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Cited 78 time in webofscience Cited 95 time in scopus
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Differentiation of tumor progression from pseudoprogression in patients with posttreatment glioblastoma using multiparametric histogram analysisopen access

Authors
Cha J.Kim S.T.Kim H.-J.Kim B.-J.Kim Y.K.Lee J.Y.Jeon P.Kim K.H.Kong D.-S.Nam D.-H.
Issue Date
Jul-2014
Publisher
American Society of Neuroradiology
Citation
American Journal of Neuroradiology, v.35, no.7, pp 1309 - 1317
Pages
9
Indexed
SCI
SCIE
SCOPUS
Journal Title
American Journal of Neuroradiology
Volume
35
Number
7
Start Page
1309
End Page
1317
URI
https://scholarworks.korea.ac.kr/kumedicine/handle/2020.sw.kumedicine/9977
DOI
10.3174/ajnr.A3876
ISSN
0195-6108
1936-959X
Abstract
BACKGROUND AND PURPOSE: The multiparametric imaging can show us different aspects of tumor behavior and may help differentiation of tumor recurrence from treatment related change. Our aim was to differentiate tumor progression from pseudoprogression in patients with glioblastoma by using multiparametric histogram analysis of 2 consecutive MR imaging studies with relative cerebral blood volume and ADC values. MATERIALS AND METHODS: Thirty-five consecutive patients with glioblastoma with new or increased size of enhancing lesions after concomitant chemoradiation therapy following surgical resection were included. Combined histograms were made by using the relative cerebral blood volume and ADC values of enhancing areas for initial and follow-up MR imaging, and subtracted histograms were also prepared. The histogram parameters between groups were compared. The diagnostic accuracy of tumor progression based on the histogram parameters of initial and follow-up MR imaging and subtracted histograms was compared and correlated with overall survival. RESULTS: Twenty-four pseudoprogressions and 11 tumor progressions were determined. Diagnosis based on the subtracted histogram mode with a multiparametric approach was more accurate than the diagnosis based on the uniparametric approach (area under the receiver operating characteristic curve of 0.877 versus 0.801), with 81.8% sensitivity and 100% specificity. A high mode of relative cerebral blood volume on the subtracted histogram by using a multiparametric approach (relative cerebral blood volume XADC) was the best predictor of true tumor progression (P < .001) and worse survival (P = .003). CONCLUSIONS: Multiparametric histogram analysis of posttreatment glioblastoma was useful to predict true tumor progression and worse survival.
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Anam Hospital (Department of Radiology, Anam Hospital)
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