Supplementary Material for: A Novel Method of Estimating Small Airway Disease Using Inspiratory-to-Expiratory Computed Tomography
Background: Disease accumulates in the small airways without being detected by conventional measurements. Objectives: To quantify small airway disease using a novel computed tomography (CT) inspiratory-to-expiratory approach called the disease probability measure (DPM) and to investigate the associa...
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creator | Kirby, M. Yin, Y. Tschirren, J. Tan, W.C. Leipsic, J. Hague, C.J. Bourbeau, J. Sin, D.D. Hogg, J.C. Coxson, H.O. For The CanCOLD Collaborative Research Group And The Canadian Respiratory Research Network |
description | Background: Disease accumulates in the small airways without being detected by conventional measurements. Objectives: To quantify small airway disease using a novel computed tomography (CT) inspiratory-to-expiratory approach called the disease probability measure (DPM) and to investigate the association with pulmonary function measurements. Methods: Participants from the population-based CanCOLD study were evaluated using full-inspiration/full-expiration CT and pulmonary function measurements. Full-inspiration and full-expiration CT images were registered, and each voxel was classified as emphysema, gas trapping (GasTrap) related to functional small airway disease, or normal using two classification approaches: parametric response map (PRM) and DPM (VIDA Diagnostics, Inc., Coralville, IA, USA). Results: The participants included never-smokers (n = 135), at risk (n = 97), Global Initiative for Chronic Obstructive Lung Disease I (GOLD I) (n = 140), and GOLD II chronic obstructive pulmonary disease (n = 96). PRMGasTrap and DPMGasTrap measurements were significantly elevated in GOLD II compared to never-smokers (p < 0.01) and at risk (p < 0.01), and for GOLD I compared to at risk (p < 0.05). Gas trapping measurements were significantly elevated in GOLD II compared to GOLD I (p < 0.0001) using the DPM classification only. Overall, DPM classified significantly more voxels as gas trapping than PRM (p < 0.0001); a spatial comparison revealed that the expiratory CT Hounsfield units (HU) for voxels classified as DPMGasTrap but PRMNormal (PRMNormal- DPMGasTrap = -785 ± 72 HU) were significantly reduced compared to voxels classified normal by both approaches (PRMNormal-DPMNormal = -722 ± 89 HU; p < 0.0001). DPM and PRMGasTrap measurements showed similar, significantly associations with forced expiratory volume in 1 s (FEV1) (p < 0.01), FEV1/forced vital capacity (p < 0.0001), residual volume/total lung capacity (p < 0.0001), bronchodilator response (p < 0.0001), and dyspnea (p < 0.05). Conclusion: CT inspiratory-to-expiratory gas trapping measurements are significantly associated with pulmonary function and symptoms. There are quantitative and spatial differences between PRM and DPM classification that need pathological investigation. |
doi_str_mv | 10.6084/m9.figshare.5335966 |
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fullrecord | <record><control><sourceid>datacite_PQ8</sourceid><recordid>TN_cdi_datacite_primary_10_6084_m9_figshare_5335966</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>10_6084_m9_figshare_5335966</sourcerecordid><originalsourceid>FETCH-datacite_primary_10_6084_m9_figshare_53359663</originalsourceid><addsrcrecordid>eNqdjzFOw0AQRbehQMAJaOYCNo5MLJwuSoygCE1CvRrhsb3Srmc1OwG25OYQKbkA1dfX19PXM-Z-UZVN9fT4ENpycGOaUKhc1vWybZpr87M_xugp0KwoGXaoJA49DCwrWMMbf5KHHenEPfAAXVIXUN08wj6g97B28oUZti4RJoL3dJpe5xSdoLLkQrnovi8NNhziUamHAwceBeOUb83VgD7R3TlvTP3cHTYvRY-KH07JRvn7lGwXlT2J2NDai4g9i9T_o34B7otejQ</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>image</recordtype></control><display><type>image</type><title>Supplementary Material for: A Novel Method of Estimating Small Airway Disease Using Inspiratory-to-Expiratory Computed Tomography</title><source>DataCite</source><creator>Kirby, M. ; Yin, Y. ; Tschirren, J. ; Tan, W.C. ; Leipsic, J. ; Hague, C.J. ; Bourbeau, J. ; Sin, D.D. ; Hogg, J.C. ; Coxson, H.O. ; For The CanCOLD Collaborative Research Group And The Canadian Respiratory Research Network</creator><creatorcontrib>Kirby, M. ; Yin, Y. ; Tschirren, J. ; Tan, W.C. ; Leipsic, J. ; Hague, C.J. ; Bourbeau, J. ; Sin, D.D. ; Hogg, J.C. ; Coxson, H.O. ; For The CanCOLD Collaborative Research Group And The Canadian Respiratory Research Network</creatorcontrib><description><![CDATA[Background: Disease accumulates in the small airways without being detected by conventional measurements. Objectives: To quantify small airway disease using a novel computed tomography (CT) inspiratory-to-expiratory approach called the disease probability measure (DPM) and to investigate the association with pulmonary function measurements. Methods: Participants from the population-based CanCOLD study were evaluated using full-inspiration/full-expiration CT and pulmonary function measurements. Full-inspiration and full-expiration CT images were registered, and each voxel was classified as emphysema, gas trapping (GasTrap) related to functional small airway disease, or normal using two classification approaches: parametric response map (PRM) and DPM (VIDA Diagnostics, Inc., Coralville, IA, USA). Results: The participants included never-smokers (n = 135), at risk (n = 97), Global Initiative for Chronic Obstructive Lung Disease I (GOLD I) (n = 140), and GOLD II chronic obstructive pulmonary disease (n = 96). PRMGasTrap and DPMGasTrap measurements were significantly elevated in GOLD II compared to never-smokers (p < 0.01) and at risk (p < 0.01), and for GOLD I compared to at risk (p < 0.05). Gas trapping measurements were significantly elevated in GOLD II compared to GOLD I (p < 0.0001) using the DPM classification only. Overall, DPM classified significantly more voxels as gas trapping than PRM (p < 0.0001); a spatial comparison revealed that the expiratory CT Hounsfield units (HU) for voxels classified as DPMGasTrap but PRMNormal (PRMNormal- DPMGasTrap = -785 ± 72 HU) were significantly reduced compared to voxels classified normal by both approaches (PRMNormal-DPMNormal = -722 ± 89 HU; p < 0.0001). DPM and PRMGasTrap measurements showed similar, significantly associations with forced expiratory volume in 1 s (FEV1) (p < 0.01), FEV1/forced vital capacity (p < 0.0001), residual volume/total lung capacity (p < 0.0001), bronchodilator response (p < 0.0001), and dyspnea (p < 0.05). Conclusion: CT inspiratory-to-expiratory gas trapping measurements are significantly associated with pulmonary function and symptoms. There are quantitative and spatial differences between PRM and DPM classification that need pathological investigation.]]></description><identifier>DOI: 10.6084/m9.figshare.5335966</identifier><language>eng</language><publisher>Karger Publishers</publisher><subject>Medicine</subject><creationdate>2017</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>776,1887</link.rule.ids><linktorsrc>$$Uhttps://commons.datacite.org/doi.org/10.6084/m9.figshare.5335966$$EView_record_in_DataCite.org$$FView_record_in_$$GDataCite.org$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Kirby, M.</creatorcontrib><creatorcontrib>Yin, Y.</creatorcontrib><creatorcontrib>Tschirren, J.</creatorcontrib><creatorcontrib>Tan, W.C.</creatorcontrib><creatorcontrib>Leipsic, J.</creatorcontrib><creatorcontrib>Hague, C.J.</creatorcontrib><creatorcontrib>Bourbeau, J.</creatorcontrib><creatorcontrib>Sin, D.D.</creatorcontrib><creatorcontrib>Hogg, J.C.</creatorcontrib><creatorcontrib>Coxson, H.O.</creatorcontrib><creatorcontrib>For The CanCOLD Collaborative Research Group And The Canadian Respiratory Research Network</creatorcontrib><title>Supplementary Material for: A Novel Method of Estimating Small Airway Disease Using Inspiratory-to-Expiratory Computed Tomography</title><description><![CDATA[Background: Disease accumulates in the small airways without being detected by conventional measurements. Objectives: To quantify small airway disease using a novel computed tomography (CT) inspiratory-to-expiratory approach called the disease probability measure (DPM) and to investigate the association with pulmonary function measurements. Methods: Participants from the population-based CanCOLD study were evaluated using full-inspiration/full-expiration CT and pulmonary function measurements. Full-inspiration and full-expiration CT images were registered, and each voxel was classified as emphysema, gas trapping (GasTrap) related to functional small airway disease, or normal using two classification approaches: parametric response map (PRM) and DPM (VIDA Diagnostics, Inc., Coralville, IA, USA). Results: The participants included never-smokers (n = 135), at risk (n = 97), Global Initiative for Chronic Obstructive Lung Disease I (GOLD I) (n = 140), and GOLD II chronic obstructive pulmonary disease (n = 96). PRMGasTrap and DPMGasTrap measurements were significantly elevated in GOLD II compared to never-smokers (p < 0.01) and at risk (p < 0.01), and for GOLD I compared to at risk (p < 0.05). Gas trapping measurements were significantly elevated in GOLD II compared to GOLD I (p < 0.0001) using the DPM classification only. Overall, DPM classified significantly more voxels as gas trapping than PRM (p < 0.0001); a spatial comparison revealed that the expiratory CT Hounsfield units (HU) for voxels classified as DPMGasTrap but PRMNormal (PRMNormal- DPMGasTrap = -785 ± 72 HU) were significantly reduced compared to voxels classified normal by both approaches (PRMNormal-DPMNormal = -722 ± 89 HU; p < 0.0001). DPM and PRMGasTrap measurements showed similar, significantly associations with forced expiratory volume in 1 s (FEV1) (p < 0.01), FEV1/forced vital capacity (p < 0.0001), residual volume/total lung capacity (p < 0.0001), bronchodilator response (p < 0.0001), and dyspnea (p < 0.05). Conclusion: CT inspiratory-to-expiratory gas trapping measurements are significantly associated with pulmonary function and symptoms. There are quantitative and spatial differences between PRM and DPM classification that need pathological investigation.]]></description><subject>Medicine</subject><fulltext>true</fulltext><rsrctype>image</rsrctype><creationdate>2017</creationdate><recordtype>image</recordtype><sourceid>PQ8</sourceid><recordid>eNqdjzFOw0AQRbehQMAJaOYCNo5MLJwuSoygCE1CvRrhsb3Srmc1OwG25OYQKbkA1dfX19PXM-Z-UZVN9fT4ENpycGOaUKhc1vWybZpr87M_xugp0KwoGXaoJA49DCwrWMMbf5KHHenEPfAAXVIXUN08wj6g97B28oUZti4RJoL3dJpe5xSdoLLkQrnovi8NNhziUamHAwceBeOUb83VgD7R3TlvTP3cHTYvRY-KH07JRvn7lGwXlT2J2NDai4g9i9T_o34B7otejQ</recordid><startdate>20170823</startdate><enddate>20170823</enddate><creator>Kirby, M.</creator><creator>Yin, Y.</creator><creator>Tschirren, J.</creator><creator>Tan, W.C.</creator><creator>Leipsic, J.</creator><creator>Hague, C.J.</creator><creator>Bourbeau, J.</creator><creator>Sin, D.D.</creator><creator>Hogg, J.C.</creator><creator>Coxson, H.O.</creator><creator>For The CanCOLD Collaborative Research Group And The Canadian Respiratory Research Network</creator><general>Karger Publishers</general><scope>DYCCY</scope><scope>PQ8</scope></search><sort><creationdate>20170823</creationdate><title>Supplementary Material for: A Novel Method of Estimating Small Airway Disease Using Inspiratory-to-Expiratory Computed Tomography</title><author>Kirby, M. ; Yin, Y. ; Tschirren, J. ; Tan, W.C. ; Leipsic, J. ; Hague, C.J. ; Bourbeau, J. ; Sin, D.D. ; Hogg, J.C. ; Coxson, H.O. ; For The CanCOLD Collaborative Research Group And The Canadian Respiratory Research Network</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-datacite_primary_10_6084_m9_figshare_53359663</frbrgroupid><rsrctype>images</rsrctype><prefilter>images</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Medicine</topic><toplevel>online_resources</toplevel><creatorcontrib>Kirby, M.</creatorcontrib><creatorcontrib>Yin, Y.</creatorcontrib><creatorcontrib>Tschirren, J.</creatorcontrib><creatorcontrib>Tan, W.C.</creatorcontrib><creatorcontrib>Leipsic, J.</creatorcontrib><creatorcontrib>Hague, C.J.</creatorcontrib><creatorcontrib>Bourbeau, J.</creatorcontrib><creatorcontrib>Sin, D.D.</creatorcontrib><creatorcontrib>Hogg, J.C.</creatorcontrib><creatorcontrib>Coxson, H.O.</creatorcontrib><creatorcontrib>For The CanCOLD Collaborative Research Group And The Canadian Respiratory Research Network</creatorcontrib><collection>DataCite (Open Access)</collection><collection>DataCite</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kirby, M.</au><au>Yin, Y.</au><au>Tschirren, J.</au><au>Tan, W.C.</au><au>Leipsic, J.</au><au>Hague, C.J.</au><au>Bourbeau, J.</au><au>Sin, D.D.</au><au>Hogg, J.C.</au><au>Coxson, H.O.</au><au>For The CanCOLD Collaborative Research Group And The Canadian Respiratory Research Network</au><format>book</format><genre>unknown</genre><ristype>GEN</ristype><title>Supplementary Material for: A Novel Method of Estimating Small Airway Disease Using Inspiratory-to-Expiratory Computed Tomography</title><date>2017-08-23</date><risdate>2017</risdate><abstract><![CDATA[Background: Disease accumulates in the small airways without being detected by conventional measurements. Objectives: To quantify small airway disease using a novel computed tomography (CT) inspiratory-to-expiratory approach called the disease probability measure (DPM) and to investigate the association with pulmonary function measurements. Methods: Participants from the population-based CanCOLD study were evaluated using full-inspiration/full-expiration CT and pulmonary function measurements. Full-inspiration and full-expiration CT images were registered, and each voxel was classified as emphysema, gas trapping (GasTrap) related to functional small airway disease, or normal using two classification approaches: parametric response map (PRM) and DPM (VIDA Diagnostics, Inc., Coralville, IA, USA). Results: The participants included never-smokers (n = 135), at risk (n = 97), Global Initiative for Chronic Obstructive Lung Disease I (GOLD I) (n = 140), and GOLD II chronic obstructive pulmonary disease (n = 96). PRMGasTrap and DPMGasTrap measurements were significantly elevated in GOLD II compared to never-smokers (p < 0.01) and at risk (p < 0.01), and for GOLD I compared to at risk (p < 0.05). Gas trapping measurements were significantly elevated in GOLD II compared to GOLD I (p < 0.0001) using the DPM classification only. Overall, DPM classified significantly more voxels as gas trapping than PRM (p < 0.0001); a spatial comparison revealed that the expiratory CT Hounsfield units (HU) for voxels classified as DPMGasTrap but PRMNormal (PRMNormal- DPMGasTrap = -785 ± 72 HU) were significantly reduced compared to voxels classified normal by both approaches (PRMNormal-DPMNormal = -722 ± 89 HU; p < 0.0001). DPM and PRMGasTrap measurements showed similar, significantly associations with forced expiratory volume in 1 s (FEV1) (p < 0.01), FEV1/forced vital capacity (p < 0.0001), residual volume/total lung capacity (p < 0.0001), bronchodilator response (p < 0.0001), and dyspnea (p < 0.05). Conclusion: CT inspiratory-to-expiratory gas trapping measurements are significantly associated with pulmonary function and symptoms. There are quantitative and spatial differences between PRM and DPM classification that need pathological investigation.]]></abstract><pub>Karger Publishers</pub><doi>10.6084/m9.figshare.5335966</doi><oa>free_for_read</oa></addata></record> |
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title | Supplementary Material for: A Novel Method of Estimating Small Airway Disease Using Inspiratory-to-Expiratory Computed Tomography |
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