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<meta name="DC.Title" content="Role of Perfusion CT in Glioma Grading and Comparison with Conventional MR Imaging Features" />
<meta name="DC.Identifier" content="10.3174/ajnr.A0688" />
<meta name="DC.Date" content="2007-11-01" />
<meta name="DC.Publisher" content="American Journal of Neuroradiology" />
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<meta name="DC.Description" content="BACKGROUND AND PURPOSE: Perfusion imaging using CT can provide additional information about tumor vascularity and angiogenesis for characterizing gliomas. The purpose of our study was to demonstrate the usefulness of various perfusion CT (PCT) parameters in assessing the grade of treatment-naïve gliomas and also to compare it with conventional MR imaging features.

MATERIALS AND METHODS: PCT was performed in 19 patients with glioma (14 high-grade gliomas and 5 low-grade gliomas). Normalized ratios of the PCT parameters (normalized cerebral blood volume [nCBV], normalized cerebral blood flow [nCBF], normalized mean transit time [nMTT]) were used for final analysis. Conventional MR imaging features of these tumors were assessed separately and compared with PCT parameters. Low- and high-grade gliomas were compared by using the nonparametric Wilcoxon 2-sample tests.

RESULTS: Mean nCBV in the high- and low-grade gliomas was 3.06 ± 1.35 and 1.44 ± 0.42, respectively, with a statistically significant difference between the 2 groups ( P = .005). Mean nCBF for the high- and low-grade gliomas was 3.03 ± 2.16 and 1.16 ± 0.36, respectively, with a statistically significant difference between the 2 groups ( P = .045). Cut points of &gt;1.92 for nCBV (85.7% sensitivity and 100% specificity), &gt;1.48 for nCBF (71.4% sensitivity and 100% specificity), and &lt;1.94 for nMTT (92.9% sensitivity and 40% specificity) were found to identify the high-grade gliomas. nCBV was the single best parameter; however, using either nCBV of &gt;1.92 or nCBF of &gt;1.48 improved the sensitivity and specificity to 92.9% and 100%, respectively. The sensitivity and specificity for diagnosing a high-grade glioma with conventional MR imaging were 85.7% and 60%, respectively.

CONCLUSIONS: PCT can be used for preoperative grading of gliomas and can provide valuable complementary information about tumor hemodynamics, not available with conventional imaging techniques. nCBV was the single best parameter correlating with glioma grades, though using nCBF when nCBV was &lt;1.92 improved the sensitivity. An nCBV threshold of &gt;1.92 was found to identify the high-grade gliomas." />
<meta name="DC.Contributor" content="S.K. Ellika" />
<meta name="DC.Contributor" content="R. Jain" />
<meta name="DC.Contributor" content="S.C. Patel" />
<meta name="DC.Contributor" content="L. Scarpace" />
<meta name="DC.Contributor" content="L.R. Schultz" />
<meta name="DC.Contributor" content="J.P. Rock" />
<meta name="DC.Contributor" content="T. Mikkelsen" />
<meta name="article:published_time" content="2007-11-01" />
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<meta name="citation_title" content="Role of Perfusion CT in Glioma Grading and Comparison with Conventional MR Imaging Features" />
<meta name="citation_abstract" lang="en" content="&lt;p&gt;&lt;b&gt;BACKGROUND AND PURPOSE:&lt;/b&gt; Perfusion imaging using CT can provide additional information about tumor vascularity and angiogenesis for characterizing gliomas. The purpose of our study was to demonstrate the usefulness of various perfusion CT (PCT) parameters in assessing the grade of treatment-naïve gliomas and also to compare it with conventional MR imaging features.&lt;/p&gt;&lt;p&gt;&lt;b&gt;MATERIALS AND METHODS:&lt;/b&gt; PCT was performed in 19 patients with glioma (14 high-grade gliomas and 5 low-grade gliomas). Normalized ratios of the PCT parameters (normalized cerebral blood volume [nCBV], normalized cerebral blood flow [nCBF], normalized mean transit time [nMTT]) were used for final analysis. Conventional MR imaging features of these tumors were assessed separately and compared with PCT parameters. Low- and high-grade gliomas were compared by using the nonparametric Wilcoxon 2-sample tests.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS:&lt;/b&gt; Mean nCBV in the high- and low-grade gliomas was 3.06 ± 1.35 and 1.44 ± 0.42, respectively, with a statistically significant difference between the 2 groups (&lt;i&gt;P&lt;/i&gt; = .005). Mean nCBF for the high- and low-grade gliomas was 3.03 ± 2.16 and 1.16 ± 0.36, respectively, with a statistically significant difference between the 2 groups (&lt;i&gt;P&lt;/i&gt; = .045). Cut points of &amp;gt;1.92 for nCBV (85.7% sensitivity and 100% specificity), &amp;gt;1.48 for nCBF (71.4% sensitivity and 100% specificity), and &amp;lt;1.94 for nMTT (92.9% sensitivity and 40% specificity) were found to identify the high-grade gliomas. nCBV was the single best parameter; however, using either nCBV of &amp;gt;1.92 or nCBF of &amp;gt;1.48 improved the sensitivity and specificity to 92.9% and 100%, respectively. The sensitivity and specificity for diagnosing a high-grade glioma with conventional MR imaging were 85.7% and 60%, respectively.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS:&lt;/b&gt; PCT can be used for preoperative grading of gliomas and can provide valuable complementary information about tumor hemodynamics, not available with conventional imaging techniques. nCBV was the single best parameter correlating with glioma grades, though using nCBF when nCBV was &amp;lt;1.92 improved the sensitivity. An nCBV threshold of &amp;gt;1.92 was found to identify the high-grade gliomas.&lt;/p&gt;" />
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<meta name="twitter:title" content="Role of Perfusion CT in Glioma Grading and Comparison with Conventional MR Imaging Features" />
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<meta name="twitter:description" content="BACKGROUND AND PURPOSE: Perfusion imaging using CT can provide additional information about tumor vascularity and angiogenesis for characterizing gliomas. The purpose of our study was to demonstrate the usefulness of various perfusion CT (PCT) parameters in assessing the grade of treatment-naïve gliomas and also to compare it with conventional MR imaging features.

MATERIALS AND METHODS: PCT was performed in 19 patients with glioma (14 high-grade gliomas and 5 low-grade gliomas). Normalized ratios of the PCT parameters (normalized cerebral blood volume [nCBV], normalized cerebral blood flow [nCBF], normalized mean transit time [nMTT]) were used for final analysis. Conventional MR imaging features of these tumors were assessed separately and compared with PCT parameters. Low- and high-grade gliomas were compared by using the nonparametric Wilcoxon 2-sample tests.

RESULTS: Mean nCBV in the high- and low-grade gliomas was 3.06 ± 1.35 and 1.44 ± 0.42, respectively, with a statistically significant difference between the 2 groups ( P = .005). Mean nCBF for the high- and low-grade gliomas was 3.03 ± 2.16 and 1.16 ± 0.36, respectively, with a statistically significant difference between the 2 groups ( P = .045). Cut points of &gt;1.92 for nCBV (85.7% sensitivity and 100% specificity), &gt;1.48 for nCBF (71.4% sensitivity and 100% specificity), and &lt;1.94 for nMTT (92.9% sensitivity and 40% specificity) were found to identify the high-grade gliomas. nCBV was the single best parameter; however, using either nCBV of &gt;1.92 or nCBF of &gt;1.48 improved the sensitivity and specificity to 92.9% and 100%, respectively. The sensitivity and specificity for diagnosing a high-grade glioma with conventional MR imaging were 85.7% and 60%, respectively.

CONCLUSIONS: PCT can be used for preoperative grading of gliomas and can provide valuable complementary information about tumor hemodynamics, not available with conventional imaging techniques. nCBV was the single best parameter correlating with glioma grades, though using nCBF when nCBV was &lt;1.92 improved the sensitivity. An nCBV threshold of &gt;1.92 was found to identify the high-grade gliomas." />
<meta name="og-title" property="og:title" content="Role of Perfusion CT in Glioma Grading and Comparison with Conventional MR Imaging Features" />
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<meta name="og-site-name" property="og:site_name" content="American Journal of Neuroradiology" />
<meta name="og-description" property="og:description" content="BACKGROUND AND PURPOSE: Perfusion imaging using CT can provide additional information about tumor vascularity and angiogenesis for characterizing gliomas. The purpose of our study was to demonstrate the usefulness of various perfusion CT (PCT) parameters in assessing the grade of treatment-naïve gliomas and also to compare it with conventional MR imaging features.

MATERIALS AND METHODS: PCT was performed in 19 patients with glioma (14 high-grade gliomas and 5 low-grade gliomas). Normalized ratios of the PCT parameters (normalized cerebral blood volume [nCBV], normalized cerebral blood flow [nCBF], normalized mean transit time [nMTT]) were used for final analysis. Conventional MR imaging features of these tumors were assessed separately and compared with PCT parameters. Low- and high-grade gliomas were compared by using the nonparametric Wilcoxon 2-sample tests.

RESULTS: Mean nCBV in the high- and low-grade gliomas was 3.06 ± 1.35 and 1.44 ± 0.42, respectively, with a statistically significant difference between the 2 groups ( P = .005). Mean nCBF for the high- and low-grade gliomas was 3.03 ± 2.16 and 1.16 ± 0.36, respectively, with a statistically significant difference between the 2 groups ( P = .045). Cut points of &gt;1.92 for nCBV (85.7% sensitivity and 100% specificity), &gt;1.48 for nCBF (71.4% sensitivity and 100% specificity), and &lt;1.94 for nMTT (92.9% sensitivity and 40% specificity) were found to identify the high-grade gliomas. nCBV was the single best parameter; however, using either nCBV of &gt;1.92 or nCBF of &gt;1.48 improved the sensitivity and specificity to 92.9% and 100%, respectively. The sensitivity and specificity for diagnosing a high-grade glioma with conventional MR imaging were 85.7% and 60%, respectively.

CONCLUSIONS: PCT can be used for preoperative grading of gliomas and can provide valuable complementary information about tumor hemodynamics, not available with conventional imaging techniques. nCBV was the single best parameter correlating with glioma grades, though using nCBF when nCBV was &lt;1.92 improved the sensitivity. An nCBV threshold of &gt;1.92 was found to identify the high-grade gliomas." />
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    <div class="highwire-article-citation highwire-citation-type-highwire-article node7426--5" data-node-nid="7426" id="top-node-7426--6809268764" data-pisa="ajnr;28/10/1981" data-pisa-master="ajnr;ajnr.A0688" data-apath="/ajnr/28/10/1981.atom" data-hw-author-tooltip-instance="highwire_author_tooltip"><div class="highwire-cite highwire-cite-highwire-article highwire-citation-jcore-article-title-complete clearfix has-author-tooltip highwire-citation-highwire-article-top-a">
  
  
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      <h1 class="highwire-cite-title" id="page-title">Role of Perfusion CT in Glioma Grading and Comparison with Conventional MR Imaging Features</h1>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">S.K. Ellika</span>, <span class="highwire-citation-author" data-delta="1">R. Jain</span>, <span class="highwire-citation-author" data-delta="2">S.C. Patel</span>, <span class="highwire-citation-author" data-delta="3">L. Scarpace</span>, <span class="highwire-citation-author" data-delta="4">L.R. Schultz</span>, <span class="highwire-citation-author" data-delta="5">J.P. Rock</span> and <span class="highwire-citation-author" data-delta="6">T. Mikkelsen</span></span></div>
  
    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">November 2007,  </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">28 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(10) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">1981-1987; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A0688 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-7426--6809268764" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">S.K. Ellika </div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=S.K.%2BEllika%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Ellika%20S&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link last"><a href="/search/author1%3AS.K.%2BEllika%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div><div class="author-tooltip-1"><div class="author-tooltip-name">R. 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Rock </div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=J.P.%2BRock%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Rock%20J&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link last"><a href="/search/author1%3AJ.P.%2BRock%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div><div class="author-tooltip-6"><div class="author-tooltip-name">T. 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    <div class="highwire-markup"><div xmlns="http://www.w3.org/1999/xhtml" data-highwire-cite-ref-tooltip-instance="highwire_reflinks_tooltip" class="content-block-markup" xmlns:xhtml="http://www.w3.org/1999/xhtml"><div class="article abstract-view"><span class="highwire-journal-article-marker-start"></span><div class="section abstract" id="abstract-1"><h2>Abstract</h2><p id="p-1"><strong>BACKGROUND AND PURPOSE:</strong> Perfusion imaging using CT can provide additional information about tumor vascularity and angiogenesis for characterizing gliomas. The purpose of our study was to demonstrate the usefulness of various perfusion CT (PCT) parameters in assessing the grade of treatment-naïve gliomas and also to compare it with conventional MR imaging features.</p><p id="p-2"><strong>MATERIALS AND METHODS:</strong> PCT was performed in 19 patients with glioma (14 high-grade gliomas and 5 low-grade gliomas). Normalized ratios of the PCT parameters (normalized cerebral blood volume [nCBV], normalized cerebral blood flow [nCBF], normalized mean transit time [nMTT]) were used for final analysis. Conventional MR imaging features of these tumors were assessed separately and compared with PCT parameters. Low- and high-grade gliomas were compared by using the nonparametric Wilcoxon 2-sample tests.</p><p id="p-3"><strong>RESULTS:</strong> Mean nCBV in the high- and low-grade gliomas was 3.06 ± 1.35 and 1.44 ± 0.42, respectively, with a statistically significant difference between the 2 groups (<em>P</em> = .005). Mean nCBF for the high- and low-grade gliomas was 3.03 ± 2.16 and 1.16 ± 0.36, respectively, with a statistically significant difference between the 2 groups (<em>P</em> = .045). Cut points of &gt;1.92 for nCBV (85.7% sensitivity and 100% specificity), &gt;1.48 for nCBF (71.4% sensitivity and 100% specificity), and &lt;1.94 for nMTT (92.9% sensitivity and 40% specificity) were found to identify the high-grade gliomas. nCBV was the single best parameter; however, using either nCBV of &gt;1.92 or nCBF of &gt;1.48 improved the sensitivity and specificity to 92.9% and 100%, respectively. The sensitivity and specificity for diagnosing a high-grade glioma with conventional MR imaging were 85.7% and 60%, respectively.</p><p id="p-4"><strong>CONCLUSIONS:</strong> PCT can be used for preoperative grading of gliomas and can provide valuable complementary information about tumor hemodynamics, not available with conventional imaging techniques. nCBV was the single best parameter correlating with glioma grades, though using nCBF when nCBV was &lt;1.92 improved the sensitivity. An nCBV threshold of &gt;1.92 was found to identify the high-grade gliomas.</p></div><ul class="copyright-statement"><li class="fn" id="copyright-statement-1">Copyright © American Society of Neuroradiology</li></ul><span class="highwire-journal-article-marker-end"></span></div><span class="related-urls"></span></div><a href="http://ajnr-stage2.stage.highwire.org/content/28/10/1981.full" class="hw-link hw-link-article-full-text" data-icon-position="" data-hide-link-title="0">View Full Text</a></div>  </div>

  
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        	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-volume highwire-cite-metadata">Vol. 28</span>, <span  class="highwire-cite-metadata-issue highwire-cite-metadata">Issue 10 </span><div  class="highwire-cite-metadata-pubdate highwire-cite-metadata">November 2007 </div></div>
      
      
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      <div class="highwire-cite-title">Role of Perfusion CT in Glioma Grading and Comparison with Conventional MR Imaging Features</div>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0"><span class="nlm-given-names">S.K.</span> <span class="nlm-surname">Ellika</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">R.</span> <span class="nlm-surname">Jain</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">S.C.</span> <span class="nlm-surname">Patel</span></span>, <span class="highwire-citation-author" data-delta="3"><span class="nlm-given-names">L.</span> <span class="nlm-surname">Scarpace</span></span>, <span class="highwire-citation-author" data-delta="4"><span class="nlm-given-names">L.R.</span> <span class="nlm-surname">Schultz</span></span>, <span class="highwire-citation-author" data-delta="5"><span class="nlm-given-names">J.P.</span> <span class="nlm-surname">Rock</span></span>, <span class="highwire-citation-author" data-delta="6"><span class="nlm-given-names">T.</span> <span class="nlm-surname">Mikkelsen</span></span></span></div>
  
    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">Nov 2007, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">28 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(10) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">1981-1987; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A0688 </span></div>
  
  
  
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      <div class="highwire-cite-title">Role of Perfusion CT in Glioma Grading and Comparison with Conventional MR Imaging Features</div>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0"><span class="nlm-given-names">S.K.</span> <span class="nlm-surname">Ellika</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">R.</span> <span class="nlm-surname">Jain</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">S.C.</span> <span class="nlm-surname">Patel</span></span>, <span class="highwire-citation-author" data-delta="3"><span class="nlm-given-names">L.</span> <span class="nlm-surname">Scarpace</span></span>, <span class="highwire-citation-author" data-delta="4"><span class="nlm-given-names">L.R.</span> <span class="nlm-surname">Schultz</span></span>, <span class="highwire-citation-author" data-delta="5"><span class="nlm-given-names">J.P.</span> <span class="nlm-surname">Rock</span></span>, <span class="highwire-citation-author" data-delta="6"><span class="nlm-given-names">T.</span> <span class="nlm-surname">Mikkelsen</span></span></span></div>
  
    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">Nov 2007, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">28 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(10) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">1981-1987; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A0688 </span></div>
  
  
  
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