusters. DPM fSAD was highest in cluster 5 (cluster 1 in SARP III: 19.0% ± 20.6; cluster 2: 18.9% ± 13.3; cluster 3: 24.9% ± 13.1; cluster 4: 24.1% ± 8.4; cluster 5: 38.8% ± 14.4; < .001). Lower whole-lung Jacobian and ADI values were associated with greater cluster severity. Compared to cluster 1, cluster 5 lung expansion was 31% smaller (Jacobian in SARP III cohort: 2.31 ± 0.6 vs 1.61 ± 0.3, respectively, < .001) and 34% more isotropic (ADI in SARP III cohort: 0.40 ± 0.1 vs 0.61 ± 0.2, < .001). Within-lung Jacobian and ADI SDs decreased as severity worsened (Jacobian SD in SARP III cohort: 0.90 ± 0.4 for cluster 1; 0.79 ± 0.3 for cluster 2; 0.62 ± 0.2 for cluster 3; 0.63 ± 0.2 for cluster 4; and 0.41 ± 0.2 for cluster 5; < .001). Conclusion Quantitative CT assessments of the degree and intraindividual regional variability of lung expansion distinguished between well-established clinical phenotypes among participants with asthma from the Severe Asthma Research Program study. © RSNA, 2022 See also the editorial by Verschakelen in this issue.Lire moins >
Lire la suite >Background Clustering key clinical characteristics of participants in the Severe Asthma Research Program (SARP), a large, multicenter prospective observational study of patients with asthma and healthy controls, has led to the identification of novel asthma phenotypes. Purpose To determine whether quantitative CT (qCT) could help distinguish between clinical asthma phenotypes. Materials and Methods A retrospective cross-sectional analysis was conducted with the use of qCT images (maximal bronchodilation at total lung capacity [TLC], or inspiration, and functional residual capacity [FRC], or expiration) from the cluster phenotypes of SARP participants (cluster 1: minimal disease; cluster 2: mild, reversible; cluster 3: obese asthma; cluster 4: severe, reversible; cluster 5: severe, irreversible) enrolled between September 2001 and December 2015. Airway morphometry was performed along standard paths (RB1, RB4, RB10, LB1, and LB10). Corresponding voxels from TLC and FRC images were mapped with use of deformable image registration to characterize disease probability maps (DPMs) of functional small airway disease (fSAD), voxel-level volume changes (Jacobian), and isotropy (anisotropic deformation index [ADI]). The association between cluster assignment and qCT measures was evaluated using linear mixed models. Results A total of 455 participants were evaluated with cluster assignments and CT (mean age ± SD, 42.1 years ± 14.7; 270 women). Airway morphometry had limited ability to help discern between clusters. DPM fSAD was highest in cluster 5 (cluster 1 in SARP III: 19.0% ± 20.6; cluster 2: 18.9% ± 13.3; cluster 3: 24.9% ± 13.1; cluster 4: 24.1% ± 8.4; cluster 5: 38.8% ± 14.4; < .001). Lower whole-lung Jacobian and ADI values were associated with greater cluster severity. Compared to cluster 1, cluster 5 lung expansion was 31% smaller (Jacobian in SARP III cohort: 2.31 ± 0.6 vs 1.61 ± 0.3, respectively, < .001) and 34% more isotropic (ADI in SARP III cohort: 0.40 ± 0.1 vs 0.61 ± 0.2, < .001). Within-lung Jacobian and ADI SDs decreased as severity worsened (Jacobian SD in SARP III cohort: 0.90 ± 0.4 for cluster 1; 0.79 ± 0.3 for cluster 2; 0.62 ± 0.2 for cluster 3; 0.63 ± 0.2 for cluster 4; and 0.41 ± 0.2 for cluster 5; < .001). Conclusion Quantitative CT assessments of the degree and intraindividual regional variability of lung expansion distinguished between well-established clinical phenotypes among participants with asthma from the Severe Asthma Research Program study. © RSNA, 2022 See also the editorial by Verschakelen in this issue.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
Université de Lille
Inserm
CHU Lille
Inserm
CHU Lille
Collections :
Date de dépôt :
2023-10-21T11:33:57Z
2023-12-06T10:34:58Z
2023-12-06T10:34:58Z
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