The Added Value of Inflow-Based Vascular-Space-Occupancy and Diffusion-Weighted Imaging in Preoperative Grading of Gliomas
Objectives: The present study aimed to study whether combined inflow-based vascular-space-occupancy (iVASO) MR imaging (MRI) and diffusion-weighted imaging (DWI) improve the diagnostic accuracy in the preoperative grading of gliomas. Methods: Fifty-one patients with histopathologically confirmed dif...
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Veröffentlicht in: | Neuro-degenerative diseases 2021-05, Vol.20 (4), p.123-130 |
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creator | Cao, Haimei Xiao, Xiang Hua, Jun Huang, Guanglong He, Wenle Qin, Jie Wu, Yuankui Li, Xiaodan |
description | Objectives: The present study aimed to study whether combined inflow-based vascular-space-occupancy (iVASO) MR imaging (MRI) and diffusion-weighted imaging (DWI) improve the diagnostic accuracy in the preoperative grading of gliomas. Methods: Fifty-one patients with histopathologically confirmed diffuse gliomas underwent preoperative structural MRI, iVASO, and DWI. We performed 2 qualitative consensus reviews: (1) structural MR images alone and (2) structural MR images with iVASO and DWI. Relative arteriolar cerebral blood volume (rCBVa) and minimum apparent diffusion coefficient (mADC) were compared between low-grade and high-grade gliomas. Receiver operating characteristic (ROC) curve analysis was performed to compare the tumor grading efficiency of rCBVa, mADC, and the combination of the two parameters. Results: Two observers diagnosed accurate tumor grade in 40 of 51 (78.4%) patients in the first review and in 46 of 51 (90.2%) in the second review. Both rCBVa and mADC showed significant differences between low-grade and high-grade gliomas. ROC analysis gave a threshold value of 1.52 for rCBVa and 0.85 × 10 −3 mm 2 /s for mADC to provide a sensitivity and specificity of 88.0 and 81.2% and 100.0 and 68.7%, respectively. The area under the ROC curve (AUC) was 0.87 and 0.85 for rCBVa and mADC, respectively. The combination of rCBVa and mADC values increased the AUC to 0.92. Conclusion: The combined application of iVASO and DWI may improve the diagnostic accuracy of glioma grading. |
doi_str_mv | 10.1159/000512545 |
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Methods: Fifty-one patients with histopathologically confirmed diffuse gliomas underwent preoperative structural MRI, iVASO, and DWI. We performed 2 qualitative consensus reviews: (1) structural MR images alone and (2) structural MR images with iVASO and DWI. Relative arteriolar cerebral blood volume (rCBVa) and minimum apparent diffusion coefficient (mADC) were compared between low-grade and high-grade gliomas. Receiver operating characteristic (ROC) curve analysis was performed to compare the tumor grading efficiency of rCBVa, mADC, and the combination of the two parameters. Results: Two observers diagnosed accurate tumor grade in 40 of 51 (78.4%) patients in the first review and in 46 of 51 (90.2%) in the second review. Both rCBVa and mADC showed significant differences between low-grade and high-grade gliomas. ROC analysis gave a threshold value of 1.52 for rCBVa and 0.85 × 10 −3 mm 2 /s for mADC to provide a sensitivity and specificity of 88.0 and 81.2% and 100.0 and 68.7%, respectively. The area under the ROC curve (AUC) was 0.87 and 0.85 for rCBVa and mADC, respectively. The combination of rCBVa and mADC values increased the AUC to 0.92. Conclusion: The combined application of iVASO and DWI may improve the diagnostic accuracy of glioma grading.</description><identifier>ISSN: 1660-2854</identifier><identifier>EISSN: 1660-2862</identifier><identifier>DOI: 10.1159/000512545</identifier><identifier>PMID: 33735873</identifier><language>eng</language><publisher>Basel, Switzerland: S. Karger AG</publisher><subject>Development and progression ; Diagnosis ; Gliomas ; Magnetic resonance imaging ; Methods ; Research Article ; Tumor staging</subject><ispartof>Neuro-degenerative diseases, 2021-05, Vol.20 (4), p.123-130</ispartof><rights>2021 S. Karger AG, Basel</rights><rights>2021 S. Karger AG, Basel.</rights><rights>COPYRIGHT 2021 S. Karger AG</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c432t-3bcc756c98308c9fb282027aa9b5d68cba5ee8b2c27bbc748e89a1d3f2fdce913</citedby><cites>FETCH-LOGICAL-c432t-3bcc756c98308c9fb282027aa9b5d68cba5ee8b2c27bbc748e89a1d3f2fdce913</cites><orcidid>0000-0002-5140-4860</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,2429,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33735873$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Cao, Haimei</creatorcontrib><creatorcontrib>Xiao, Xiang</creatorcontrib><creatorcontrib>Hua, Jun</creatorcontrib><creatorcontrib>Huang, Guanglong</creatorcontrib><creatorcontrib>He, Wenle</creatorcontrib><creatorcontrib>Qin, Jie</creatorcontrib><creatorcontrib>Wu, Yuankui</creatorcontrib><creatorcontrib>Li, Xiaodan</creatorcontrib><title>The Added Value of Inflow-Based Vascular-Space-Occupancy and Diffusion-Weighted Imaging in Preoperative Grading of Gliomas</title><title>Neuro-degenerative diseases</title><addtitle>Neurodegener Dis</addtitle><description>Objectives: The present study aimed to study whether combined inflow-based vascular-space-occupancy (iVASO) MR imaging (MRI) and diffusion-weighted imaging (DWI) improve the diagnostic accuracy in the preoperative grading of gliomas. Methods: Fifty-one patients with histopathologically confirmed diffuse gliomas underwent preoperative structural MRI, iVASO, and DWI. We performed 2 qualitative consensus reviews: (1) structural MR images alone and (2) structural MR images with iVASO and DWI. Relative arteriolar cerebral blood volume (rCBVa) and minimum apparent diffusion coefficient (mADC) were compared between low-grade and high-grade gliomas. Receiver operating characteristic (ROC) curve analysis was performed to compare the tumor grading efficiency of rCBVa, mADC, and the combination of the two parameters. Results: Two observers diagnosed accurate tumor grade in 40 of 51 (78.4%) patients in the first review and in 46 of 51 (90.2%) in the second review. Both rCBVa and mADC showed significant differences between low-grade and high-grade gliomas. ROC analysis gave a threshold value of 1.52 for rCBVa and 0.85 × 10 −3 mm 2 /s for mADC to provide a sensitivity and specificity of 88.0 and 81.2% and 100.0 and 68.7%, respectively. The area under the ROC curve (AUC) was 0.87 and 0.85 for rCBVa and mADC, respectively. The combination of rCBVa and mADC values increased the AUC to 0.92. Conclusion: The combined application of iVASO and DWI may improve the diagnostic accuracy of glioma grading.</description><subject>Development and progression</subject><subject>Diagnosis</subject><subject>Gliomas</subject><subject>Magnetic resonance imaging</subject><subject>Methods</subject><subject>Research Article</subject><subject>Tumor staging</subject><issn>1660-2854</issn><issn>1660-2862</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNpt0d2L1DAQAPAiineePvguUjgQfeiZj2bbPq63ui4cnuCpj2WaTLrRtKlJq5x_vVl7Fg-OPCRMfjMwM0nylJIzSkX1mhAiKBO5uJcc09WKZKxcsfvLW-RHyaMQvhHCqqKiD5MjzgsuyoIfJ7-v9piulUKVfgE7Yep0uuu1db-yNxD-RoOcLPjs0wASs0sppwF6eZ1Cr9KN0XoKxvXZVzTtfox-10Fr-jY1ffrRoxvQw2h-Yrr1oA7xWH9rjesgPE4eaLABn9zcJ8nnd2-vzt9nF5fb3fn6IpM5Z2PGGykLsZJVyUkpK92wkhFWAFSNUKtSNiAQy4ZJVjSNLPISywqo4pppJbGi_CR5OdcdvPsxYRjrzgSJ1kKPbgo1E4TnvKw4j_R0pi1YrE2v3ehBHni9LkicGhO0iOrsDhWPws5I16M2MX4r4cV_CXsEO-6Ds9MYJxduw1czlN6F4FHXgzcd-Ouakvqw6npZdbTPb9qamg7VIv_tNoJnM_gOvkW_gCX_9M7vD5vNLOpBaf4HvNi2oA</recordid><startdate>20210501</startdate><enddate>20210501</enddate><creator>Cao, Haimei</creator><creator>Xiao, Xiang</creator><creator>Hua, Jun</creator><creator>Huang, Guanglong</creator><creator>He, Wenle</creator><creator>Qin, Jie</creator><creator>Wu, Yuankui</creator><creator>Li, Xiaodan</creator><general>S. Karger AG</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-5140-4860</orcidid></search><sort><creationdate>20210501</creationdate><title>The Added Value of Inflow-Based Vascular-Space-Occupancy and Diffusion-Weighted Imaging in Preoperative Grading of Gliomas</title><author>Cao, Haimei ; Xiao, Xiang ; Hua, Jun ; Huang, Guanglong ; He, Wenle ; Qin, Jie ; Wu, Yuankui ; Li, Xiaodan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c432t-3bcc756c98308c9fb282027aa9b5d68cba5ee8b2c27bbc748e89a1d3f2fdce913</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Development and progression</topic><topic>Diagnosis</topic><topic>Gliomas</topic><topic>Magnetic resonance imaging</topic><topic>Methods</topic><topic>Research Article</topic><topic>Tumor staging</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cao, Haimei</creatorcontrib><creatorcontrib>Xiao, Xiang</creatorcontrib><creatorcontrib>Hua, Jun</creatorcontrib><creatorcontrib>Huang, Guanglong</creatorcontrib><creatorcontrib>He, Wenle</creatorcontrib><creatorcontrib>Qin, Jie</creatorcontrib><creatorcontrib>Wu, Yuankui</creatorcontrib><creatorcontrib>Li, Xiaodan</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Neuro-degenerative diseases</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cao, Haimei</au><au>Xiao, Xiang</au><au>Hua, Jun</au><au>Huang, Guanglong</au><au>He, Wenle</au><au>Qin, Jie</au><au>Wu, Yuankui</au><au>Li, Xiaodan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Added Value of Inflow-Based Vascular-Space-Occupancy and Diffusion-Weighted Imaging in Preoperative Grading of Gliomas</atitle><jtitle>Neuro-degenerative diseases</jtitle><addtitle>Neurodegener Dis</addtitle><date>2021-05-01</date><risdate>2021</risdate><volume>20</volume><issue>4</issue><spage>123</spage><epage>130</epage><pages>123-130</pages><issn>1660-2854</issn><eissn>1660-2862</eissn><abstract>Objectives: The present study aimed to study whether combined inflow-based vascular-space-occupancy (iVASO) MR imaging (MRI) and diffusion-weighted imaging (DWI) improve the diagnostic accuracy in the preoperative grading of gliomas. Methods: Fifty-one patients with histopathologically confirmed diffuse gliomas underwent preoperative structural MRI, iVASO, and DWI. We performed 2 qualitative consensus reviews: (1) structural MR images alone and (2) structural MR images with iVASO and DWI. Relative arteriolar cerebral blood volume (rCBVa) and minimum apparent diffusion coefficient (mADC) were compared between low-grade and high-grade gliomas. Receiver operating characteristic (ROC) curve analysis was performed to compare the tumor grading efficiency of rCBVa, mADC, and the combination of the two parameters. Results: Two observers diagnosed accurate tumor grade in 40 of 51 (78.4%) patients in the first review and in 46 of 51 (90.2%) in the second review. Both rCBVa and mADC showed significant differences between low-grade and high-grade gliomas. ROC analysis gave a threshold value of 1.52 for rCBVa and 0.85 × 10 −3 mm 2 /s for mADC to provide a sensitivity and specificity of 88.0 and 81.2% and 100.0 and 68.7%, respectively. The area under the ROC curve (AUC) was 0.87 and 0.85 for rCBVa and mADC, respectively. The combination of rCBVa and mADC values increased the AUC to 0.92. Conclusion: The combined application of iVASO and DWI may improve the diagnostic accuracy of glioma grading.</abstract><cop>Basel, Switzerland</cop><pub>S. Karger AG</pub><pmid>33735873</pmid><doi>10.1159/000512545</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-5140-4860</orcidid></addata></record> |
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subjects | Development and progression Diagnosis Gliomas Magnetic resonance imaging Methods Research Article Tumor staging |
title | The Added Value of Inflow-Based Vascular-Space-Occupancy and Diffusion-Weighted Imaging in Preoperative Grading of Gliomas |
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