Chronic hypersensitivity pneumonitis: identification of key prognostic determinants using automated CT analysis
Background Chronic hypersensitivity pneumonitis (CHP) has a variable disease course. Computer analysis of CT features was used to identify a subset of CHP patients with an outcome similar to patients with idiopathic pulmonary fibrosis (IPF). Methods Consecutive patients with a multi-disciplinary tea...
Ausführliche Beschreibung
Autor*in: |
Jacob, Joseph [verfasserIn] |
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Englisch |
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2017 |
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© The Author(s). 2017 |
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Übergeordnetes Werk: |
Enthalten in: BMC pulmonary medicine - London : BioMed Central, 2001, 17(2017), 1 vom: 04. Mai |
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Übergeordnetes Werk: |
volume:17 ; year:2017 ; number:1 ; day:04 ; month:05 |
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DOI / URN: |
10.1186/s12890-017-0418-2 |
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SPR027996433 |
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520 | |a Background Chronic hypersensitivity pneumonitis (CHP) has a variable disease course. Computer analysis of CT features was used to identify a subset of CHP patients with an outcome similar to patients with idiopathic pulmonary fibrosis (IPF). Methods Consecutive patients with a multi-disciplinary team diagnosis of CHP (n = 116) had pulmonary function tests (FEV1, FVC, DLco, Kco, and a composite physiologic index [CPI]) and CT variables predictive of mortality evaluated by analysing visual and computer-based (CALIPER) parenchymal features: total interstitial lung disease (ILD) extent, honeycombing, reticular pattern, ground glass opacities, pulmonary vessel volume (PVV), emphysema, and traction bronchiectasis. Mean survival was compared between both CHP and IPF patients (n = 185). Results In CHP, visual/CALIPER measures of reticular pattern, honeycombing, visual traction bronchiectasis, and CALIPER ILD extent were predictive of mortality (p < 0 · 05) on univariate analysis. PVV was strongly predictive of mortality on univariate (p < 0 · 0001) and multivariate analysis independent of age, gender and disease severity (represented by the CPI [p < 0 · 01]). CHP patients with a PVV threshold >6 · 5% of the lung had a mean survival (35 · 3 ± 6 · 1 months; n = 20/116 [17%]) and rate of disease progression that closely matched IPF patients (38 · 4 ± 2 · 2 months; n = 185). Conclusions Pulmonary vessel volume can identify CHP patients at risk of aggressive disease and a poor IPF-like prognosis. | ||
650 | 4 | |a Chronic hypersensitivity pneumonitis |7 (dpeaa)DE-He213 | |
650 | 4 | |a Pulmonary vessel volume |7 (dpeaa)DE-He213 | |
650 | 4 | |a Idiopathic pulmonary fibrosis |7 (dpeaa)DE-He213 | |
650 | 4 | |a Quantitative CT analysis |7 (dpeaa)DE-He213 | |
700 | 1 | |a Bartholmai, Brian J. |4 aut | |
700 | 1 | |a Egashira, Ryoko |4 aut | |
700 | 1 | |a Brun, Anne Laure |4 aut | |
700 | 1 | |a Rajagopalan, Srinivasan |4 aut | |
700 | 1 | |a Karwoski, Ronald |4 aut | |
700 | 1 | |a Kokosi, Maria |4 aut | |
700 | 1 | |a Hansell, David M. |4 aut | |
700 | 1 | |a Wells, Athol U. |4 aut | |
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10.1186/s12890-017-0418-2 doi (DE-627)SPR027996433 (SPR)s12890-017-0418-2-e DE-627 ger DE-627 rakwb eng Jacob, Joseph verfasserin (orcid)0000-0002-8054-2293 aut Chronic hypersensitivity pneumonitis: identification of key prognostic determinants using automated CT analysis 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2017 Background Chronic hypersensitivity pneumonitis (CHP) has a variable disease course. Computer analysis of CT features was used to identify a subset of CHP patients with an outcome similar to patients with idiopathic pulmonary fibrosis (IPF). Methods Consecutive patients with a multi-disciplinary team diagnosis of CHP (n = 116) had pulmonary function tests (FEV1, FVC, DLco, Kco, and a composite physiologic index [CPI]) and CT variables predictive of mortality evaluated by analysing visual and computer-based (CALIPER) parenchymal features: total interstitial lung disease (ILD) extent, honeycombing, reticular pattern, ground glass opacities, pulmonary vessel volume (PVV), emphysema, and traction bronchiectasis. Mean survival was compared between both CHP and IPF patients (n = 185). Results In CHP, visual/CALIPER measures of reticular pattern, honeycombing, visual traction bronchiectasis, and CALIPER ILD extent were predictive of mortality (p < 0 · 05) on univariate analysis. PVV was strongly predictive of mortality on univariate (p < 0 · 0001) and multivariate analysis independent of age, gender and disease severity (represented by the CPI [p < 0 · 01]). CHP patients with a PVV threshold >6 · 5% of the lung had a mean survival (35 · 3 ± 6 · 1 months; n = 20/116 [17%]) and rate of disease progression that closely matched IPF patients (38 · 4 ± 2 · 2 months; n = 185). Conclusions Pulmonary vessel volume can identify CHP patients at risk of aggressive disease and a poor IPF-like prognosis. Chronic hypersensitivity pneumonitis (dpeaa)DE-He213 Pulmonary vessel volume (dpeaa)DE-He213 Idiopathic pulmonary fibrosis (dpeaa)DE-He213 Quantitative CT analysis (dpeaa)DE-He213 Bartholmai, Brian J. aut Egashira, Ryoko aut Brun, Anne Laure aut Rajagopalan, Srinivasan aut Karwoski, Ronald aut Kokosi, Maria aut Hansell, David M. aut Wells, Athol U. aut Enthalten in BMC pulmonary medicine London : BioMed Central, 2001 17(2017), 1 vom: 04. Mai (DE-627)335489125 (DE-600)2059871-3 1471-2466 nnns volume:17 year:2017 number:1 day:04 month:05 https://dx.doi.org/10.1186/s12890-017-0418-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2017 1 04 05 |
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10.1186/s12890-017-0418-2 doi (DE-627)SPR027996433 (SPR)s12890-017-0418-2-e DE-627 ger DE-627 rakwb eng Jacob, Joseph verfasserin (orcid)0000-0002-8054-2293 aut Chronic hypersensitivity pneumonitis: identification of key prognostic determinants using automated CT analysis 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2017 Background Chronic hypersensitivity pneumonitis (CHP) has a variable disease course. Computer analysis of CT features was used to identify a subset of CHP patients with an outcome similar to patients with idiopathic pulmonary fibrosis (IPF). Methods Consecutive patients with a multi-disciplinary team diagnosis of CHP (n = 116) had pulmonary function tests (FEV1, FVC, DLco, Kco, and a composite physiologic index [CPI]) and CT variables predictive of mortality evaluated by analysing visual and computer-based (CALIPER) parenchymal features: total interstitial lung disease (ILD) extent, honeycombing, reticular pattern, ground glass opacities, pulmonary vessel volume (PVV), emphysema, and traction bronchiectasis. Mean survival was compared between both CHP and IPF patients (n = 185). Results In CHP, visual/CALIPER measures of reticular pattern, honeycombing, visual traction bronchiectasis, and CALIPER ILD extent were predictive of mortality (p < 0 · 05) on univariate analysis. PVV was strongly predictive of mortality on univariate (p < 0 · 0001) and multivariate analysis independent of age, gender and disease severity (represented by the CPI [p < 0 · 01]). CHP patients with a PVV threshold >6 · 5% of the lung had a mean survival (35 · 3 ± 6 · 1 months; n = 20/116 [17%]) and rate of disease progression that closely matched IPF patients (38 · 4 ± 2 · 2 months; n = 185). Conclusions Pulmonary vessel volume can identify CHP patients at risk of aggressive disease and a poor IPF-like prognosis. Chronic hypersensitivity pneumonitis (dpeaa)DE-He213 Pulmonary vessel volume (dpeaa)DE-He213 Idiopathic pulmonary fibrosis (dpeaa)DE-He213 Quantitative CT analysis (dpeaa)DE-He213 Bartholmai, Brian J. aut Egashira, Ryoko aut Brun, Anne Laure aut Rajagopalan, Srinivasan aut Karwoski, Ronald aut Kokosi, Maria aut Hansell, David M. aut Wells, Athol U. aut Enthalten in BMC pulmonary medicine London : BioMed Central, 2001 17(2017), 1 vom: 04. Mai (DE-627)335489125 (DE-600)2059871-3 1471-2466 nnns volume:17 year:2017 number:1 day:04 month:05 https://dx.doi.org/10.1186/s12890-017-0418-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2017 1 04 05 |
allfields_unstemmed |
10.1186/s12890-017-0418-2 doi (DE-627)SPR027996433 (SPR)s12890-017-0418-2-e DE-627 ger DE-627 rakwb eng Jacob, Joseph verfasserin (orcid)0000-0002-8054-2293 aut Chronic hypersensitivity pneumonitis: identification of key prognostic determinants using automated CT analysis 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2017 Background Chronic hypersensitivity pneumonitis (CHP) has a variable disease course. Computer analysis of CT features was used to identify a subset of CHP patients with an outcome similar to patients with idiopathic pulmonary fibrosis (IPF). Methods Consecutive patients with a multi-disciplinary team diagnosis of CHP (n = 116) had pulmonary function tests (FEV1, FVC, DLco, Kco, and a composite physiologic index [CPI]) and CT variables predictive of mortality evaluated by analysing visual and computer-based (CALIPER) parenchymal features: total interstitial lung disease (ILD) extent, honeycombing, reticular pattern, ground glass opacities, pulmonary vessel volume (PVV), emphysema, and traction bronchiectasis. Mean survival was compared between both CHP and IPF patients (n = 185). Results In CHP, visual/CALIPER measures of reticular pattern, honeycombing, visual traction bronchiectasis, and CALIPER ILD extent were predictive of mortality (p < 0 · 05) on univariate analysis. PVV was strongly predictive of mortality on univariate (p < 0 · 0001) and multivariate analysis independent of age, gender and disease severity (represented by the CPI [p < 0 · 01]). CHP patients with a PVV threshold >6 · 5% of the lung had a mean survival (35 · 3 ± 6 · 1 months; n = 20/116 [17%]) and rate of disease progression that closely matched IPF patients (38 · 4 ± 2 · 2 months; n = 185). Conclusions Pulmonary vessel volume can identify CHP patients at risk of aggressive disease and a poor IPF-like prognosis. Chronic hypersensitivity pneumonitis (dpeaa)DE-He213 Pulmonary vessel volume (dpeaa)DE-He213 Idiopathic pulmonary fibrosis (dpeaa)DE-He213 Quantitative CT analysis (dpeaa)DE-He213 Bartholmai, Brian J. aut Egashira, Ryoko aut Brun, Anne Laure aut Rajagopalan, Srinivasan aut Karwoski, Ronald aut Kokosi, Maria aut Hansell, David M. aut Wells, Athol U. aut Enthalten in BMC pulmonary medicine London : BioMed Central, 2001 17(2017), 1 vom: 04. Mai (DE-627)335489125 (DE-600)2059871-3 1471-2466 nnns volume:17 year:2017 number:1 day:04 month:05 https://dx.doi.org/10.1186/s12890-017-0418-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2017 1 04 05 |
allfieldsGer |
10.1186/s12890-017-0418-2 doi (DE-627)SPR027996433 (SPR)s12890-017-0418-2-e DE-627 ger DE-627 rakwb eng Jacob, Joseph verfasserin (orcid)0000-0002-8054-2293 aut Chronic hypersensitivity pneumonitis: identification of key prognostic determinants using automated CT analysis 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2017 Background Chronic hypersensitivity pneumonitis (CHP) has a variable disease course. Computer analysis of CT features was used to identify a subset of CHP patients with an outcome similar to patients with idiopathic pulmonary fibrosis (IPF). Methods Consecutive patients with a multi-disciplinary team diagnosis of CHP (n = 116) had pulmonary function tests (FEV1, FVC, DLco, Kco, and a composite physiologic index [CPI]) and CT variables predictive of mortality evaluated by analysing visual and computer-based (CALIPER) parenchymal features: total interstitial lung disease (ILD) extent, honeycombing, reticular pattern, ground glass opacities, pulmonary vessel volume (PVV), emphysema, and traction bronchiectasis. Mean survival was compared between both CHP and IPF patients (n = 185). Results In CHP, visual/CALIPER measures of reticular pattern, honeycombing, visual traction bronchiectasis, and CALIPER ILD extent were predictive of mortality (p < 0 · 05) on univariate analysis. PVV was strongly predictive of mortality on univariate (p < 0 · 0001) and multivariate analysis independent of age, gender and disease severity (represented by the CPI [p < 0 · 01]). CHP patients with a PVV threshold >6 · 5% of the lung had a mean survival (35 · 3 ± 6 · 1 months; n = 20/116 [17%]) and rate of disease progression that closely matched IPF patients (38 · 4 ± 2 · 2 months; n = 185). Conclusions Pulmonary vessel volume can identify CHP patients at risk of aggressive disease and a poor IPF-like prognosis. Chronic hypersensitivity pneumonitis (dpeaa)DE-He213 Pulmonary vessel volume (dpeaa)DE-He213 Idiopathic pulmonary fibrosis (dpeaa)DE-He213 Quantitative CT analysis (dpeaa)DE-He213 Bartholmai, Brian J. aut Egashira, Ryoko aut Brun, Anne Laure aut Rajagopalan, Srinivasan aut Karwoski, Ronald aut Kokosi, Maria aut Hansell, David M. aut Wells, Athol U. aut Enthalten in BMC pulmonary medicine London : BioMed Central, 2001 17(2017), 1 vom: 04. Mai (DE-627)335489125 (DE-600)2059871-3 1471-2466 nnns volume:17 year:2017 number:1 day:04 month:05 https://dx.doi.org/10.1186/s12890-017-0418-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2017 1 04 05 |
allfieldsSound |
10.1186/s12890-017-0418-2 doi (DE-627)SPR027996433 (SPR)s12890-017-0418-2-e DE-627 ger DE-627 rakwb eng Jacob, Joseph verfasserin (orcid)0000-0002-8054-2293 aut Chronic hypersensitivity pneumonitis: identification of key prognostic determinants using automated CT analysis 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2017 Background Chronic hypersensitivity pneumonitis (CHP) has a variable disease course. Computer analysis of CT features was used to identify a subset of CHP patients with an outcome similar to patients with idiopathic pulmonary fibrosis (IPF). Methods Consecutive patients with a multi-disciplinary team diagnosis of CHP (n = 116) had pulmonary function tests (FEV1, FVC, DLco, Kco, and a composite physiologic index [CPI]) and CT variables predictive of mortality evaluated by analysing visual and computer-based (CALIPER) parenchymal features: total interstitial lung disease (ILD) extent, honeycombing, reticular pattern, ground glass opacities, pulmonary vessel volume (PVV), emphysema, and traction bronchiectasis. Mean survival was compared between both CHP and IPF patients (n = 185). Results In CHP, visual/CALIPER measures of reticular pattern, honeycombing, visual traction bronchiectasis, and CALIPER ILD extent were predictive of mortality (p < 0 · 05) on univariate analysis. PVV was strongly predictive of mortality on univariate (p < 0 · 0001) and multivariate analysis independent of age, gender and disease severity (represented by the CPI [p < 0 · 01]). CHP patients with a PVV threshold >6 · 5% of the lung had a mean survival (35 · 3 ± 6 · 1 months; n = 20/116 [17%]) and rate of disease progression that closely matched IPF patients (38 · 4 ± 2 · 2 months; n = 185). Conclusions Pulmonary vessel volume can identify CHP patients at risk of aggressive disease and a poor IPF-like prognosis. Chronic hypersensitivity pneumonitis (dpeaa)DE-He213 Pulmonary vessel volume (dpeaa)DE-He213 Idiopathic pulmonary fibrosis (dpeaa)DE-He213 Quantitative CT analysis (dpeaa)DE-He213 Bartholmai, Brian J. aut Egashira, Ryoko aut Brun, Anne Laure aut Rajagopalan, Srinivasan aut Karwoski, Ronald aut Kokosi, Maria aut Hansell, David M. aut Wells, Athol U. aut Enthalten in BMC pulmonary medicine London : BioMed Central, 2001 17(2017), 1 vom: 04. Mai (DE-627)335489125 (DE-600)2059871-3 1471-2466 nnns volume:17 year:2017 number:1 day:04 month:05 https://dx.doi.org/10.1186/s12890-017-0418-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2017 1 04 05 |
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Computer analysis of CT features was used to identify a subset of CHP patients with an outcome similar to patients with idiopathic pulmonary fibrosis (IPF). Methods Consecutive patients with a multi-disciplinary team diagnosis of CHP (n = 116) had pulmonary function tests (FEV1, FVC, DLco, Kco, and a composite physiologic index [CPI]) and CT variables predictive of mortality evaluated by analysing visual and computer-based (CALIPER) parenchymal features: total interstitial lung disease (ILD) extent, honeycombing, reticular pattern, ground glass opacities, pulmonary vessel volume (PVV), emphysema, and traction bronchiectasis. Mean survival was compared between both CHP and IPF patients (n = 185). Results In CHP, visual/CALIPER measures of reticular pattern, honeycombing, visual traction bronchiectasis, and CALIPER ILD extent were predictive of mortality (p < 0 · 05) on univariate analysis. PVV was strongly predictive of mortality on univariate (p < 0 · 0001) and multivariate analysis independent of age, gender and disease severity (represented by the CPI [p < 0 · 01]). CHP patients with a PVV threshold >6 · 5% of the lung had a mean survival (35 · 3 ± 6 · 1 months; n = 20/116 [17%]) and rate of disease progression that closely matched IPF patients (38 · 4 ± 2 · 2 months; n = 185). 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Jacob, Joseph misc Chronic hypersensitivity pneumonitis misc Pulmonary vessel volume misc Idiopathic pulmonary fibrosis misc Quantitative CT analysis Chronic hypersensitivity pneumonitis: identification of key prognostic determinants using automated CT analysis |
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Chronic hypersensitivity pneumonitis: identification of key prognostic determinants using automated CT analysis Chronic hypersensitivity pneumonitis (dpeaa)DE-He213 Pulmonary vessel volume (dpeaa)DE-He213 Idiopathic pulmonary fibrosis (dpeaa)DE-He213 Quantitative CT analysis (dpeaa)DE-He213 |
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chronic hypersensitivity pneumonitis: identification of key prognostic determinants using automated ct analysis |
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Chronic hypersensitivity pneumonitis: identification of key prognostic determinants using automated CT analysis |
abstract |
Background Chronic hypersensitivity pneumonitis (CHP) has a variable disease course. Computer analysis of CT features was used to identify a subset of CHP patients with an outcome similar to patients with idiopathic pulmonary fibrosis (IPF). Methods Consecutive patients with a multi-disciplinary team diagnosis of CHP (n = 116) had pulmonary function tests (FEV1, FVC, DLco, Kco, and a composite physiologic index [CPI]) and CT variables predictive of mortality evaluated by analysing visual and computer-based (CALIPER) parenchymal features: total interstitial lung disease (ILD) extent, honeycombing, reticular pattern, ground glass opacities, pulmonary vessel volume (PVV), emphysema, and traction bronchiectasis. Mean survival was compared between both CHP and IPF patients (n = 185). Results In CHP, visual/CALIPER measures of reticular pattern, honeycombing, visual traction bronchiectasis, and CALIPER ILD extent were predictive of mortality (p < 0 · 05) on univariate analysis. PVV was strongly predictive of mortality on univariate (p < 0 · 0001) and multivariate analysis independent of age, gender and disease severity (represented by the CPI [p < 0 · 01]). CHP patients with a PVV threshold >6 · 5% of the lung had a mean survival (35 · 3 ± 6 · 1 months; n = 20/116 [17%]) and rate of disease progression that closely matched IPF patients (38 · 4 ± 2 · 2 months; n = 185). Conclusions Pulmonary vessel volume can identify CHP patients at risk of aggressive disease and a poor IPF-like prognosis. © The Author(s). 2017 |
abstractGer |
Background Chronic hypersensitivity pneumonitis (CHP) has a variable disease course. Computer analysis of CT features was used to identify a subset of CHP patients with an outcome similar to patients with idiopathic pulmonary fibrosis (IPF). Methods Consecutive patients with a multi-disciplinary team diagnosis of CHP (n = 116) had pulmonary function tests (FEV1, FVC, DLco, Kco, and a composite physiologic index [CPI]) and CT variables predictive of mortality evaluated by analysing visual and computer-based (CALIPER) parenchymal features: total interstitial lung disease (ILD) extent, honeycombing, reticular pattern, ground glass opacities, pulmonary vessel volume (PVV), emphysema, and traction bronchiectasis. Mean survival was compared between both CHP and IPF patients (n = 185). Results In CHP, visual/CALIPER measures of reticular pattern, honeycombing, visual traction bronchiectasis, and CALIPER ILD extent were predictive of mortality (p < 0 · 05) on univariate analysis. PVV was strongly predictive of mortality on univariate (p < 0 · 0001) and multivariate analysis independent of age, gender and disease severity (represented by the CPI [p < 0 · 01]). CHP patients with a PVV threshold >6 · 5% of the lung had a mean survival (35 · 3 ± 6 · 1 months; n = 20/116 [17%]) and rate of disease progression that closely matched IPF patients (38 · 4 ± 2 · 2 months; n = 185). Conclusions Pulmonary vessel volume can identify CHP patients at risk of aggressive disease and a poor IPF-like prognosis. © The Author(s). 2017 |
abstract_unstemmed |
Background Chronic hypersensitivity pneumonitis (CHP) has a variable disease course. Computer analysis of CT features was used to identify a subset of CHP patients with an outcome similar to patients with idiopathic pulmonary fibrosis (IPF). Methods Consecutive patients with a multi-disciplinary team diagnosis of CHP (n = 116) had pulmonary function tests (FEV1, FVC, DLco, Kco, and a composite physiologic index [CPI]) and CT variables predictive of mortality evaluated by analysing visual and computer-based (CALIPER) parenchymal features: total interstitial lung disease (ILD) extent, honeycombing, reticular pattern, ground glass opacities, pulmonary vessel volume (PVV), emphysema, and traction bronchiectasis. Mean survival was compared between both CHP and IPF patients (n = 185). Results In CHP, visual/CALIPER measures of reticular pattern, honeycombing, visual traction bronchiectasis, and CALIPER ILD extent were predictive of mortality (p < 0 · 05) on univariate analysis. PVV was strongly predictive of mortality on univariate (p < 0 · 0001) and multivariate analysis independent of age, gender and disease severity (represented by the CPI [p < 0 · 01]). CHP patients with a PVV threshold >6 · 5% of the lung had a mean survival (35 · 3 ± 6 · 1 months; n = 20/116 [17%]) and rate of disease progression that closely matched IPF patients (38 · 4 ± 2 · 2 months; n = 185). Conclusions Pulmonary vessel volume can identify CHP patients at risk of aggressive disease and a poor IPF-like prognosis. © The Author(s). 2017 |
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Bartholmai, Brian J. Egashira, Ryoko Brun, Anne Laure Rajagopalan, Srinivasan Karwoski, Ronald Kokosi, Maria Hansell, David M. Wells, Athol U. |
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Computer analysis of CT features was used to identify a subset of CHP patients with an outcome similar to patients with idiopathic pulmonary fibrosis (IPF). Methods Consecutive patients with a multi-disciplinary team diagnosis of CHP (n = 116) had pulmonary function tests (FEV1, FVC, DLco, Kco, and a composite physiologic index [CPI]) and CT variables predictive of mortality evaluated by analysing visual and computer-based (CALIPER) parenchymal features: total interstitial lung disease (ILD) extent, honeycombing, reticular pattern, ground glass opacities, pulmonary vessel volume (PVV), emphysema, and traction bronchiectasis. Mean survival was compared between both CHP and IPF patients (n = 185). Results In CHP, visual/CALIPER measures of reticular pattern, honeycombing, visual traction bronchiectasis, and CALIPER ILD extent were predictive of mortality (p < 0 · 05) on univariate analysis. PVV was strongly predictive of mortality on univariate (p < 0 · 0001) and multivariate analysis independent of age, gender and disease severity (represented by the CPI [p < 0 · 01]). CHP patients with a PVV threshold >6 · 5% of the lung had a mean survival (35 · 3 ± 6 · 1 months; n = 20/116 [17%]) and rate of disease progression that closely matched IPF patients (38 · 4 ± 2 · 2 months; n = 185). Conclusions Pulmonary vessel volume can identify CHP patients at risk of aggressive disease and a poor IPF-like prognosis.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Chronic hypersensitivity pneumonitis</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Pulmonary vessel volume</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Idiopathic pulmonary fibrosis</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Quantitative CT analysis</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Bartholmai, Brian J.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Egashira, Ryoko</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Brun, Anne Laure</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Rajagopalan, Srinivasan</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Karwoski, Ronald</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kokosi, Maria</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hansell, David M.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wells, Athol U.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">BMC pulmonary medicine</subfield><subfield code="d">London : BioMed Central, 2001</subfield><subfield code="g">17(2017), 1 vom: 04. 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