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<meta name="DC.Title" content="Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using Diffusion Tensor Imaging and Dynamic Susceptibility Contrast MRI" />
<meta name="DC.Identifier" content="10.3174/ajnr.A4474" />
<meta name="DC.Date" content="2016-01-01" />
<meta name="DC.Publisher" content="American Journal of Neuroradiology" />
<meta name="DC.Rights" content="© 2016 by American Journal of Neuroradiology. Indicates open access to non-subscribers at www.ajnr.org" />
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<meta name="DC.Description" content="BACKGROUND AND PURPOSE: Early assessment of treatment response is critical in patients with glioblastomas. A combination of DTI and DSC perfusion imaging parameters was evaluated to distinguish glioblastomas with true progression from mixed response and pseudoprogression.

MATERIALS AND METHODS: Forty-one patients with glioblastomas exhibiting enhancing lesions within 6 months after completion of chemoradiation therapy were retrospectively studied. All patients underwent surgery after MR imaging and were histologically classified as having true progression (&gt;75% tumor), mixed response (25%–75% tumor), or pseudoprogression (&lt;25% tumor). Mean diffusivity, fractional anisotropy, linear anisotropy coefficient, planar anisotropy coefficient, spheric anisotropy coefficient, and maximum relative cerebral blood volume values were measured from the enhancing tissue. A multivariate logistic regression analysis was used to determine the best model for classification of true progression from mixed response or pseudoprogression.

RESULTS: Significantly elevated maximum relative cerebral blood volume, fractional anisotropy, linear anisotropy coefficient, and planar anisotropy coefficient and decreased spheric anisotropy coefficient were observed in true progression compared with pseudoprogression ( P &lt; .05). There were also significant differences in maximum relative cerebral blood volume, fractional anisotropy, planar anisotropy coefficient, and spheric anisotropy coefficient measurements between mixed response and true progression groups. The best model to distinguish true progression from non–true progression (pseudoprogression and mixed) consisted of fractional anisotropy, linear anisotropy coefficient, and maximum relative cerebral blood volume, resulting in an area under the curve of 0.905. This model also differentiated true progression from mixed response with an area under the curve of 0.901. A combination of fractional anisotropy and maximum relative cerebral blood volume differentiated pseudoprogression from nonpseudoprogression (true progression and mixed) with an area under the curve of 0.807.

CONCLUSIONS: DTI and DSC perfusion imaging can improve accuracy in assessing treatment response and may aid in individualized treatment of patients with glioblastomas.

AUC
:   area under the curve
CL
:   linear anisotropy coefficient
CP
:   planar anisotropy coefficient
CS
:   spheric anisotropy coefficient
FA
:   fractional anisotropy
LRM
:   logistic regression model
max
:   maximum
MD
:   mean diffusivity
PsP
:   pseudoprogression
rCBV
:   relative cerebral blood volume
TP
:   true progression" />
<meta name="DC.Contributor" content="S. Wang" />
<meta name="DC.Contributor" content="M. Martinez-Lage" />
<meta name="DC.Contributor" content="Y. Sakai" />
<meta name="DC.Contributor" content="S. Chawla" />
<meta name="DC.Contributor" content="S.G. Kim" />
<meta name="DC.Contributor" content="M. Alonso-Basanta" />
<meta name="DC.Contributor" content="R.A. Lustig" />
<meta name="DC.Contributor" content="S. Brem" />
<meta name="DC.Contributor" content="S. Mohan" />
<meta name="DC.Contributor" content="R.L. Wolf" />
<meta name="DC.Contributor" content="A. Desai" />
<meta name="DC.Contributor" content="H. Poptani" />
<meta name="article:published_time" content="2016-01-01" />
<meta name="article:section" content="ADULT BRAIN" />
<meta name="citation_title" content="Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using Diffusion Tensor Imaging and Dynamic Susceptibility Contrast MRI" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE:&lt;/h3&gt;
&lt;p&gt;Early assessment of treatment response is critical in patients with glioblastomas. A combination of DTI and DSC perfusion imaging parameters was evaluated to distinguish glioblastomas with true progression from mixed response and pseudoprogression.&lt;/p&gt;&lt;h3&gt;MATERIALS AND METHODS:&lt;/h3&gt;
&lt;p&gt;Forty-one patients with glioblastomas exhibiting enhancing lesions within 6 months after completion of chemoradiation therapy were retrospectively studied. All patients underwent surgery after MR imaging and were histologically classified as having true progression (&amp;gt;75% tumor), mixed response (25%–75% tumor), or pseudoprogression (&amp;lt;25% tumor). Mean diffusivity, fractional anisotropy, linear anisotropy coefficient, planar anisotropy coefficient, spheric anisotropy coefficient, and maximum relative cerebral blood volume values were measured from the enhancing tissue. A multivariate logistic regression analysis was used to determine the best model for classification of true progression from mixed response or pseudoprogression.&lt;/p&gt;&lt;h3&gt;RESULTS:&lt;/h3&gt;
&lt;p&gt;Significantly elevated maximum relative cerebral blood volume, fractional anisotropy, linear anisotropy coefficient, and planar anisotropy coefficient and decreased spheric anisotropy coefficient were observed in true progression compared with pseudoprogression (&lt;i&gt;P&lt;/i&gt; &amp;lt; .05). There were also significant differences in maximum relative cerebral blood volume, fractional anisotropy, planar anisotropy coefficient, and spheric anisotropy coefficient measurements between mixed response and true progression groups. The best model to distinguish true progression from non–true progression (pseudoprogression and mixed) consisted of fractional anisotropy, linear anisotropy coefficient, and maximum relative cerebral blood volume, resulting in an area under the curve of 0.905. This model also differentiated true progression from mixed response with an area under the curve of 0.901. A combination of fractional anisotropy and maximum relative cerebral blood volume differentiated pseudoprogression from nonpseudoprogression (true progression and mixed) with an area under the curve of 0.807.&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;DTI and DSC perfusion imaging can improve accuracy in assessing treatment response and may aid in individualized treatment of patients with glioblastomas.&lt;/p&gt;" />
<meta name="citation_journal_title" content="American Journal of Neuroradiology" />
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<meta name="twitter:title" content="Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using Diffusion Tensor Imaging and Dynamic Susceptibility Contrast MRI" />
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<meta name="twitter:description" content="BACKGROUND AND PURPOSE: Early assessment of treatment response is critical in patients with glioblastomas. A combination of DTI and DSC perfusion imaging parameters was evaluated to distinguish glioblastomas with true progression from mixed response and pseudoprogression.

MATERIALS AND METHODS: Forty-one patients with glioblastomas exhibiting enhancing lesions within 6 months after completion of chemoradiation therapy were retrospectively studied. All patients underwent surgery after MR imaging and were histologically classified as having true progression (&gt;75% tumor), mixed response (25%–75% tumor), or pseudoprogression (&lt;25% tumor). Mean diffusivity, fractional anisotropy, linear anisotropy coefficient, planar anisotropy coefficient, spheric anisotropy coefficient, and maximum relative cerebral blood volume values were measured from the enhancing tissue. A multivariate logistic regression analysis was used to determine the best model for classification of true progression from mixed response or pseudoprogression.

RESULTS: Significantly elevated maximum relative cerebral blood volume, fractional anisotropy, linear anisotropy coefficient, and planar anisotropy coefficient and decreased spheric anisotropy coefficient were observed in true progression compared with pseudoprogression ( P &lt; .05). There were also significant differences in maximum relative cerebral blood volume, fractional anisotropy, planar anisotropy coefficient, and spheric anisotropy coefficient measurements between mixed response and true progression groups. The best model to distinguish true progression from non–true progression (pseudoprogression and mixed) consisted of fractional anisotropy, linear anisotropy coefficient, and maximum relative cerebral blood volume, resulting in an area under the curve of 0.905. This model also differentiated true progression from mixed response with an area under the curve of 0.901. A combination of fractional anisotropy and maximum relative cerebral blood volume differentiated pseudoprogression from nonpseudoprogression (true progression and mixed) with an area under the curve of 0.807.

CONCLUSIONS: DTI and DSC perfusion imaging can improve accuracy in assessing treatment response and may aid in individualized treatment of patients with glioblastomas.

AUC
:   area under the curve
CL
:   linear anisotropy coefficient
CP
:   planar anisotropy coefficient
CS
:   spheric anisotropy coefficient
FA
:   fractional anisotropy
LRM
:   logistic regression model
max
:   maximum
MD
:   mean diffusivity
PsP
:   pseudoprogression
rCBV
:   relative cerebral blood volume
TP
:   true progression" />
<meta name="og-title" property="og:title" content="Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using Diffusion Tensor Imaging and Dynamic Susceptibility Contrast MRI" />
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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: Early assessment of treatment response is critical in patients with glioblastomas. A combination of DTI and DSC perfusion imaging parameters was evaluated to distinguish glioblastomas with true progression from mixed response and pseudoprogression.

MATERIALS AND METHODS: Forty-one patients with glioblastomas exhibiting enhancing lesions within 6 months after completion of chemoradiation therapy were retrospectively studied. All patients underwent surgery after MR imaging and were histologically classified as having true progression (&gt;75% tumor), mixed response (25%–75% tumor), or pseudoprogression (&lt;25% tumor). Mean diffusivity, fractional anisotropy, linear anisotropy coefficient, planar anisotropy coefficient, spheric anisotropy coefficient, and maximum relative cerebral blood volume values were measured from the enhancing tissue. A multivariate logistic regression analysis was used to determine the best model for classification of true progression from mixed response or pseudoprogression.

RESULTS: Significantly elevated maximum relative cerebral blood volume, fractional anisotropy, linear anisotropy coefficient, and planar anisotropy coefficient and decreased spheric anisotropy coefficient were observed in true progression compared with pseudoprogression ( P &lt; .05). There were also significant differences in maximum relative cerebral blood volume, fractional anisotropy, planar anisotropy coefficient, and spheric anisotropy coefficient measurements between mixed response and true progression groups. The best model to distinguish true progression from non–true progression (pseudoprogression and mixed) consisted of fractional anisotropy, linear anisotropy coefficient, and maximum relative cerebral blood volume, resulting in an area under the curve of 0.905. This model also differentiated true progression from mixed response with an area under the curve of 0.901. A combination of fractional anisotropy and maximum relative cerebral blood volume differentiated pseudoprogression from nonpseudoprogression (true progression and mixed) with an area under the curve of 0.807.

CONCLUSIONS: DTI and DSC perfusion imaging can improve accuracy in assessing treatment response and may aid in individualized treatment of patients with glioblastomas.

AUC
:   area under the curve
CL
:   linear anisotropy coefficient
CP
:   planar anisotropy coefficient
CS
:   spheric anisotropy coefficient
FA
:   fractional anisotropy
LRM
:   logistic regression model
max
:   maximum
MD
:   mean diffusivity
PsP
:   pseudoprogression
rCBV
:   relative cerebral blood volume
TP
:   true progression" />
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    <div class="highwire-article-citation highwire-citation-type-highwire-article node14211--5" data-node-nid="14211" id="top-node-14211--61907654728" data-pisa="ajnr;37/1/28" data-pisa-master="ajnr;ajnr.A4474" data-apath="/ajnr/37/1/28.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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    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">S. Wang</span>, <span class="highwire-citation-author" data-delta="1">M. Martinez-Lage</span>, <span class="highwire-citation-author" data-delta="2">Y. Sakai</span>, <span class="highwire-citation-author" data-delta="3">S. Chawla</span>, <span class="highwire-citation-author" data-delta="4">S.G. Kim</span>, <span class="highwire-citation-author" data-delta="5">M. Alonso-Basanta</span>, <span class="highwire-citation-author" data-delta="6">R.A. Lustig</span>, <span class="highwire-citation-author" data-delta="7">S. Brem</span>, <span class="highwire-citation-author" data-delta="8">S. Mohan</span>, <span class="highwire-citation-author" data-delta="9">R.L. Wolf</span>, <span class="highwire-citation-author" data-delta="10">A. Desai</span> and <span class="highwire-citation-author" data-delta="11">H. Poptani</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">January 2016,  </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">37 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(1) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">28-36; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A4474 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-14211--61907654728" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">S. Wang </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Departments of Radiology (S.W., Y.S., S.M., R.L.W., H.P.)</div></span></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.%2BWang%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=Wang%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.%2BWang%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">M. Martinez-Lage </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Division of Neuroradiology, Pathology and Laboratory Medicine (M.M.-L.)</div></span></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=M.%2BMartinez-Lage%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=Martinez-Lage%20M&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%3AM.%2BMartinez-Lage%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-2"><div class="author-tooltip-name">Y. Sakai </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Departments of Radiology (S.W., Y.S., S.M., R.L.W., H.P.)</div></span></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=Y.%2BSakai%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=Sakai%20Y&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%3AY.%2BSakai%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-3"><div class="author-tooltip-name">S. Chawla </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>f</span>Department of Radiology (S.C., S.G.K.), Center for Biomedical Imaging, New York University School of Medicine, New York, New York.</div></span></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.%2BChawla%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=Chawla%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.%2BChawla%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-4"><div class="author-tooltip-name">S.G. Kim </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>f</span>Department of Radiology (S.C., S.G.K.), Center for Biomedical Imaging, New York University School of Medicine, New York, New York.</div></span></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.G.%2BKim%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=Kim%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.G.%2BKim%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-5"><div class="author-tooltip-name">M. 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Lustig </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>c</span>Radiation Oncology (M.A.-B., R.A.L.,)</div></span></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=R.A.%2BLustig%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=Lustig%20R&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%3AR.A.%2BLustig%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-7"><div class="author-tooltip-name">S. Brem </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>d</span>Neurosurgery (S.B.)</div></span></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.%2BBrem%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=Brem%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.%2BBrem%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-8"><div class="author-tooltip-name">S. Mohan </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Departments of Radiology (S.W., Y.S., S.M., R.L.W., H.P.)</div></span></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.%2BMohan%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=Mohan%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.%2BMohan%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-9"><div class="author-tooltip-name">R.L. Wolf </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Departments of Radiology (S.W., Y.S., S.M., R.L.W., H.P.)</div></span></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=R.L.%2BWolf%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=Wolf%20R&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%3AR.L.%2BWolf%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-10"><div class="author-tooltip-name">A. Desai </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>e</span>Hematology-Oncology (A.D.), Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania</div></span></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=A.%2BDesai%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=Desai%20A&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%3AA.%2BDesai%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-11"><div class="author-tooltip-name">H. Poptani </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Departments of Radiology (S.W., Y.S., S.M., R.L.W., H.P.)</div></span></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=H.%2BPoptani%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=Poptani%20H&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%3AH.%2BPoptani%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div></div></div>  </div>

  
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    <div class="highwire-markup"><div xmlns="http://www.w3.org/1999/xhtml" xmlns:xhtml="http://www.w3.org/1999/xhtml" class="section ref-list" id="ref-list-1"><h2 class="">References</h2><ol class="cit-list ref-use-labels"><li><span class="ref-label">1.</span><a class="rev-xref-ref" href="#xref-ref-1-1" title="View reference 1. in text" id="ref-1">↵</a><div class="cit ref-cit ref-journal" id="cit-37.1.28.1"><div class="cit-metadata"><ol class="cit-auth-list"><li>
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</li><li><span class="cit-auth"><span class="cit-name-surname">Cha</span>  <span class="cit-name-given-names">J</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Kim</span>  <span class="cit-name-given-names">ST</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Kim</span>  <span class="cit-name-given-names">HJ</span></span>, <span class="cit-etal">et al</span></li></ol><cite>. <span class="cit-article-title">Differentiation of tumor progression from pseudoprogression in patients with posttreatment glioblastoma using multiparametric histogram analysis</span>. <abbr class="cit-jnl-abbrev">AJNR Am J Neuroradiol</abbr> <span class="cit-pub-date">2014</span>;<span class="cit-vol">35</span>:<span class="cit-fpage">1309</span>–<span class="cit-lpage">17</span><span class="cit-pub-id-sep cit-pub-id-doi-sep"> </span><span class="cit-pub-id cit-pub-id-doi"><span class="cit-pub-id-scheme-doi">doi:</span>10.3174/ajnr.A3876</span><span class="cit-pub-id-sep cit-pub-id-pmid-sep"> </span><span class="cit-pub-id cit-pub-id-pmid"><span class="cit-pub-id-scheme-pmid">pmid:</span>24676005</span></cite></div><div class="cit-extra"><a href="/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NDoiYWpuciI7czo1OiJyZXNpZCI7czo5OiIzNS83LzEzMDkiO3M6NDoiYXRvbSI7czoxODoiL2FqbnIvMzcvMS8yOC5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30=" class="cit-ref-sprinkles cit-ref-sprinkles-ijlink"><span><span class="cit-reflinks-abstract">Abstract</span><span class="cit-sep cit-reflinks-variant-name-sep">/</span><span class="cit-reflinks-full-text"><span class="free-full-text">FREE </span>Full Text</span></span></a></div></div></li><li><span class="ref-label">5.</span><a class="rev-xref-ref" href="#xref-ref-5-1" title="View reference 5. in text" id="ref-5">↵</a><div class="cit ref-cit ref-journal" id="cit-37.1.28.5" data-doi="10.1148/radiol.13122024"><div class="cit-metadata"><ol class="cit-auth-list"><li>
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</li><li><span class="cit-auth"><span class="cit-name-surname">Jahangiri</span>  <span class="cit-name-given-names">A</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Aghi</span>  <span class="cit-name-given-names">MK</span></span></li></ol><cite>. <span class="cit-article-title">Pseudoprogression and treatment effect</span>. <abbr class="cit-jnl-abbrev">Neurosurg Clin N Am</abbr> <span class="cit-pub-date">2012</span>;<span class="cit-vol">23</span>:<span class="cit-fpage">277</span>–<span class="cit-lpage">87</span>, <span class="cit-fpage">viii</span>–<span class="cit-lpage">ix</span><span class="cit-pub-id-sep cit-pub-id-doi-sep"> </span><span class="cit-pub-id cit-pub-id-doi"><span class="cit-pub-id-scheme-doi">doi:</span>10.1016/j.nec.2012.01.002</span><span class="cit-pub-id-sep cit-pub-id-pmid-sep"> </span><span class="cit-pub-id cit-pub-id-pmid"><span class="cit-pub-id-scheme-pmid">pmid:</span>22440871</span></cite></div><div class="cit-extra"><a href="/lookup/external-ref?access_num=10.1016/j.nec.2012.01.002&amp;link_type=DOI" class="cit-ref-sprinkles cit-ref-sprinkles-doi cit-ref-sprinkles-crossref"><span>CrossRef</span></a><a href="/lookup/external-ref?access_num=22440871&amp;link_type=MED&amp;atom=%2Fajnr%2F37%2F1%2F28.atom" class="cit-ref-sprinkles cit-ref-sprinkles-medline"><span>PubMed</span></a></div></div></li><li><span class="ref-label">33.</span><a class="rev-xref-ref" href="#xref-ref-33-1" title="View reference 33. in text" id="ref-33">↵</a><div class="cit ref-cit ref-journal" id="cit-37.1.28.33" data-doi="10.1371/journal.pone.0090535"><div class="cit-metadata"><ol class="cit-auth-list"><li>
</li><li><span class="cit-auth"><span class="cit-name-surname">Aquino</span>  <span class="cit-name-given-names">D</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Di Stefano</span>  <span class="cit-name-given-names">AL</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Scotti</span>  <span class="cit-name-given-names">A</span></span>, <span class="cit-etal">et al</span></li></ol><cite>. <span class="cit-article-title">Parametric response maps of perfusion MRI may identify recurrent glioblastomas responsive to bevacizumab and irinotecan</span>. <abbr class="cit-jnl-abbrev">PLoS One</abbr> <span class="cit-pub-date">2014</span>;<span class="cit-vol">9</span>:<span class="cit-fpage">e90535</span><span class="cit-pub-id-sep cit-pub-id-doi-sep"> </span><span class="cit-pub-id cit-pub-id-doi"><span class="cit-pub-id-scheme-doi">doi:</span>10.1371/journal.pone.0090535</span><span class="cit-pub-id-sep cit-pub-id-pmid-sep"> </span><span class="cit-pub-id cit-pub-id-pmid"><span class="cit-pub-id-scheme-pmid">pmid:</span>24675671</span></cite></div><div class="cit-extra"><a href="/lookup/external-ref?access_num=10.1371/journal.pone.0090535&amp;link_type=DOI" class="cit-ref-sprinkles cit-ref-sprinkles-doi cit-ref-sprinkles-crossref"><span>CrossRef</span></a><a href="/lookup/external-ref?access_num=24675671&amp;link_type=MED&amp;atom=%2Fajnr%2F37%2F1%2F28.atom" class="cit-ref-sprinkles cit-ref-sprinkles-medline"><span>PubMed</span></a></div></div></li></ol></div></div>  </div>

  
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        	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-volume highwire-cite-metadata">Vol. 37</span>, <span  class="highwire-cite-metadata-issue highwire-cite-metadata">Issue 1 </span><div  class="highwire-cite-metadata-pubdate highwire-cite-metadata">1 Jan 2016 </div></div>
      
      
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    	<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.</span> <span class="nlm-surname">Wang</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">M.</span> <span class="nlm-surname">Martinez-Lage</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">Y.</span> <span class="nlm-surname">Sakai</span></span>, <span class="highwire-citation-author" data-delta="3"><span class="nlm-given-names">S.</span> <span class="nlm-surname">Chawla</span></span>, <span class="highwire-citation-author" data-delta="4"><span class="nlm-given-names">S.G.</span> <span class="nlm-surname">Kim</span></span>, <span class="highwire-citation-author" data-delta="5"><span class="nlm-given-names">M.</span> <span class="nlm-surname">Alonso-Basanta</span></span>, <span class="highwire-citation-author" data-delta="6"><span class="nlm-given-names">R.A.</span> <span class="nlm-surname">Lustig</span></span>, <span class="highwire-citation-author" data-delta="7"><span class="nlm-given-names">S.</span> <span class="nlm-surname">Brem</span></span>, <span class="highwire-citation-author" data-delta="8"><span class="nlm-given-names">S.</span> <span class="nlm-surname">Mohan</span></span>, <span class="highwire-citation-author" data-delta="9"><span class="nlm-given-names">R.L.</span> <span class="nlm-surname">Wolf</span></span>, <span class="highwire-citation-author" data-delta="10"><span class="nlm-given-names">A.</span> <span class="nlm-surname">Desai</span></span>, <span class="highwire-citation-author" data-delta="11"><span class="nlm-given-names">H.</span> <span class="nlm-surname">Poptani</span></span></span></div>
  
    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-oa-ind highwire-cite-metadata"><i class="highwire-oa-indicator"></i> </span><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">Jan 2016, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">37 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(1) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">28-36; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A4474 </span></div>
  
  
  
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      <div class="highwire-cite-title">Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using Diffusion Tensor Imaging and Dynamic Susceptibility Contrast MRI</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.</span> <span class="nlm-surname">Wang</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">M.</span> <span class="nlm-surname">Martinez-Lage</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">Y.</span> <span class="nlm-surname">Sakai</span></span>, <span class="highwire-citation-author" data-delta="3"><span class="nlm-given-names">S.</span> <span class="nlm-surname">Chawla</span></span>, <span class="highwire-citation-author" data-delta="4"><span class="nlm-given-names">S.G.</span> <span class="nlm-surname">Kim</span></span>, <span class="highwire-citation-author" data-delta="5"><span class="nlm-given-names">M.</span> <span class="nlm-surname">Alonso-Basanta</span></span>, <span class="highwire-citation-author" data-delta="6"><span class="nlm-given-names">R.A.</span> <span class="nlm-surname">Lustig</span></span>, <span class="highwire-citation-author" data-delta="7"><span class="nlm-given-names">S.</span> <span class="nlm-surname">Brem</span></span>, <span class="highwire-citation-author" data-delta="8"><span class="nlm-given-names">S.</span> <span class="nlm-surname">Mohan</span></span>, <span class="highwire-citation-author" data-delta="9"><span class="nlm-given-names">R.L.</span> <span class="nlm-surname">Wolf</span></span>, <span class="highwire-citation-author" data-delta="10"><span class="nlm-given-names">A.</span> <span class="nlm-surname">Desai</span></span>, <span class="highwire-citation-author" data-delta="11"><span class="nlm-given-names">H.</span> <span class="nlm-surname">Poptani</span></span></span></div>
  
    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-oa-ind highwire-cite-metadata"><i class="highwire-oa-indicator"></i> </span><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">Jan 2016, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">37 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(1) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">28-36; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A4474 </span></div>
  
  
  
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