New classification of dynamic computed tomography images predictive of malignant characteristics of hepatocellular carcinoma
Aim: The aim of this study was to elucidate whether the histopathological characteristics of hepatocellular carcinoma (HCC) can be predicted from baseline dynamic computed tomography (CT) images. Methods: This retrospective study included 86 consecutive patients with HCC who underwent surgical res...
Gespeichert in:
| Veröffentlicht in: | Hepatology research 2010-10, Vol.40 (10), p.1006-1014 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1014 |
|---|---|
| container_issue | 10 |
| container_start_page | 1006 |
| container_title | Hepatology research |
| container_volume | 40 |
| creator | Kawamura, Yusuke Ikeda, Kenji Hirakawa, Miharu Yatsuji, Hiromi Sezaki, Hitomi Hosaka, Tetsuya Akuta, Norio Kobayashi, Masahiro Saitoh, Satoshi Suzuki, Fumitaka Suzuki, Yoshiyuki Arase, Yasuji Kumada, Hiromitsu |
| description | Aim: The aim of this study was to elucidate whether the histopathological characteristics of hepatocellular carcinoma (HCC) can be predicted from baseline dynamic computed tomography (CT) images.
Methods: This retrospective study included 86 consecutive patients with HCC who underwent surgical resection between January 2000 and September 2008. The arterial‐ and portal‐phase dynamic CT images obtained preoperatively were classified into four enhancement patterns: Type‐1 and Type‐2 are homogeneous enhancement patterns without or with increased arterial blood flow, respectively; Type‐3, heterogeneous enhancement pattern with septum‐like structure; and Type‐4, heterogeneous enhancement pattern with irregular ring‐like structures. We also evaluated the predictive factors for poorly‐differentiated HCC, specific macroscopic type of HCC (simple nodular type with extranodular growth [SNEG] and confluent multinodular [CMN]) by univariate and multivariate analyses.
Results: The percentages of poorly‐differentiated HCC according to the enhancement pattern were three of 51 nodules (6%) of Type‐1 and ‐2, three of 24 (13%) of Type‐3, and eight of 11 (73%) of Type‐4. The percentages of SNEG/CMN according to the enhancement pattern were 12 of 51 nodules (24%) of Type‐1 and ‐2, 13 of 24 (54%) of Type‐3, and five of 11 (45%) of Type‐4. Multivariate analysis identified Type‐4 pattern as a significant and independent predictor of poorly‐differentiated HCC (P |
| doi_str_mv | 10.1111/j.1872-034X.2010.00703.x |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_954581110</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>756663520</sourcerecordid><originalsourceid>FETCH-LOGICAL-c5573-452ce79ca7bc7f421195d10270ded3589534763b00f6c34eb58e7b72c088ca43</originalsourceid><addsrcrecordid>eNqNkU1v1DAQhiMEoqXwF5BvnLLY8Vf2wAFV_UBqF4QqgbhYzmSy6yWJg53QXak_vg5b9gq-eOR53_HMPFlGGF2wdN5vF6zURU65-L4oaHqlVFO-2D3LTo-J5ynmpcoVF-okexXjllKmaSFeZicFLUvNuTrNHlZ4T6C1MbrGgR2d74lvSL3vbeeAgO-GacSajL7z62CHzZ64zq4xkiFg7WB0v3E2dLZ16972I4GNDRZGDC6ODuKc3OBgRw_YtlNrAwEbwPW-s6-zF41tI755us-yu8uLu_Pr_Obz1afzjzc5SKl5LmQBqJdgdQW6EQVjS1kzWmhaY81luZRcaMUrShsFXGAlS9SVLiBNCVbws-zdoewQ_K8J42g6F-dubI9-imYphSzTWuk_lVoqpbgsZmV5UELwMQZszBDSYsLeMGpmRmZrZhRmRmFmRuYPI7NL1rdPn0xVh_XR-BdKEnw4CO5di_v_LmyuL758TVHy5wd_IoC7o9-Gn0ZprqX5troylyt1y2_5D8P4I3OEsaE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>756663520</pqid></control><display><type>article</type><title>New classification of dynamic computed tomography images predictive of malignant characteristics of hepatocellular carcinoma</title><source>Access via Wiley Online Library</source><creator>Kawamura, Yusuke ; Ikeda, Kenji ; Hirakawa, Miharu ; Yatsuji, Hiromi ; Sezaki, Hitomi ; Hosaka, Tetsuya ; Akuta, Norio ; Kobayashi, Masahiro ; Saitoh, Satoshi ; Suzuki, Fumitaka ; Suzuki, Yoshiyuki ; Arase, Yasuji ; Kumada, Hiromitsu</creator><creatorcontrib>Kawamura, Yusuke ; Ikeda, Kenji ; Hirakawa, Miharu ; Yatsuji, Hiromi ; Sezaki, Hitomi ; Hosaka, Tetsuya ; Akuta, Norio ; Kobayashi, Masahiro ; Saitoh, Satoshi ; Suzuki, Fumitaka ; Suzuki, Yoshiyuki ; Arase, Yasuji ; Kumada, Hiromitsu</creatorcontrib><description>Aim: The aim of this study was to elucidate whether the histopathological characteristics of hepatocellular carcinoma (HCC) can be predicted from baseline dynamic computed tomography (CT) images.
Methods: This retrospective study included 86 consecutive patients with HCC who underwent surgical resection between January 2000 and September 2008. The arterial‐ and portal‐phase dynamic CT images obtained preoperatively were classified into four enhancement patterns: Type‐1 and Type‐2 are homogeneous enhancement patterns without or with increased arterial blood flow, respectively; Type‐3, heterogeneous enhancement pattern with septum‐like structure; and Type‐4, heterogeneous enhancement pattern with irregular ring‐like structures. We also evaluated the predictive factors for poorly‐differentiated HCC, specific macroscopic type of HCC (simple nodular type with extranodular growth [SNEG] and confluent multinodular [CMN]) by univariate and multivariate analyses.
Results: The percentages of poorly‐differentiated HCC according to the enhancement pattern were three of 51 nodules (6%) of Type‐1 and ‐2, three of 24 (13%) of Type‐3, and eight of 11 (73%) of Type‐4. The percentages of SNEG/CMN according to the enhancement pattern were 12 of 51 nodules (24%) of Type‐1 and ‐2, 13 of 24 (54%) of Type‐3, and five of 11 (45%) of Type‐4. Multivariate analysis identified Type‐4 pattern as a significant and independent predictor of poorly‐differentiated HCC (P < 0.001) while Type‐3 pattern was a significant predictor of SNEG/CMN (P = 0.017).
Conclusion: Heterogeneity of dynamic CT images correlates with malignant characteristics of HCC and can be potentially used to predict the malignant potential of HCC before treatment.</description><identifier>ISSN: 1386-6346</identifier><identifier>EISSN: 1872-034X</identifier><identifier>DOI: 10.1111/j.1872-034X.2010.00703.x</identifier><identifier>PMID: 20887336</identifier><language>eng</language><publisher>Melbourne, Australia: Blackwell Publishing Asia</publisher><subject>Classification ; confluent multinodular type ; dynamic computed tomography ; hepatocellular carcinoma ; poorly-differentiated hepatocellular carcinoma ; radiofrequency ablation ; simple nodular type with extranodular growth type</subject><ispartof>Hepatology research, 2010-10, Vol.40 (10), p.1006-1014</ispartof><rights>2010 The Japan Society of Hepatology</rights><rights>2010 The Japan Society of Hepatology.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5573-452ce79ca7bc7f421195d10270ded3589534763b00f6c34eb58e7b72c088ca43</citedby><cites>FETCH-LOGICAL-c5573-452ce79ca7bc7f421195d10270ded3589534763b00f6c34eb58e7b72c088ca43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fj.1872-034X.2010.00703.x$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fj.1872-034X.2010.00703.x$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20887336$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kawamura, Yusuke</creatorcontrib><creatorcontrib>Ikeda, Kenji</creatorcontrib><creatorcontrib>Hirakawa, Miharu</creatorcontrib><creatorcontrib>Yatsuji, Hiromi</creatorcontrib><creatorcontrib>Sezaki, Hitomi</creatorcontrib><creatorcontrib>Hosaka, Tetsuya</creatorcontrib><creatorcontrib>Akuta, Norio</creatorcontrib><creatorcontrib>Kobayashi, Masahiro</creatorcontrib><creatorcontrib>Saitoh, Satoshi</creatorcontrib><creatorcontrib>Suzuki, Fumitaka</creatorcontrib><creatorcontrib>Suzuki, Yoshiyuki</creatorcontrib><creatorcontrib>Arase, Yasuji</creatorcontrib><creatorcontrib>Kumada, Hiromitsu</creatorcontrib><title>New classification of dynamic computed tomography images predictive of malignant characteristics of hepatocellular carcinoma</title><title>Hepatology research</title><addtitle>Hepatol Res</addtitle><description>Aim: The aim of this study was to elucidate whether the histopathological characteristics of hepatocellular carcinoma (HCC) can be predicted from baseline dynamic computed tomography (CT) images.
Methods: This retrospective study included 86 consecutive patients with HCC who underwent surgical resection between January 2000 and September 2008. The arterial‐ and portal‐phase dynamic CT images obtained preoperatively were classified into four enhancement patterns: Type‐1 and Type‐2 are homogeneous enhancement patterns without or with increased arterial blood flow, respectively; Type‐3, heterogeneous enhancement pattern with septum‐like structure; and Type‐4, heterogeneous enhancement pattern with irregular ring‐like structures. We also evaluated the predictive factors for poorly‐differentiated HCC, specific macroscopic type of HCC (simple nodular type with extranodular growth [SNEG] and confluent multinodular [CMN]) by univariate and multivariate analyses.
Results: The percentages of poorly‐differentiated HCC according to the enhancement pattern were three of 51 nodules (6%) of Type‐1 and ‐2, three of 24 (13%) of Type‐3, and eight of 11 (73%) of Type‐4. The percentages of SNEG/CMN according to the enhancement pattern were 12 of 51 nodules (24%) of Type‐1 and ‐2, 13 of 24 (54%) of Type‐3, and five of 11 (45%) of Type‐4. Multivariate analysis identified Type‐4 pattern as a significant and independent predictor of poorly‐differentiated HCC (P < 0.001) while Type‐3 pattern was a significant predictor of SNEG/CMN (P = 0.017).
Conclusion: Heterogeneity of dynamic CT images correlates with malignant characteristics of HCC and can be potentially used to predict the malignant potential of HCC before treatment.</description><subject>Classification</subject><subject>confluent multinodular type</subject><subject>dynamic computed tomography</subject><subject>hepatocellular carcinoma</subject><subject>poorly-differentiated hepatocellular carcinoma</subject><subject>radiofrequency ablation</subject><subject>simple nodular type with extranodular growth type</subject><issn>1386-6346</issn><issn>1872-034X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><recordid>eNqNkU1v1DAQhiMEoqXwF5BvnLLY8Vf2wAFV_UBqF4QqgbhYzmSy6yWJg53QXak_vg5b9gq-eOR53_HMPFlGGF2wdN5vF6zURU65-L4oaHqlVFO-2D3LTo-J5ynmpcoVF-okexXjllKmaSFeZicFLUvNuTrNHlZ4T6C1MbrGgR2d74lvSL3vbeeAgO-GacSajL7z62CHzZ64zq4xkiFg7WB0v3E2dLZ16972I4GNDRZGDC6ODuKc3OBgRw_YtlNrAwEbwPW-s6-zF41tI755us-yu8uLu_Pr_Obz1afzjzc5SKl5LmQBqJdgdQW6EQVjS1kzWmhaY81luZRcaMUrShsFXGAlS9SVLiBNCVbws-zdoewQ_K8J42g6F-dubI9-imYphSzTWuk_lVoqpbgsZmV5UELwMQZszBDSYsLeMGpmRmZrZhRmRmFmRuYPI7NL1rdPn0xVh_XR-BdKEnw4CO5di_v_LmyuL758TVHy5wd_IoC7o9-Gn0ZprqX5troylyt1y2_5D8P4I3OEsaE</recordid><startdate>201010</startdate><enddate>201010</enddate><creator>Kawamura, Yusuke</creator><creator>Ikeda, Kenji</creator><creator>Hirakawa, Miharu</creator><creator>Yatsuji, Hiromi</creator><creator>Sezaki, Hitomi</creator><creator>Hosaka, Tetsuya</creator><creator>Akuta, Norio</creator><creator>Kobayashi, Masahiro</creator><creator>Saitoh, Satoshi</creator><creator>Suzuki, Fumitaka</creator><creator>Suzuki, Yoshiyuki</creator><creator>Arase, Yasuji</creator><creator>Kumada, Hiromitsu</creator><general>Blackwell Publishing Asia</general><scope>BSCLL</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope></search><sort><creationdate>201010</creationdate><title>New classification of dynamic computed tomography images predictive of malignant characteristics of hepatocellular carcinoma</title><author>Kawamura, Yusuke ; Ikeda, Kenji ; Hirakawa, Miharu ; Yatsuji, Hiromi ; Sezaki, Hitomi ; Hosaka, Tetsuya ; Akuta, Norio ; Kobayashi, Masahiro ; Saitoh, Satoshi ; Suzuki, Fumitaka ; Suzuki, Yoshiyuki ; Arase, Yasuji ; Kumada, Hiromitsu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5573-452ce79ca7bc7f421195d10270ded3589534763b00f6c34eb58e7b72c088ca43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Classification</topic><topic>confluent multinodular type</topic><topic>dynamic computed tomography</topic><topic>hepatocellular carcinoma</topic><topic>poorly-differentiated hepatocellular carcinoma</topic><topic>radiofrequency ablation</topic><topic>simple nodular type with extranodular growth type</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kawamura, Yusuke</creatorcontrib><creatorcontrib>Ikeda, Kenji</creatorcontrib><creatorcontrib>Hirakawa, Miharu</creatorcontrib><creatorcontrib>Yatsuji, Hiromi</creatorcontrib><creatorcontrib>Sezaki, Hitomi</creatorcontrib><creatorcontrib>Hosaka, Tetsuya</creatorcontrib><creatorcontrib>Akuta, Norio</creatorcontrib><creatorcontrib>Kobayashi, Masahiro</creatorcontrib><creatorcontrib>Saitoh, Satoshi</creatorcontrib><creatorcontrib>Suzuki, Fumitaka</creatorcontrib><creatorcontrib>Suzuki, Yoshiyuki</creatorcontrib><creatorcontrib>Arase, Yasuji</creatorcontrib><creatorcontrib>Kumada, Hiromitsu</creatorcontrib><collection>Istex</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Hepatology research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kawamura, Yusuke</au><au>Ikeda, Kenji</au><au>Hirakawa, Miharu</au><au>Yatsuji, Hiromi</au><au>Sezaki, Hitomi</au><au>Hosaka, Tetsuya</au><au>Akuta, Norio</au><au>Kobayashi, Masahiro</au><au>Saitoh, Satoshi</au><au>Suzuki, Fumitaka</au><au>Suzuki, Yoshiyuki</au><au>Arase, Yasuji</au><au>Kumada, Hiromitsu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>New classification of dynamic computed tomography images predictive of malignant characteristics of hepatocellular carcinoma</atitle><jtitle>Hepatology research</jtitle><addtitle>Hepatol Res</addtitle><date>2010-10</date><risdate>2010</risdate><volume>40</volume><issue>10</issue><spage>1006</spage><epage>1014</epage><pages>1006-1014</pages><issn>1386-6346</issn><eissn>1872-034X</eissn><abstract>Aim: The aim of this study was to elucidate whether the histopathological characteristics of hepatocellular carcinoma (HCC) can be predicted from baseline dynamic computed tomography (CT) images.
Methods: This retrospective study included 86 consecutive patients with HCC who underwent surgical resection between January 2000 and September 2008. The arterial‐ and portal‐phase dynamic CT images obtained preoperatively were classified into four enhancement patterns: Type‐1 and Type‐2 are homogeneous enhancement patterns without or with increased arterial blood flow, respectively; Type‐3, heterogeneous enhancement pattern with septum‐like structure; and Type‐4, heterogeneous enhancement pattern with irregular ring‐like structures. We also evaluated the predictive factors for poorly‐differentiated HCC, specific macroscopic type of HCC (simple nodular type with extranodular growth [SNEG] and confluent multinodular [CMN]) by univariate and multivariate analyses.
Results: The percentages of poorly‐differentiated HCC according to the enhancement pattern were three of 51 nodules (6%) of Type‐1 and ‐2, three of 24 (13%) of Type‐3, and eight of 11 (73%) of Type‐4. The percentages of SNEG/CMN according to the enhancement pattern were 12 of 51 nodules (24%) of Type‐1 and ‐2, 13 of 24 (54%) of Type‐3, and five of 11 (45%) of Type‐4. Multivariate analysis identified Type‐4 pattern as a significant and independent predictor of poorly‐differentiated HCC (P < 0.001) while Type‐3 pattern was a significant predictor of SNEG/CMN (P = 0.017).
Conclusion: Heterogeneity of dynamic CT images correlates with malignant characteristics of HCC and can be potentially used to predict the malignant potential of HCC before treatment.</abstract><cop>Melbourne, Australia</cop><pub>Blackwell Publishing Asia</pub><pmid>20887336</pmid><doi>10.1111/j.1872-034X.2010.00703.x</doi><tpages>9</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1386-6346 |
| ispartof | Hepatology research, 2010-10, Vol.40 (10), p.1006-1014 |
| issn | 1386-6346 1872-034X |
| language | eng |
| recordid | cdi_proquest_miscellaneous_954581110 |
| source | Access via Wiley Online Library |
| subjects | Classification confluent multinodular type dynamic computed tomography hepatocellular carcinoma poorly-differentiated hepatocellular carcinoma radiofrequency ablation simple nodular type with extranodular growth type |
| title | New classification of dynamic computed tomography images predictive of malignant characteristics of hepatocellular carcinoma |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-18T21%3A19%3A28IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=New%20classification%20of%20dynamic%20computed%20tomography%20images%20predictive%20of%20malignant%20characteristics%20of%20hepatocellular%20carcinoma&rft.jtitle=Hepatology%20research&rft.au=Kawamura,%20Yusuke&rft.date=2010-10&rft.volume=40&rft.issue=10&rft.spage=1006&rft.epage=1014&rft.pages=1006-1014&rft.issn=1386-6346&rft.eissn=1872-034X&rft_id=info:doi/10.1111/j.1872-034X.2010.00703.x&rft_dat=%3Cproquest_cross%3E756663520%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=756663520&rft_id=info:pmid/20887336&rfr_iscdi=true |