MRI characteristics for differentiating mucinous borderline ovarian tumours from mucinous ovarian cancers
To investigate the magnetic resonance imaging (MRI) characteristics that could differentiate mucinous borderline ovarian tumours (MBOTs) from mucinous ovarian cancers (MOCs). MRI data from 75 patients with MBOTs and 38 patients with MOCs were reviewed retrospectively. The clinicopathological and MRI...
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| Veröffentlicht in: | Clinical radiology 2022-02, Vol.77 (2), p.142-147 |
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| creator | Yang, X.Y. Li, X. Ma, F.H. Li, H.M. Zhao, S.H. Li, Y.A. Qiang, J.W. |
| description | To investigate the magnetic resonance imaging (MRI) characteristics that could differentiate mucinous borderline ovarian tumours (MBOTs) from mucinous ovarian cancers (MOCs).
MRI data from 75 patients with MBOTs and 38 patients with MOCs were reviewed retrospectively. The clinicopathological and MRI features, including age, bilaterality, maximum diameter (MD), shape, margin, configuration, cystic–solid interface, papillae, MD of the cyst walls and septa, MD of the solid components, number of cysts, honeycomb loculi, signal of the cystic and solid components, apparent diffusion coefficient (ADC) value and enhancement ratio of the solid components, peritoneal implants and ascites, were compared using univariable analysis and multivariable logistic regression analysis.
There were 76 MBOTs and 39 MOCs, and median patient age was 41 years (range 16–77 years) and 51 years (range 15–90 years), respectively (p=0.004). There were significant differences between MBOTs and MOCs regarding the presence of papillae (p=0.013), MD of the solid components (p=0.001), enhancement ratio of the solid components (p=0.003), ADC value (p |
| doi_str_mv | 10.1016/j.crad.2021.10.022 |
| format | Article |
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MRI data from 75 patients with MBOTs and 38 patients with MOCs were reviewed retrospectively. The clinicopathological and MRI features, including age, bilaterality, maximum diameter (MD), shape, margin, configuration, cystic–solid interface, papillae, MD of the cyst walls and septa, MD of the solid components, number of cysts, honeycomb loculi, signal of the cystic and solid components, apparent diffusion coefficient (ADC) value and enhancement ratio of the solid components, peritoneal implants and ascites, were compared using univariable analysis and multivariable logistic regression analysis.
There were 76 MBOTs and 39 MOCs, and median patient age was 41 years (range 16–77 years) and 51 years (range 15–90 years), respectively (p=0.004). There were significant differences between MBOTs and MOCs regarding the presence of papillae (p=0.013), MD of the solid components (p=0.001), enhancement ratio of the solid components (p=0.003), ADC value (p<0.001), and ascites (p<0.001). The optimal cut-off ADC value was 1.16 × 10−3 mm2/s, with a sensitivity of 87.1%, a specificity of 83.3%, and an area under the curve (AUC) of 0.917.
Compared with MOCs, MBOTs had fewer papillae or solid components, lower enhancement ratio, higher ADC values, and were less likely to have moderate or massive ascites.
•MRI can be used to differentiate MBOTs and MOCs.•Compared with MOCs, MBOTs have lower enhancement ratio and higher ADC values.•In contrast to MOCs, MBOTs frequently have fewer solid components or ascites.•The cut-off ADC value to distinguish MBOTs from MOCs is 1.16 × 10−3 mm2/s.</description><identifier>ISSN: 0009-9260</identifier><identifier>EISSN: 1365-229X</identifier><identifier>DOI: 10.1016/j.crad.2021.10.022</identifier><identifier>PMID: 34848025</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Adolescent ; Adult ; Aged ; Carcinoma, Ovarian Epithelial - diagnostic imaging ; Diagnosis, Differential ; Female ; Humans ; Magnetic Resonance Imaging - methods ; Middle Aged ; Ovarian Neoplasms - diagnostic imaging ; Ovary - diagnostic imaging ; Retrospective Studies ; Young Adult</subject><ispartof>Clinical radiology, 2022-02, Vol.77 (2), p.142-147</ispartof><rights>2021 The Royal College of Radiologists</rights><rights>Copyright © 2021 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c356t-987cbebab4a8d16200c4b835b27b97621cd0db1ae4f9642507b0efcf0df57a263</citedby><cites>FETCH-LOGICAL-c356t-987cbebab4a8d16200c4b835b27b97621cd0db1ae4f9642507b0efcf0df57a263</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0009926021005286$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65534</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34848025$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yang, X.Y.</creatorcontrib><creatorcontrib>Li, X.</creatorcontrib><creatorcontrib>Ma, F.H.</creatorcontrib><creatorcontrib>Li, H.M.</creatorcontrib><creatorcontrib>Zhao, S.H.</creatorcontrib><creatorcontrib>Li, Y.A.</creatorcontrib><creatorcontrib>Qiang, J.W.</creatorcontrib><title>MRI characteristics for differentiating mucinous borderline ovarian tumours from mucinous ovarian cancers</title><title>Clinical radiology</title><addtitle>Clin Radiol</addtitle><description>To investigate the magnetic resonance imaging (MRI) characteristics that could differentiate mucinous borderline ovarian tumours (MBOTs) from mucinous ovarian cancers (MOCs).
MRI data from 75 patients with MBOTs and 38 patients with MOCs were reviewed retrospectively. The clinicopathological and MRI features, including age, bilaterality, maximum diameter (MD), shape, margin, configuration, cystic–solid interface, papillae, MD of the cyst walls and septa, MD of the solid components, number of cysts, honeycomb loculi, signal of the cystic and solid components, apparent diffusion coefficient (ADC) value and enhancement ratio of the solid components, peritoneal implants and ascites, were compared using univariable analysis and multivariable logistic regression analysis.
There were 76 MBOTs and 39 MOCs, and median patient age was 41 years (range 16–77 years) and 51 years (range 15–90 years), respectively (p=0.004). There were significant differences between MBOTs and MOCs regarding the presence of papillae (p=0.013), MD of the solid components (p=0.001), enhancement ratio of the solid components (p=0.003), ADC value (p<0.001), and ascites (p<0.001). The optimal cut-off ADC value was 1.16 × 10−3 mm2/s, with a sensitivity of 87.1%, a specificity of 83.3%, and an area under the curve (AUC) of 0.917.
Compared with MOCs, MBOTs had fewer papillae or solid components, lower enhancement ratio, higher ADC values, and were less likely to have moderate or massive ascites.
•MRI can be used to differentiate MBOTs and MOCs.•Compared with MOCs, MBOTs have lower enhancement ratio and higher ADC values.•In contrast to MOCs, MBOTs frequently have fewer solid components or ascites.•The cut-off ADC value to distinguish MBOTs from MOCs is 1.16 × 10−3 mm2/s.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Aged</subject><subject>Carcinoma, Ovarian Epithelial - diagnostic imaging</subject><subject>Diagnosis, Differential</subject><subject>Female</subject><subject>Humans</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Middle Aged</subject><subject>Ovarian Neoplasms - diagnostic imaging</subject><subject>Ovary - diagnostic imaging</subject><subject>Retrospective Studies</subject><subject>Young Adult</subject><issn>0009-9260</issn><issn>1365-229X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kEtr3DAURkVp6EzS_oEsipfdeCLJkh_QTRnyGEgIhASyE3pcpRrG1vTKDuTfR2aSdJeV0NX5Pq4OIaeMrhhl9dl2ZVG7Faec5cGKcv6FLFlVy5Lz7vErWVJKu7LjNV2Q45S281Vw8Y0sKtGKlnK5JOHmblPYvxq1HQFDGoNNhY9YuOA9IAxj0GMYnop-smGIUypMRAe4CwMU8Vlj0EMxTn2cMOcw9v_B91erBwuYvpMjr3cJfrydJ-Th4vx-fVVe315u1n-uS1vJeiy7trEGjDZCt47VnFIrTFtJwxvTNTVn1lFnmAbhu1pwSRtDwVtPnZeN5nV1Qn4devcY_02QRtWHZGG30wPktVTWIXnFhJQZ5QfUYkwJwas9hl7ji2JUzYrVVs2K1ax4nmXFOfTzrX8yPbiPyLvTDPw-AJB_-RwAVbIBsgMXEOyoXAyf9b8CbCOPsw</recordid><startdate>202202</startdate><enddate>202202</enddate><creator>Yang, X.Y.</creator><creator>Li, X.</creator><creator>Ma, F.H.</creator><creator>Li, H.M.</creator><creator>Zhao, S.H.</creator><creator>Li, Y.A.</creator><creator>Qiang, J.W.</creator><general>Elsevier Ltd</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>7X8</scope></search><sort><creationdate>202202</creationdate><title>MRI characteristics for differentiating mucinous borderline ovarian tumours from mucinous ovarian cancers</title><author>Yang, X.Y. ; Li, X. ; Ma, F.H. ; Li, H.M. ; Zhao, S.H. ; Li, Y.A. ; Qiang, J.W.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c356t-987cbebab4a8d16200c4b835b27b97621cd0db1ae4f9642507b0efcf0df57a263</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Aged</topic><topic>Carcinoma, Ovarian Epithelial - diagnostic imaging</topic><topic>Diagnosis, Differential</topic><topic>Female</topic><topic>Humans</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Middle Aged</topic><topic>Ovarian Neoplasms - diagnostic imaging</topic><topic>Ovary - diagnostic imaging</topic><topic>Retrospective Studies</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yang, X.Y.</creatorcontrib><creatorcontrib>Li, X.</creatorcontrib><creatorcontrib>Ma, F.H.</creatorcontrib><creatorcontrib>Li, H.M.</creatorcontrib><creatorcontrib>Zhao, S.H.</creatorcontrib><creatorcontrib>Li, Y.A.</creatorcontrib><creatorcontrib>Qiang, J.W.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Clinical radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yang, X.Y.</au><au>Li, X.</au><au>Ma, F.H.</au><au>Li, H.M.</au><au>Zhao, S.H.</au><au>Li, Y.A.</au><au>Qiang, J.W.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MRI characteristics for differentiating mucinous borderline ovarian tumours from mucinous ovarian cancers</atitle><jtitle>Clinical radiology</jtitle><addtitle>Clin Radiol</addtitle><date>2022-02</date><risdate>2022</risdate><volume>77</volume><issue>2</issue><spage>142</spage><epage>147</epage><pages>142-147</pages><issn>0009-9260</issn><eissn>1365-229X</eissn><abstract>To investigate the magnetic resonance imaging (MRI) characteristics that could differentiate mucinous borderline ovarian tumours (MBOTs) from mucinous ovarian cancers (MOCs).
MRI data from 75 patients with MBOTs and 38 patients with MOCs were reviewed retrospectively. The clinicopathological and MRI features, including age, bilaterality, maximum diameter (MD), shape, margin, configuration, cystic–solid interface, papillae, MD of the cyst walls and septa, MD of the solid components, number of cysts, honeycomb loculi, signal of the cystic and solid components, apparent diffusion coefficient (ADC) value and enhancement ratio of the solid components, peritoneal implants and ascites, were compared using univariable analysis and multivariable logistic regression analysis.
There were 76 MBOTs and 39 MOCs, and median patient age was 41 years (range 16–77 years) and 51 years (range 15–90 years), respectively (p=0.004). There were significant differences between MBOTs and MOCs regarding the presence of papillae (p=0.013), MD of the solid components (p=0.001), enhancement ratio of the solid components (p=0.003), ADC value (p<0.001), and ascites (p<0.001). The optimal cut-off ADC value was 1.16 × 10−3 mm2/s, with a sensitivity of 87.1%, a specificity of 83.3%, and an area under the curve (AUC) of 0.917.
Compared with MOCs, MBOTs had fewer papillae or solid components, lower enhancement ratio, higher ADC values, and were less likely to have moderate or massive ascites.
•MRI can be used to differentiate MBOTs and MOCs.•Compared with MOCs, MBOTs have lower enhancement ratio and higher ADC values.•In contrast to MOCs, MBOTs frequently have fewer solid components or ascites.•The cut-off ADC value to distinguish MBOTs from MOCs is 1.16 × 10−3 mm2/s.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>34848025</pmid><doi>10.1016/j.crad.2021.10.022</doi><tpages>6</tpages></addata></record> |
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| subjects | Adolescent Adult Aged Carcinoma, Ovarian Epithelial - diagnostic imaging Diagnosis, Differential Female Humans Magnetic Resonance Imaging - methods Middle Aged Ovarian Neoplasms - diagnostic imaging Ovary - diagnostic imaging Retrospective Studies Young Adult |
| title | MRI characteristics for differentiating mucinous borderline ovarian tumours from mucinous ovarian cancers |
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