Literature DB >> 24293201

Effect of contrast leakage on the detection of abnormal brain tumor vasculature in high-grade glioma.

Peter S LaViolette1, Mitchell K Daun1, Eric S Paulson2, Kathleen M Schmainda3.   

Abstract

Abnormal brain tumor vasculature has recently been highlighted by a dynamic susceptibility contrast (DSC) MRI processing technique. The technique uses independent component analysis (ICA) to separate arterial and venous perfusion. The overlap of the two, i.e. arterio-venous overlap or AVOL, preferentially occurs in brain tumors and predicts response to anti-angiogenic therapy. The effects of contrast agent leakage on the AVOL biomarker have yet to be established. DSC was acquired during two separate contrast boluses in ten patients undergoing clinical imaging for brain tumor diagnosis. Three components were modeled with ICA, which included the arterial and venous components. The percentage of each component as well as a third component were determined within contrast enhancing tumor and compared. AVOL within enhancing tumor was also compared between doses. The percentage of enhancing tumor classified as not arterial or venous and instead into a third component with contrast agent leakage apparent in the time-series was significantly greater for the first contrast dose compared to the second. The amount of AVOL detected within enhancing tumor was also significantly greater with the second dose compared to the first. Contrast leakage results in large signal variance classified as a separate component by the ICA algorithm. The use of a second dose mitigates the effect and allows measurement of AVOL within enhancement.

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Year:  2013        PMID: 24293201      PMCID: PMC4316680          DOI: 10.1007/s11060-013-1318-9

Source DB:  PubMed          Journal:  J Neurooncol        ISSN: 0167-594X            Impact factor:   4.130


  32 in total

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2.  Relative cerebral blood volume values to differentiate high-grade glioma recurrence from posttreatment radiation effect: direct correlation between image-guided tissue histopathology and localized dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging measurements.

Authors:  L S Hu; L C Baxter; K A Smith; B G Feuerstein; J P Karis; J M Eschbacher; S W Coons; P Nakaji; R F Yeh; J Debbins; J E Heiserman
Journal:  AJNR Am J Neuroradiol       Date:  2008-12-04       Impact factor: 3.825

3.  Analysis of fMRI data by blind separation into independent spatial components.

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Journal:  Hum Brain Mapp       Date:  1998       Impact factor: 5.038

4.  Comparison of first-pass and second-bolus dynamic susceptibility perfusion MRI in brain tumors.

Authors:  M Vittoria Spampinato; Caroline Wooten; Margaret Dorlon; Nada Besenski; Zoran Rumboldt
Journal:  Neuroradiology       Date:  2006-09-30       Impact factor: 2.804

5.  Potential for differentiation of pseudoprogression from true tumor progression with dynamic susceptibility-weighted contrast-enhanced magnetic resonance imaging using ferumoxytol vs. gadoteridol: a pilot study.

Authors:  Seymur Gahramanov; Ahmed M Raslan; Leslie L Muldoon; Bronwyn E Hamilton; William D Rooney; Csanad G Varallyay; Jeffrey M Njus; Marianne Haluska; Edward A Neuwelt
Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-04-13       Impact factor: 7.038

6.  Correlation between dynamic MRI and outcome in patients with malignant gliomas.

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Journal:  Neurology       Date:  1998-03       Impact factor: 9.910

7.  Correlation of MR imaging-determined cerebral blood volume maps with histologic and angiographic determination of vascularity of gliomas.

Authors:  T Sugahara; Y Korogi; M Kochi; I Ikushima; T Hirai; T Okuda; Y Shigematsu; L Liang; Y Ge; Y Ushio; M Takahashi
Journal:  AJR Am J Roentgenol       Date:  1998-12       Impact factor: 3.959

8.  Optimized preload leakage-correction methods to improve the diagnostic accuracy of dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging in posttreatment gliomas.

Authors:  L S Hu; L C Baxter; D S Pinnaduwage; T L Paine; J P Karis; B G Feuerstein; K M Schmainda; A C Dueck; J Debbins; K A Smith; P Nakaji; J M Eschbacher; S W Coons; J E Heiserman
Journal:  AJNR Am J Neuroradiol       Date:  2009-09-12       Impact factor: 3.825

9.  The vasculature of experimental brain tumours. Part 1. A sequential light and electron microscope study of angiogenesis.

Authors:  B R Deane; P L Lantos
Journal:  J Neurol Sci       Date:  1981-01       Impact factor: 3.181

Review 10.  The 2007 WHO classification of tumours of the central nervous system.

Authors:  David N Louis; Hiroko Ohgaki; Otmar D Wiestler; Webster K Cavenee; Peter C Burger; Anne Jouvet; Bernd W Scheithauer; Paul Kleihues
Journal:  Acta Neuropathol       Date:  2007-07-06       Impact factor: 17.088

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  4 in total

1.  Evaluation of Encephaloduroarteriosynangiosis Efficacy Using Probabilistic Independent Component Analysis Applied to Dynamic Susceptibility Contrast Perfusion MRI.

Authors:  A N Laiwalla; F Kurth; K Leu; R Liou; J Pamplona; Y C Ooi; N Salamon; B M Ellingson; N R Gonzalez
Journal:  AJNR Am J Neuroradiol       Date:  2017-01-19       Impact factor: 3.825

2.  Revealing hemodynamic heterogeneity of gliomas based on signal profile features of dynamic susceptibility contrast-enhanced MRI.

Authors:  Bing Ji; Silun Wang; Zhou Liu; Brent D Weinberg; Xiaofeng Yang; Tianming Liu; Liya Wang; Hui Mao
Journal:  Neuroimage Clin       Date:  2019-05-22       Impact factor: 4.881

3.  Pathological brain detection in MRI scanning by wavelet packet Tsallis entropy and fuzzy support vector machine.

Authors:  Yu-Dong Zhang; Shui-Hua Wang; Xiao-Jun Yang; Zheng-Chao Dong; Ge Liu; Preetha Phillips; Ti-Fei Yuan
Journal:  Springerplus       Date:  2015-11-24

4.  Quantitative measurement of blood flow in paediatric brain tumours-a comparative study of dynamic susceptibility contrast and multi time-point arterial spin labelled MRI.

Authors:  Rishma Vidyasagar; Laurence Abernethy; Barry Pizer; Shivaram Avula; Laura M Parkes
Journal:  Br J Radiol       Date:  2016-03-15       Impact factor: 3.039

  4 in total

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