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Dynamic contrast-enhanced MRI may be helpful to predict response and prognosis after bevacizumab treatment in patients with recurrent high-grade glioma: comparison with diffusion tensor and dynamic susceptibility contrast imaging

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dc.contributor.author강석구-
dc.contributor.author김세훈-
dc.contributor.author김의현-
dc.contributor.author문주형-
dc.contributor.author박예원-
dc.contributor.author안성수-
dc.contributor.author이승구-
dc.contributor.author장종희-
dc.date.accessioned2021-12-28T17:33:25Z-
dc.date.available2021-12-28T17:33:25Z-
dc.date.issued2021-11-
dc.identifier.issn0028-3940-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/187158-
dc.description.abstractPurpose: We aimed to evaluate the utility of diffusion tensor imaging (DTI), dynamic contrast-enhanced (DCE), and dynamic susceptibility contrast (DSC) imaging for stratifying bevacizumab treatment outcomes in patients with recurrent high-grade glioma. Methods: Fifty-three patients with recurrent high-grade glioma who underwent baseline magnetic resonance imaging including DTI, DCE, and DSC before bevacizumab treatment were included. The mean apparent diffusion coefficient, fractional anisotropy, normalized cerebral blood volume, normalized cerebral blood flow, volume transfer constant, rate transfer coefficient (Kep), extravascular extracellular volume fraction, and plasma volume fraction were assessed. Predictors of response status, progression-free survival (PFS), and overall survival (OS) were determined using logistic regression and Cox proportional hazard modeling. Results: Responders (n = 16) showed significantly longer PFS and OS (P < 0.001) compared with nonresponders (n = 37). Multivariable analysis revealed that lower mean Kep (odds ratio = 0.01, P = 0.008) was the only independent predictor of favorable response after adjustment for age, isocitrate dehydrogenase (IDH) mutation status, and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. Multivariable Cox proportional hazard modeling showed that a higher mean Kep was the only variable associated with shorter PFS (hazard ratio [HR] = 7.90, P = 0.006) and OS (HR = 9.71, P = 0.020) after adjustment for age, IDH mutation status, and MGMT promoter methylation status. Conclusion: Baseline mean Kep may be a useful biomarker for predicting response and stratifying patient outcomes following bevacizumab treatment in patients with recurrent high-grade glioma.-
dc.description.statementOfResponsibilityrestriction-
dc.languageEnglish-
dc.publisherSpringer-Verlag-
dc.relation.isPartOfNEURORADIOLOGY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHBevacizumab / therapeutic use-
dc.subject.MESHBrain Neoplasms* / diagnostic imaging-
dc.subject.MESHBrain Neoplasms* / drug therapy-
dc.subject.MESHContrast Media-
dc.subject.MESHDiffusion Tensor Imaging-
dc.subject.MESHGlioma* / diagnostic imaging-
dc.subject.MESHGlioma* / drug therapy-
dc.subject.MESHHumans-
dc.subject.MESHMagnetic Resonance Imaging-
dc.subject.MESHNeoplasm Recurrence, Local / diagnostic imaging-
dc.subject.MESHNeoplasm Recurrence, Local / drug therapy-
dc.subject.MESHPrognosis-
dc.titleDynamic contrast-enhanced MRI may be helpful to predict response and prognosis after bevacizumab treatment in patients with recurrent high-grade glioma: comparison with diffusion tensor and dynamic susceptibility contrast imaging-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Neurosurgery (신경외과학교실)-
dc.contributor.googleauthorYae Won Park-
dc.contributor.googleauthorSung Soo Ahn-
dc.contributor.googleauthorJu Hyung Moon-
dc.contributor.googleauthorEui Hyun Kim-
dc.contributor.googleauthorSeok-Gu Kang-
dc.contributor.googleauthorJong Hee Chang-
dc.contributor.googleauthorSe Hoon Kim-
dc.contributor.googleauthorSeung-Koo Lee-
dc.identifier.doi10.1007/s00234-021-02693-z-
dc.contributor.localIdA00036-
dc.contributor.localIdA00610-
dc.contributor.localIdA00837-
dc.contributor.localIdA01383-
dc.contributor.localIdA05330-
dc.contributor.localIdA02234-
dc.contributor.localIdA02912-
dc.contributor.localIdA03470-
dc.relation.journalcodeJ02358-
dc.identifier.eissn1432-1920-
dc.identifier.pmid33755766-
dc.identifier.urlhttps://link.springer.com/article/10.1007%2Fs00234-021-02693-z-
dc.subject.keywordBevacizumab-
dc.subject.keywordDiffusion tensor imaging-
dc.subject.keywordGlioma-
dc.subject.keywordMagnetic resonance imaging-
dc.contributor.alternativeNameKang, Seok Gu-
dc.contributor.affiliatedAuthor강석구-
dc.contributor.affiliatedAuthor김세훈-
dc.contributor.affiliatedAuthor김의현-
dc.contributor.affiliatedAuthor문주형-
dc.contributor.affiliatedAuthor박예원-
dc.contributor.affiliatedAuthor안성수-
dc.contributor.affiliatedAuthor이승구-
dc.contributor.affiliatedAuthor장종희-
dc.citation.volume63-
dc.citation.number11-
dc.citation.startPage1811-
dc.citation.endPage1822-
dc.identifier.bibliographicCitationNEURORADIOLOGY, Vol.63(11) : 1811-1822, 2021-11-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Neurosurgery (신경외과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Pathology (병리학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers

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