Literature DB >> 16951209

The extent and severity of vascular leakage as evidence of tumor aggressiveness in high-grade gliomas.

Yue Cao1, Vijaya Nagesh, Daniel Hamstra, Christina I Tsien, Brian D Ross, Thomas L Chenevert, Larry Junck, Theodore S Lawrence.   

Abstract

Magnetic resonance imaging reveals heterogeneous regions within high-grade gliomas, such as a contrast-enhanced rim, a necrotic core, and non-contrast-enhanced abnormalities. It is unclear which of these regions best describes tumor aggressiveness. We hypothesized that the vascular leakage volume, reflecting disorganized angiogenesis typical of glioblastoma, would be a strong predictor of clinical outcome. The FLAIR tumor volume, post-gadolinium T1 tumor volume, tumor vascular leakage volume determined by dynamic contrast-enhanced imaging, and volume of the contrast-enhanced rim seen on post-gadolinium T1-weighted images were defined for 20 patients about to undergo treatment for newly diagnosed high-grade gliomas. The potential for imaging characteristics to improve prediction of survival and time to progression over clinical variables was tested by using Cox regression analysis. Single-variable Cox regression analysis of each of the four tumor subvolumes revealed that the vascular leakage volume was the only significant predictor of survival. When the joint effect of clinical variables and the vascular leakage volume were tested for prediction of survival, only the age and the vascular leakage volume were selected as significant predictors. However, when time to progression was tested as a dependent variable, both the vascular leakage volume and the vascular permeability were selected as copredictors, along with surgical status. Our findings suggest that for patients with high-grade glioma, time to progression after radiation therapy is influenced by both underlying biological aggressiveness (vascularity) and volume of aggressive tumor. In contrast, survival depends chiefly on the volume of aggressive tumor at the time of presentation.

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Year:  2006        PMID: 16951209     DOI: 10.1158/0008-5472.CAN-05-4328

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  30 in total

1.  In vivo correlation of tumor blood volume and permeability with histologic and molecular angiogenic markers in gliomas.

Authors:  R Jain; J Gutierrez; J Narang; L Scarpace; L R Schultz; N Lemke; S C Patel; T Mikkelsen; J P Rock
Journal:  AJNR Am J Neuroradiol       Date:  2010-11-11       Impact factor: 3.825

2.  ¹⁸F-Fluoromisonidazole positron emission tomography may differentiate glioblastoma multiforme from less malignant gliomas.

Authors:  Kenji Hirata; Shunsuke Terasaka; Tohru Shiga; Naoya Hattori; Keiichi Magota; Hiroyuki Kobayashi; Shigeru Yamaguchi; Kiyohiro Houkin; Shinya Tanaka; Yuji Kuge; Nagara Tamaki
Journal:  Eur J Nucl Med Mol Imaging       Date:  2012-02-04       Impact factor: 9.236

3.  Prognosis prediction of non-enhancing T2 high signal intensity lesions in glioblastoma patients after standard treatment: application of dynamic contrast-enhanced MR imaging.

Authors:  Rihyeon Kim; Seung Hong Choi; Tae Jin Yun; Soon-Tae Lee; Chul-Kee Park; Tae Min Kim; Ji-Hoon Kim; Sun-Won Park; Chul-Ho Sohn; Sung-Hye Park; Il Han Kim
Journal:  Eur Radiol       Date:  2016-06-29       Impact factor: 5.315

4.  Tumor image signatures and habitats: a processing pipeline of multimodality metabolic and physiological images.

Authors:  Daekeun You; Michelle M Kim; Madhava P Aryal; Hemant Parmar; Morand Piert; Theodore S Lawrence; Yue Cao
Journal:  J Med Imaging (Bellingham)       Date:  2017-11-15

Review 5.  The promise of dynamic contrast-enhanced imaging in radiation therapy.

Authors:  Yue Cao
Journal:  Semin Radiat Oncol       Date:  2011-04       Impact factor: 5.934

Review 6.  MR-guided radiation therapy: transformative technology and its role in the central nervous system.

Authors:  Yue Cao; Chia-Lin Tseng; James M Balter; Feifei Teng; Hemant A Parmar; Arjun Sahgal
Journal:  Neuro Oncol       Date:  2017-04-01       Impact factor: 12.300

7.  Breast cancer redox heterogeneity detectable with chemical exchange saturation transfer (CEST) MRI.

Authors:  Kejia Cai; He N Xu; Anup Singh; Lily Moon; Mohammad Haris; Ravinder Reddy; Lin Z Li
Journal:  Mol Imaging Biol       Date:  2014-10       Impact factor: 3.488

8.  Physiological imaging-defined, response-driven subvolumes of a tumor.

Authors:  Reza Farjam; Christina I Tsien; Felix Y Feng; Diana Gomez-Hassan; James A Hayman; Theodore S Lawrence; Yue Cao
Journal:  Int J Radiat Oncol Biol Phys       Date:  2012-12-17       Impact factor: 7.038

9.  Complementary but distinct roles for MRI and 18F-fluoromisonidazole PET in the assessment of human glioblastomas.

Authors:  Kristin R Swanson; Gargi Chakraborty; Christina H Wang; Russell Rockne; Hana L P Harpold; Mark Muzi; Tom C H Adamsen; Kenneth A Krohn; Alexander M Spence
Journal:  J Nucl Med       Date:  2008-12-17       Impact factor: 10.057

10.  MRI-based characterization of vascular disruption by 5,6-dimethylxanthenone-acetic acid in gliomas.

Authors:  Mukund Seshadri; Michael J Ciesielski
Journal:  J Cereb Blood Flow Metab       Date:  2009-05-20       Impact factor: 6.200

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