Differentiation of adenocarcinoma in situ with alveolar collapse from minimally invasive adenocarcinoma or invasive adenocarcinoma appearing as part-solid ground-glass nodules (≤ 2 cm) using computed tomography
Purpose To investigate the differentiating computed tomographic (CT) features between adenocarcinoma in situ (AIS) with alveolar collapse and minimally invasive adenocarcinoma (MIA) or invasive adenocarcinoma (IA) appearing as part-solid nodules. Methods A total of 147 consecutive patients with 157...
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| Veröffentlicht in: | Japanese journal of radiology 2022-01, Vol.40 (1), p.29-37 |
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| creator | Xu, Liyun Lin, Shuaidong Zhang, Yongkui |
| description | Purpose
To investigate the differentiating computed tomographic (CT) features between adenocarcinoma in situ (AIS) with alveolar collapse and minimally invasive adenocarcinoma (MIA) or invasive adenocarcinoma (IA) appearing as part-solid nodules.
Methods
A total of 147 consecutive patients with 157 pathology-confirmed part-solid ground-glass nodules (GGNs) ≤ 20 mm without other pathological condition such as inflammation and fibrosis who underwent chest CT were included.
Results
The 157 part-solid GGNs included 33 (21.02%) pathologically confirmed AISs with alveolar collapse. Multivariate analysis revealed that smaller lesion size (odds ratio [OR] 0.671), and well-defined border (OR 5.544), concentrated distribution (OR 7.994), and homogeneity of the solid portion (OR 4.365) were significant independent predictors for differentiating AIS with alveolar collapse from MIA (
P
|
| doi_str_mv | 10.1007/s11604-021-01183-9 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2555968364</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2555968364</sourcerecordid><originalsourceid>FETCH-LOGICAL-c399t-587bf5a930f80852e6b41e0de9c8de5648e98874ecbe1c4efb30025f55cfd0773</originalsourceid><addsrcrecordid>eNp9kcFqFTEUhoMotl59ARcScFMXo8kkmWSWUq0KBTcK7kImc3KbkknGZOaWu3Pbt3DRJ_El3PdJnOutFQq6yoF8_38O_4_QU0peUkLkq0JpQ3hFaloRShWr2nvokKpGVpSoL_dvZ0kP0KNSzglpOOP8ITpgnFHFOTtEP9945yBDnLyZfIo4OWx6iMmabH1Mg8E-4uKnGV_46QybsIEUTMY2hWDGAtjlNODBRz-YELYLvTHFb-CuS8r__DLjCCb7uMam4NHkqSop-B6vc5pjX62DKQXH1M8BCj66vry6_nZZ__huhxd4LjuZTcM4T9DjKQ1pnc14tn2MHjgTCjy5eVfo88nbT8fvq9OP7z4cvz6tLGvbqRJKdk6YlhGniBI1NB2nQHporepBNFxBq5TkYDugloPrGCG1cEJY1xMp2Qod7X3HnL7OUCY9-GJhySZCmouuhRBto9iS_Ao9v4OepznH5TpdN7SRSjLZLFS9p2xOpWRwesxLtHmrKdG72vW-dr3Urn_XrttF9OzGeu4G6G8lf3peALYHyrgLGvLf3f-x_QW3-MEc</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2616787376</pqid></control><display><type>article</type><title>Differentiation of adenocarcinoma in situ with alveolar collapse from minimally invasive adenocarcinoma or invasive adenocarcinoma appearing as part-solid ground-glass nodules (≤ 2 cm) using computed tomography</title><source>MEDLINE</source><source>SpringerLink Journals - AutoHoldings</source><creator>Xu, Liyun ; Lin, Shuaidong ; Zhang, Yongkui</creator><creatorcontrib>Xu, Liyun ; Lin, Shuaidong ; Zhang, Yongkui</creatorcontrib><description>Purpose
To investigate the differentiating computed tomographic (CT) features between adenocarcinoma in situ (AIS) with alveolar collapse and minimally invasive adenocarcinoma (MIA) or invasive adenocarcinoma (IA) appearing as part-solid nodules.
Methods
A total of 147 consecutive patients with 157 pathology-confirmed part-solid ground-glass nodules (GGNs) ≤ 20 mm without other pathological condition such as inflammation and fibrosis who underwent chest CT were included.
Results
The 157 part-solid GGNs included 33 (21.02%) pathologically confirmed AISs with alveolar collapse. Multivariate analysis revealed that smaller lesion size (odds ratio [OR] 0.671), and well-defined border (OR 5.544), concentrated distribution (OR 7.994), and homogeneity of the solid portion (OR 4.365) were significant independent predictors for differentiating AIS with alveolar collapse from MIA (
P
< 0.05) with excellent accuracy (area under receiver operating characteristic [ROC] curve, 0.902). Multivariate analysis revealed that smaller lesion size (OR 0.782), and size (OR 0.821), well-defined border (OR 5.752), and homogeneity of solid portion (OR 6.182) were significant independent predictors differentiating AIS with alveolar collapse from IA (
P
< 0.05) with excellent accuracy (area under ROC curve 0.910).
Conclusion
Among part-solid GGNs, AIS with alveolar collapse can be accurately differentiated from MIA on the basis of smaller lesion size, well-defined border, concentrated distribution, and homogeneity of solid portion, and from IA according to smaller lesion size, and smaller size, well-defined border, and homogeneity of solid portion.</description><identifier>ISSN: 1867-1071</identifier><identifier>EISSN: 1867-108X</identifier><identifier>DOI: 10.1007/s11604-021-01183-9</identifier><identifier>PMID: 34318443</identifier><language>eng</language><publisher>Singapore: Springer Singapore</publisher><subject>Adenocarcinoma ; Adenocarcinoma - diagnostic imaging ; Adenocarcinoma in Situ ; Alveoli ; Cancer ; Computed tomography ; Fibrosis ; Homogeneity ; Humans ; Imaging ; Lesions ; Lung Neoplasms - diagnostic imaging ; Medicine ; Medicine & Public Health ; Multivariate analysis ; Neoplasm Invasiveness ; Nodules ; Nuclear Medicine ; Original Article ; Radiology ; Radiotherapy ; Retrospective Studies ; Tomography, X-Ray Computed</subject><ispartof>Japanese journal of radiology, 2022-01, Vol.40 (1), p.29-37</ispartof><rights>Japan Radiological Society 2021</rights><rights>2021. Japan Radiological Society.</rights><rights>Japan Radiological Society 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c399t-587bf5a930f80852e6b41e0de9c8de5648e98874ecbe1c4efb30025f55cfd0773</citedby><cites>FETCH-LOGICAL-c399t-587bf5a930f80852e6b41e0de9c8de5648e98874ecbe1c4efb30025f55cfd0773</cites><orcidid>0000-0001-9339-6961</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11604-021-01183-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11604-021-01183-9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27923,27924,41487,42556,51318</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34318443$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Xu, Liyun</creatorcontrib><creatorcontrib>Lin, Shuaidong</creatorcontrib><creatorcontrib>Zhang, Yongkui</creatorcontrib><title>Differentiation of adenocarcinoma in situ with alveolar collapse from minimally invasive adenocarcinoma or invasive adenocarcinoma appearing as part-solid ground-glass nodules (≤ 2 cm) using computed tomography</title><title>Japanese journal of radiology</title><addtitle>Jpn J Radiol</addtitle><addtitle>Jpn J Radiol</addtitle><description>Purpose
To investigate the differentiating computed tomographic (CT) features between adenocarcinoma in situ (AIS) with alveolar collapse and minimally invasive adenocarcinoma (MIA) or invasive adenocarcinoma (IA) appearing as part-solid nodules.
Methods
A total of 147 consecutive patients with 157 pathology-confirmed part-solid ground-glass nodules (GGNs) ≤ 20 mm without other pathological condition such as inflammation and fibrosis who underwent chest CT were included.
Results
The 157 part-solid GGNs included 33 (21.02%) pathologically confirmed AISs with alveolar collapse. Multivariate analysis revealed that smaller lesion size (odds ratio [OR] 0.671), and well-defined border (OR 5.544), concentrated distribution (OR 7.994), and homogeneity of the solid portion (OR 4.365) were significant independent predictors for differentiating AIS with alveolar collapse from MIA (
P
< 0.05) with excellent accuracy (area under receiver operating characteristic [ROC] curve, 0.902). Multivariate analysis revealed that smaller lesion size (OR 0.782), and size (OR 0.821), well-defined border (OR 5.752), and homogeneity of solid portion (OR 6.182) were significant independent predictors differentiating AIS with alveolar collapse from IA (
P
< 0.05) with excellent accuracy (area under ROC curve 0.910).
Conclusion
Among part-solid GGNs, AIS with alveolar collapse can be accurately differentiated from MIA on the basis of smaller lesion size, well-defined border, concentrated distribution, and homogeneity of solid portion, and from IA according to smaller lesion size, and smaller size, well-defined border, and homogeneity of solid portion.</description><subject>Adenocarcinoma</subject><subject>Adenocarcinoma - diagnostic imaging</subject><subject>Adenocarcinoma in Situ</subject><subject>Alveoli</subject><subject>Cancer</subject><subject>Computed tomography</subject><subject>Fibrosis</subject><subject>Homogeneity</subject><subject>Humans</subject><subject>Imaging</subject><subject>Lesions</subject><subject>Lung Neoplasms - diagnostic imaging</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Multivariate analysis</subject><subject>Neoplasm Invasiveness</subject><subject>Nodules</subject><subject>Nuclear Medicine</subject><subject>Original Article</subject><subject>Radiology</subject><subject>Radiotherapy</subject><subject>Retrospective Studies</subject><subject>Tomography, X-Ray Computed</subject><issn>1867-1071</issn><issn>1867-108X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kcFqFTEUhoMotl59ARcScFMXo8kkmWSWUq0KBTcK7kImc3KbkknGZOaWu3Pbt3DRJ_El3PdJnOutFQq6yoF8_38O_4_QU0peUkLkq0JpQ3hFaloRShWr2nvokKpGVpSoL_dvZ0kP0KNSzglpOOP8ITpgnFHFOTtEP9945yBDnLyZfIo4OWx6iMmabH1Mg8E-4uKnGV_46QybsIEUTMY2hWDGAtjlNODBRz-YELYLvTHFb-CuS8r__DLjCCb7uMam4NHkqSop-B6vc5pjX62DKQXH1M8BCj66vry6_nZZ__huhxd4LjuZTcM4T9DjKQ1pnc14tn2MHjgTCjy5eVfo88nbT8fvq9OP7z4cvz6tLGvbqRJKdk6YlhGniBI1NB2nQHporepBNFxBq5TkYDugloPrGCG1cEJY1xMp2Qod7X3HnL7OUCY9-GJhySZCmouuhRBto9iS_Ao9v4OepznH5TpdN7SRSjLZLFS9p2xOpWRwesxLtHmrKdG72vW-dr3Urn_XrttF9OzGeu4G6G8lf3peALYHyrgLGvLf3f-x_QW3-MEc</recordid><startdate>20220101</startdate><enddate>20220101</enddate><creator>Xu, Liyun</creator><creator>Lin, Shuaidong</creator><creator>Zhang, Yongkui</creator><general>Springer Singapore</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QO</scope><scope>7RV</scope><scope>7TK</scope><scope>7U7</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-9339-6961</orcidid></search><sort><creationdate>20220101</creationdate><title>Differentiation of adenocarcinoma in situ with alveolar collapse from minimally invasive adenocarcinoma or invasive adenocarcinoma appearing as part-solid ground-glass nodules (≤ 2 cm) using computed tomography</title><author>Xu, Liyun ; Lin, Shuaidong ; Zhang, Yongkui</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c399t-587bf5a930f80852e6b41e0de9c8de5648e98874ecbe1c4efb30025f55cfd0773</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Adenocarcinoma</topic><topic>Adenocarcinoma - diagnostic imaging</topic><topic>Adenocarcinoma in Situ</topic><topic>Alveoli</topic><topic>Cancer</topic><topic>Computed tomography</topic><topic>Fibrosis</topic><topic>Homogeneity</topic><topic>Humans</topic><topic>Imaging</topic><topic>Lesions</topic><topic>Lung Neoplasms - diagnostic imaging</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Multivariate analysis</topic><topic>Neoplasm Invasiveness</topic><topic>Nodules</topic><topic>Nuclear Medicine</topic><topic>Original Article</topic><topic>Radiology</topic><topic>Radiotherapy</topic><topic>Retrospective Studies</topic><topic>Tomography, X-Ray Computed</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xu, Liyun</creatorcontrib><creatorcontrib>Lin, Shuaidong</creatorcontrib><creatorcontrib>Zhang, Yongkui</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>Japanese journal of radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xu, Liyun</au><au>Lin, Shuaidong</au><au>Zhang, Yongkui</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Differentiation of adenocarcinoma in situ with alveolar collapse from minimally invasive adenocarcinoma or invasive adenocarcinoma appearing as part-solid ground-glass nodules (≤ 2 cm) using computed tomography</atitle><jtitle>Japanese journal of radiology</jtitle><stitle>Jpn J Radiol</stitle><addtitle>Jpn J Radiol</addtitle><date>2022-01-01</date><risdate>2022</risdate><volume>40</volume><issue>1</issue><spage>29</spage><epage>37</epage><pages>29-37</pages><issn>1867-1071</issn><eissn>1867-108X</eissn><abstract>Purpose
To investigate the differentiating computed tomographic (CT) features between adenocarcinoma in situ (AIS) with alveolar collapse and minimally invasive adenocarcinoma (MIA) or invasive adenocarcinoma (IA) appearing as part-solid nodules.
Methods
A total of 147 consecutive patients with 157 pathology-confirmed part-solid ground-glass nodules (GGNs) ≤ 20 mm without other pathological condition such as inflammation and fibrosis who underwent chest CT were included.
Results
The 157 part-solid GGNs included 33 (21.02%) pathologically confirmed AISs with alveolar collapse. Multivariate analysis revealed that smaller lesion size (odds ratio [OR] 0.671), and well-defined border (OR 5.544), concentrated distribution (OR 7.994), and homogeneity of the solid portion (OR 4.365) were significant independent predictors for differentiating AIS with alveolar collapse from MIA (
P
< 0.05) with excellent accuracy (area under receiver operating characteristic [ROC] curve, 0.902). Multivariate analysis revealed that smaller lesion size (OR 0.782), and size (OR 0.821), well-defined border (OR 5.752), and homogeneity of solid portion (OR 6.182) were significant independent predictors differentiating AIS with alveolar collapse from IA (
P
< 0.05) with excellent accuracy (area under ROC curve 0.910).
Conclusion
Among part-solid GGNs, AIS with alveolar collapse can be accurately differentiated from MIA on the basis of smaller lesion size, well-defined border, concentrated distribution, and homogeneity of solid portion, and from IA according to smaller lesion size, and smaller size, well-defined border, and homogeneity of solid portion.</abstract><cop>Singapore</cop><pub>Springer Singapore</pub><pmid>34318443</pmid><doi>10.1007/s11604-021-01183-9</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0001-9339-6961</orcidid></addata></record> |
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| identifier | ISSN: 1867-1071 |
| ispartof | Japanese journal of radiology, 2022-01, Vol.40 (1), p.29-37 |
| issn | 1867-1071 1867-108X |
| language | eng |
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| source | MEDLINE; SpringerLink Journals - AutoHoldings |
| subjects | Adenocarcinoma Adenocarcinoma - diagnostic imaging Adenocarcinoma in Situ Alveoli Cancer Computed tomography Fibrosis Homogeneity Humans Imaging Lesions Lung Neoplasms - diagnostic imaging Medicine Medicine & Public Health Multivariate analysis Neoplasm Invasiveness Nodules Nuclear Medicine Original Article Radiology Radiotherapy Retrospective Studies Tomography, X-Ray Computed |
| title | Differentiation of adenocarcinoma in situ with alveolar collapse from minimally invasive adenocarcinoma or invasive adenocarcinoma appearing as part-solid ground-glass nodules (≤ 2 cm) using computed tomography |
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