Validation of a computed tomography diagnostic model for differentiating fibrotic hypersensitivity pneumonitis from idiopathic pulmonary fibrosis
The diagnosis of fibrotic hypersensitivity pneumonitis (fHP) from other interstitial lung diseases, particularly idiopathic pulmonary fibrosis (IPF), is often difficult. This study aimed to examine computed tomography (CT) findings that were useful for differentiating between fHP and IPF and to deve...
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| Veröffentlicht in: | Respiratory investigation 2024-09, Vol.62 (5), p.798-803 |
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| creator | Sumikawa, Hiromitsu Komiya, Kosaku Egashira, Ryoko Tominaga, Junya Ueno, Midori Fukuda, Taiki Yamada, Daisuke Takei, Reoto Kataoka, Kensuke Kimura, Tomoki Kondoh, Yasuhiro Ejima, Masaru Shimamura, Takashi Tateishi, Tomoya Tomioka, Hiromi Miyazaki, Yasunari Suda, Takafumi Johkoh, Takeshi |
| description | The diagnosis of fibrotic hypersensitivity pneumonitis (fHP) from other interstitial lung diseases, particularly idiopathic pulmonary fibrosis (IPF), is often difficult. This study aimed to examine computed tomography (CT) findings that were useful for differentiating between fHP and IPF and to develop and validate a radiological diagnostic model.
In this study, 246 patients (fHP, n = 104; IPF, n = 142) from two institutions were included and randomly divided into the test (n = 164) and validation (n = 82) groups (at a 2:1 ratio). Three radiologists evaluated CT findings, such as pulmonary fibrosis, small airway disease, and predominant distribution, and compared them between fHP and IPF using binomial logistic regression and multivariate analysis. A prognostic model was developed from the test group and validated with the validation group.
Ground-glass opacity (GGO) with traction bronchiectasis (TB), honeycombing, hypoattenuation area, three-density pattern, diffuse craniocaudal distribution, peribronchovascular opacities in the upper lung, and random distribution were more common in fHP than in IPF. In multivariate analysis, GGO with TB, peribronchovascular opacities in the upper lung, and random distribution were significant features. The area under the curve of the fHP diagnostic model with the three aforementioned CT features was 0.733 (95% confidence interval [CI], 0.655–0.811, p |
| doi_str_mv | 10.1016/j.resinv.2024.07.002 |
| format | Article |
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In this study, 246 patients (fHP, n = 104; IPF, n = 142) from two institutions were included and randomly divided into the test (n = 164) and validation (n = 82) groups (at a 2:1 ratio). Three radiologists evaluated CT findings, such as pulmonary fibrosis, small airway disease, and predominant distribution, and compared them between fHP and IPF using binomial logistic regression and multivariate analysis. A prognostic model was developed from the test group and validated with the validation group.
Ground-glass opacity (GGO) with traction bronchiectasis (TB), honeycombing, hypoattenuation area, three-density pattern, diffuse craniocaudal distribution, peribronchovascular opacities in the upper lung, and random distribution were more common in fHP than in IPF. In multivariate analysis, GGO with TB, peribronchovascular opacities in the upper lung, and random distribution were significant features. The area under the curve of the fHP diagnostic model with the three aforementioned CT features was 0.733 (95% confidence interval [CI], 0.655–0.811, p < 0.001) in the test group and 0.630 (95% CI, 0.504–0.755, p < 0.047) in the validation group.
GGO with TB, peribronchovascular opacities in the upper lung, and random distribution were important CT features for differentiating fHP from IPF.</description><identifier>ISSN: 2212-5345</identifier><identifier>ISSN: 2212-5353</identifier><identifier>EISSN: 2212-5353</identifier><identifier>DOI: 10.1016/j.resinv.2024.07.002</identifier><identifier>PMID: 38996781</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Diagnostic model ; Fibrotic hypersensitivity pneumonitis ; Idiopathic pulmonary fibrosis</subject><ispartof>Respiratory investigation, 2024-09, Vol.62 (5), p.798-803</ispartof><rights>2024 The Japanese Respiratory Society</rights><rights>Copyright © 2024 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c241t-6340867333a19027581b487b150e6a1bd096eb8da98d05ea62f8ec392a121c143</cites><orcidid>0000-0001-9173-738X ; 0000-0001-9745-3329 ; 0000-0002-4521-5019 ; 0000-0002-8679-1661 ; 0009-0005-1907-5285 ; 0000-0001-5402-3185 ; 0000-0002-3944-6881 ; 0009-0000-1506-1306 ; 0000-0001-9842-778X ; 0000-0001-7566-546X ; 0000-0002-9073-9815</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38996781$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sumikawa, Hiromitsu</creatorcontrib><creatorcontrib>Komiya, Kosaku</creatorcontrib><creatorcontrib>Egashira, Ryoko</creatorcontrib><creatorcontrib>Tominaga, Junya</creatorcontrib><creatorcontrib>Ueno, Midori</creatorcontrib><creatorcontrib>Fukuda, Taiki</creatorcontrib><creatorcontrib>Yamada, Daisuke</creatorcontrib><creatorcontrib>Takei, Reoto</creatorcontrib><creatorcontrib>Kataoka, Kensuke</creatorcontrib><creatorcontrib>Kimura, Tomoki</creatorcontrib><creatorcontrib>Kondoh, Yasuhiro</creatorcontrib><creatorcontrib>Ejima, Masaru</creatorcontrib><creatorcontrib>Shimamura, Takashi</creatorcontrib><creatorcontrib>Tateishi, Tomoya</creatorcontrib><creatorcontrib>Tomioka, Hiromi</creatorcontrib><creatorcontrib>Miyazaki, Yasunari</creatorcontrib><creatorcontrib>Suda, Takafumi</creatorcontrib><creatorcontrib>Johkoh, Takeshi</creatorcontrib><title>Validation of a computed tomography diagnostic model for differentiating fibrotic hypersensitivity pneumonitis from idiopathic pulmonary fibrosis</title><title>Respiratory investigation</title><addtitle>Respir Investig</addtitle><description>The diagnosis of fibrotic hypersensitivity pneumonitis (fHP) from other interstitial lung diseases, particularly idiopathic pulmonary fibrosis (IPF), is often difficult. This study aimed to examine computed tomography (CT) findings that were useful for differentiating between fHP and IPF and to develop and validate a radiological diagnostic model.
In this study, 246 patients (fHP, n = 104; IPF, n = 142) from two institutions were included and randomly divided into the test (n = 164) and validation (n = 82) groups (at a 2:1 ratio). Three radiologists evaluated CT findings, such as pulmonary fibrosis, small airway disease, and predominant distribution, and compared them between fHP and IPF using binomial logistic regression and multivariate analysis. A prognostic model was developed from the test group and validated with the validation group.
Ground-glass opacity (GGO) with traction bronchiectasis (TB), honeycombing, hypoattenuation area, three-density pattern, diffuse craniocaudal distribution, peribronchovascular opacities in the upper lung, and random distribution were more common in fHP than in IPF. In multivariate analysis, GGO with TB, peribronchovascular opacities in the upper lung, and random distribution were significant features. The area under the curve of the fHP diagnostic model with the three aforementioned CT features was 0.733 (95% confidence interval [CI], 0.655–0.811, p < 0.001) in the test group and 0.630 (95% CI, 0.504–0.755, p < 0.047) in the validation group.
GGO with TB, peribronchovascular opacities in the upper lung, and random distribution were important CT features for differentiating fHP from IPF.</description><subject>Diagnostic model</subject><subject>Fibrotic hypersensitivity pneumonitis</subject><subject>Idiopathic pulmonary fibrosis</subject><issn>2212-5345</issn><issn>2212-5353</issn><issn>2212-5353</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kc9u1DAQxiMEolXpGyDkI5dN_SdxnAsSqiggVeICXC3HnuzOKrGD7ay0j8Eb41VKj_Vl7PHv88z4q6r3jNaMMnl3rCMk9KeaU97UtKsp5a-qa84Z37WiFa-f9017Vd2mdKRlyZY3TL6troTqe9kpdl39_W0mdCZj8CSMxBAb5mXN4EgOc9hHsxzOxKHZ-5AyWjIHBxMZQyzJcYQIPmNR-z0ZcYjhghzOC8QEPmHGE-YzWTysc_DlmMgYw0zQYVhMPhR4WadyZeJ50ydM76o3o5kS3D7Fm-rXw5ef9992jz--fr___LizZYi8k6KhSnZCCMN6yrtWsaFR3cBaCtKwwdFewqCc6ZWjLRjJRwVW9NwwzixrxE31cXt3ieHPCinrGZOFaTIewpq0oF2v2rZRsqDNhtrSYYow6iXiXJrWjOqLH_qoNz_0xQ9NO138KLIPTxXWYQb3LPr_-wX4tAFQ5jwhRJ0sgrfgMILN2gV8ucI_fK6iBg</recordid><startdate>20240901</startdate><enddate>20240901</enddate><creator>Sumikawa, Hiromitsu</creator><creator>Komiya, Kosaku</creator><creator>Egashira, Ryoko</creator><creator>Tominaga, Junya</creator><creator>Ueno, Midori</creator><creator>Fukuda, Taiki</creator><creator>Yamada, Daisuke</creator><creator>Takei, Reoto</creator><creator>Kataoka, Kensuke</creator><creator>Kimura, Tomoki</creator><creator>Kondoh, Yasuhiro</creator><creator>Ejima, Masaru</creator><creator>Shimamura, Takashi</creator><creator>Tateishi, Tomoya</creator><creator>Tomioka, Hiromi</creator><creator>Miyazaki, Yasunari</creator><creator>Suda, Takafumi</creator><creator>Johkoh, Takeshi</creator><general>Elsevier B.V</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-9173-738X</orcidid><orcidid>https://orcid.org/0000-0001-9745-3329</orcidid><orcidid>https://orcid.org/0000-0002-4521-5019</orcidid><orcidid>https://orcid.org/0000-0002-8679-1661</orcidid><orcidid>https://orcid.org/0009-0005-1907-5285</orcidid><orcidid>https://orcid.org/0000-0001-5402-3185</orcidid><orcidid>https://orcid.org/0000-0002-3944-6881</orcidid><orcidid>https://orcid.org/0009-0000-1506-1306</orcidid><orcidid>https://orcid.org/0000-0001-9842-778X</orcidid><orcidid>https://orcid.org/0000-0001-7566-546X</orcidid><orcidid>https://orcid.org/0000-0002-9073-9815</orcidid></search><sort><creationdate>20240901</creationdate><title>Validation of a computed tomography diagnostic model for differentiating fibrotic hypersensitivity pneumonitis from idiopathic pulmonary fibrosis</title><author>Sumikawa, Hiromitsu ; Komiya, Kosaku ; Egashira, Ryoko ; Tominaga, Junya ; Ueno, Midori ; Fukuda, Taiki ; Yamada, Daisuke ; Takei, Reoto ; Kataoka, Kensuke ; Kimura, Tomoki ; Kondoh, Yasuhiro ; Ejima, Masaru ; Shimamura, Takashi ; Tateishi, Tomoya ; Tomioka, Hiromi ; Miyazaki, Yasunari ; Suda, Takafumi ; Johkoh, Takeshi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c241t-6340867333a19027581b487b150e6a1bd096eb8da98d05ea62f8ec392a121c143</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Diagnostic model</topic><topic>Fibrotic hypersensitivity pneumonitis</topic><topic>Idiopathic pulmonary fibrosis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sumikawa, Hiromitsu</creatorcontrib><creatorcontrib>Komiya, Kosaku</creatorcontrib><creatorcontrib>Egashira, Ryoko</creatorcontrib><creatorcontrib>Tominaga, Junya</creatorcontrib><creatorcontrib>Ueno, Midori</creatorcontrib><creatorcontrib>Fukuda, Taiki</creatorcontrib><creatorcontrib>Yamada, Daisuke</creatorcontrib><creatorcontrib>Takei, Reoto</creatorcontrib><creatorcontrib>Kataoka, Kensuke</creatorcontrib><creatorcontrib>Kimura, Tomoki</creatorcontrib><creatorcontrib>Kondoh, Yasuhiro</creatorcontrib><creatorcontrib>Ejima, Masaru</creatorcontrib><creatorcontrib>Shimamura, Takashi</creatorcontrib><creatorcontrib>Tateishi, Tomoya</creatorcontrib><creatorcontrib>Tomioka, Hiromi</creatorcontrib><creatorcontrib>Miyazaki, Yasunari</creatorcontrib><creatorcontrib>Suda, Takafumi</creatorcontrib><creatorcontrib>Johkoh, Takeshi</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Respiratory investigation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sumikawa, Hiromitsu</au><au>Komiya, Kosaku</au><au>Egashira, Ryoko</au><au>Tominaga, Junya</au><au>Ueno, Midori</au><au>Fukuda, Taiki</au><au>Yamada, Daisuke</au><au>Takei, Reoto</au><au>Kataoka, Kensuke</au><au>Kimura, Tomoki</au><au>Kondoh, Yasuhiro</au><au>Ejima, Masaru</au><au>Shimamura, Takashi</au><au>Tateishi, Tomoya</au><au>Tomioka, Hiromi</au><au>Miyazaki, Yasunari</au><au>Suda, Takafumi</au><au>Johkoh, Takeshi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Validation of a computed tomography diagnostic model for differentiating fibrotic hypersensitivity pneumonitis from idiopathic pulmonary fibrosis</atitle><jtitle>Respiratory investigation</jtitle><addtitle>Respir Investig</addtitle><date>2024-09-01</date><risdate>2024</risdate><volume>62</volume><issue>5</issue><spage>798</spage><epage>803</epage><pages>798-803</pages><issn>2212-5345</issn><issn>2212-5353</issn><eissn>2212-5353</eissn><abstract>The diagnosis of fibrotic hypersensitivity pneumonitis (fHP) from other interstitial lung diseases, particularly idiopathic pulmonary fibrosis (IPF), is often difficult. This study aimed to examine computed tomography (CT) findings that were useful for differentiating between fHP and IPF and to develop and validate a radiological diagnostic model.
In this study, 246 patients (fHP, n = 104; IPF, n = 142) from two institutions were included and randomly divided into the test (n = 164) and validation (n = 82) groups (at a 2:1 ratio). Three radiologists evaluated CT findings, such as pulmonary fibrosis, small airway disease, and predominant distribution, and compared them between fHP and IPF using binomial logistic regression and multivariate analysis. A prognostic model was developed from the test group and validated with the validation group.
Ground-glass opacity (GGO) with traction bronchiectasis (TB), honeycombing, hypoattenuation area, three-density pattern, diffuse craniocaudal distribution, peribronchovascular opacities in the upper lung, and random distribution were more common in fHP than in IPF. In multivariate analysis, GGO with TB, peribronchovascular opacities in the upper lung, and random distribution were significant features. The area under the curve of the fHP diagnostic model with the three aforementioned CT features was 0.733 (95% confidence interval [CI], 0.655–0.811, p < 0.001) in the test group and 0.630 (95% CI, 0.504–0.755, p < 0.047) in the validation group.
GGO with TB, peribronchovascular opacities in the upper lung, and random distribution were important CT features for differentiating fHP from IPF.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>38996781</pmid><doi>10.1016/j.resinv.2024.07.002</doi><tpages>6</tpages><orcidid>https://orcid.org/0000-0001-9173-738X</orcidid><orcidid>https://orcid.org/0000-0001-9745-3329</orcidid><orcidid>https://orcid.org/0000-0002-4521-5019</orcidid><orcidid>https://orcid.org/0000-0002-8679-1661</orcidid><orcidid>https://orcid.org/0009-0005-1907-5285</orcidid><orcidid>https://orcid.org/0000-0001-5402-3185</orcidid><orcidid>https://orcid.org/0000-0002-3944-6881</orcidid><orcidid>https://orcid.org/0009-0000-1506-1306</orcidid><orcidid>https://orcid.org/0000-0001-9842-778X</orcidid><orcidid>https://orcid.org/0000-0001-7566-546X</orcidid><orcidid>https://orcid.org/0000-0002-9073-9815</orcidid></addata></record> |
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| subjects | Diagnostic model Fibrotic hypersensitivity pneumonitis Idiopathic pulmonary fibrosis |
| title | Validation of a computed tomography diagnostic model for differentiating fibrotic hypersensitivity pneumonitis from idiopathic pulmonary fibrosis |
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