Effect of contrast leakage on the detection of abnormal brain tumor vasculature in high-grade glioma.
Effect of contrast leakage on the detection of abnormal brain tumor vasculature in high-grade glioma.
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DOI：
10.1007/s11060-013-1318-9
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发表时间：
2014-02
影响因子：
3.9
通讯作者：
Schmainda, Kathleen M.
中科院分区：
文献类型：
--
作者：
LaViolette, Peter S.;Daun, Mitchell K.;Paulson, Eric S.;Schmainda, Kathleen M.
关键词：
最近，动态磁化率对比(DSC)MRI处理技术突出了异常的脑肿瘤血管形成。该技术使用独立分量分析(ICA)来分离动脉和静脉灌注。两者的重叠，即动-静脉重叠或AVOL，优先发生在脑肿瘤中，并预测抗血管生成治疗的反应。造影剂泄漏对AVOL生物标记物的影响尚未确定。DSC是在10名接受临床成像诊断脑肿瘤的患者中在两次单独的对比剂注射中获得的。用ICA模拟了三个部分，包括动脉和静脉部分。在对比剂增强的肿瘤中测定每种成分以及第三种成分的百分比，并进行比较。并比较不同剂量的AVOL对肿瘤的增强作用。与第二次相比，第一次对比剂剂量的时间序列中明显有造影剂渗漏的强化肿瘤的百分比被归类为不是动脉或静脉的，而是第三种成分。在增强的肿瘤内检测到的AVOL的量与第一次相比，第二次剂量也明显更大。对比度泄漏导致较大的信号方差被ICA算法归类为单独的分量。第二次剂量的使用减轻了这种影响，并允许在增强范围内测量AVOL。
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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影响因子：
5.7
作者：
Calhoun VD;Liu J;Adali T
通讯作者：
Adali T
影响因子：
3.5
作者：
Hu, L. S.;Baxter, L. C.;Heiserman, J. E.
通讯作者：
Heiserman, J. E.
影响因子：
4.4
作者：
DEANE, BR;LANTOS, PL
通讯作者：
LANTOS, PL
DOI：
10.1016/j.ijrobp.2009.10.072
发表时间：
2011-02-01
影响因子：
7
作者：
Gahramanov, Seymur;Raslan, Ahmed M.;Neuwelt, Edward A.
通讯作者：
Neuwelt, Edward A.
DOI：
10.1006/cbmr.1996.0014
发表时间：
1996-06-01
期刊：
COMPUTERS AND BIOMEDICAL RESEARCH
影响因子：
--
作者：
Cox, RW
通讯作者：
Cox, RW