Literature DB >> 17886561

Prediction of oligodendroglial tumor subtype and grade using perfusion weighted magnetic resonance imaging.

Robert G Whitmore1, Jaroslaw Krejza, Gurpreet S Kapoor, Jason Huse, John H Woo, Stephanie Bloom, Joanna Lopinto, Ronald L Wolf, Kevin Judy, Myrna R Rosenfeld, Jaclyn A Biegel, Elias R Melhem, Donald M O'Rourke.   

Abstract

OBJECT: Treatment of patients with oligodendrogliomas relies on histopathological grade and characteristic cytogenetic deletions of 1p and 19q, shown to predict radio- and chemosensitivity and prolonged survival. Perfusion weighted magnetic resonance (MR) imaging allows for noninvasive determination of relative tumor blood volume (rTBV) and has been used to predict the grade of astrocytic neoplasms. The aim of this study was to use perfusion weighted MR imaging to predict tumor grade and cytogenetic profile in oligodendroglial neoplasms.
METHODS: Thirty patients with oligodendroglial neoplasms who underwent preoperative perfusion MR imaging were retrospectively identified. Tumors were classified by histopathological grade and stratified into two cytogenetic groups: 1p or 1p and 19q loss of heterozygosity (LOH) (Group 1), and 19q LOH only on intact alleles (Group 2). Tumor blood volume was calculated in relation to contralateral white matter. Multivariate logistic regression analysis was used to develop predictive models of cytogenetic profile and tumor grade.
RESULTS: In World Health Organization Grade II neoplasms, the rTBV was significantly greater (p < 0.05) in Group 1 (mean 2.44, range 0.96-3.28; seven patients) compared with Group 2 (mean 1.69, range 1.27-2.08; seven patients). In Grade III neoplasms, the differences between Group 1 (mean 3.38, range 1.59-6.26; four patients) and Group 2 (mean 2.83, range 1.81-3.76; 12 patients) were not significant. The rTBV was significantly greater (p < 0.05) in Grade III neoplasms (mean 2.97, range 1.59-6.26; 16 patients) compared with Grade II neoplasms (mean 2.07, range 0.96-3.28; 14 patients). The models integrating rTBV with cytogenetic profile and grade showed prediction accuracies of 68 and 73%, respectively.
CONCLUSIONS: Oligodendroglial classification models derived from advanced imaging will improve the accuracy of tumor grading, provide prognostic information, and have potential to influence treatment decisions.

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Year:  2007        PMID: 17886561     DOI: 10.3171/JNS-07/09/0600

Source DB:  PubMed          Journal:  J Neurosurg        ISSN: 0022-3085            Impact factor:   5.115


  35 in total

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2.  Effect of Perfusion on Diffusion Kurtosis Imaging Estimates for In Vivo Assessment of Integrated 2016 WHO Glioma Grades : A Cross-Sectional Observational Study.

Authors:  Johann-Martin Hempel; Jens Schittenhelm; Cornelia Brendle; Benjamin Bender; Georg Bier; Marco Skardelly; Ghazaleh Tabatabai; Salvador Castaneda Vega; Ulrike Ernemann; Uwe Klose
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Review 3.  Radiogenomics and imaging phenotypes in glioblastoma: novel observations and correlation with molecular characteristics.

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4.  Combined diffusion and perfusion MR imaging as biomarkers of prognosis in immunocompetent patients with primary central nervous system lymphoma.

Authors:  F E Valles; C L Perez-Valles; S Regalado; R F Barajas; J L Rubenstein; S Cha
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5.  Dynamic susceptibility contrast and diffusion MR imaging identify oligodendroglioma as defined by the 2016 WHO classification for brain tumors: histogram analysis approach.

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6.  Imaging characteristics of oligodendrogliomas that predict grade.

Authors:  L Khalid; M Carone; N Dumrongpisutikul; J Intrapiromkul; D Bonekamp; P B Barker; D M Yousem
Journal:  AJNR Am J Neuroradiol       Date:  2012-01-19       Impact factor: 3.825

7.  3D Pseudocontinuous Arterial Spin-Labeling MR Imaging in the Preoperative Evaluation of Gliomas.

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8.  Multimodal MR imaging (diffusion, perfusion, and spectroscopy): is it possible to distinguish oligodendroglial tumor grade and 1p/19q codeletion in the pretherapeutic diagnosis?

Authors:  S Fellah; D Caudal; A M De Paula; P Dory-Lautrec; D Figarella-Branger; O Chinot; P Metellus; P J Cozzone; S Confort-Gouny; B Ghattas; V Callot; N Girard
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9.  Multiparametric characterization of grade 2 glioma subtypes using magnetic resonance spectroscopic, perfusion, and diffusion imaging.

Authors:  Wei Bian; Inas S Khayal; Janine M Lupo; Colleen McGue; Scott Vandenberg; Kathleen R Lamborn; Susan M Chang; Soonmee Cha; Sarah J Nelson
Journal:  Transl Oncol       Date:  2009-12       Impact factor: 4.243

10.  Perfusion weighted magnetic resonance imaging to distinguish the recurrence of metastatic brain tumors from radiation necrosis after stereotactic radiosurgery.

Authors:  Koichi Mitsuya; Yoko Nakasu; Satoshi Horiguchi; Hideyuki Harada; Tetsuo Nishimura; Etsuro Bando; Hiroto Okawa; Yoshihiro Furukawa; Tatsuo Hirai; Masahiro Endo
Journal:  J Neurooncol       Date:  2010-01-08       Impact factor: 4.130

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