Strumia Maddalena, Reichardt Wilfried, Staszewski Ori, Heiland Dieter Henrik, Weyerbrock Astrid, Mader Irina, Bock Michael
German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, Heidelberg, Germany.
University Medical Center Freiburg, Radiology-Medical Physics, Breisacher Str. 60a, 79106, Freiburg, Germany.
MAGMA. 2016 Oct;29(5):765-75. doi: 10.1007/s10334-016-0558-z. Epub 2016 Apr 20.
To differentiate between abnormal tumor vessels and regular brain vasculature using new quantitative measures in time-of-flight (TOF) MR angiography (MRA) data.
In this work time-of-flight (TOF) MR angiography data are acquired in 11 glioma patients to quantify vessel abnormality. Brain vessels are first segmented with a new algorithm, efficient monte-carlo image-analysis for the location of vascular entity (EMILOVE), and are then characterized in three brain regions: tumor, normal-appearing contralateral brain, and the total brain volume without the tumor. For characterization local vessel orientation angles and the dot product between local orientation vectors are calculated and averaged in the 3 regions. Additionally, correlation with histological and genetic markers is performed.
Both the local vessel orientation angles and the dot product show a statistically significant difference (p < 0.005) between tumor vessels and normal brain vasculature. Furthermore, the connection to both histology and the gene expression of the tumor can be found-here, the measures were compared to the proliferation marker Ki-67 [MIB] and genome-wide expression analysis. The results in a subgroup indicate that the dot product measure may be correlated with activated genetic pathways.
It is possible to define a measure of vessel abnormality based on local vessel orientation angles which can differentiate between normal brain vasculature and glioblastoma vessels.
利用飞行时间（TOF）磁共振血管造影（MRA）数据中的新定量测量方法，区分异常肿瘤血管和正常脑脉管系统。
在本研究中，对11例神经胶质瘤患者采集飞行时间（TOF）磁共振血管造影数据，以量化血管异常情况。首先用一种新算法——用于血管实体定位的高效蒙特卡洛图像分析（EMILOVE）对脑内血管进行分割，然后在三个脑区进行特征分析：肿瘤、对侧外观正常的脑区以及不包括肿瘤的全脑体积。为进行特征分析，计算局部血管取向角以及局部取向向量之间的点积，并在这三个区域求平均值。此外，还进行了与组织学和基因标志物的相关性分析。
局部血管取向角和点积在肿瘤血管与正常脑脉管系统之间均显示出统计学上的显著差异（p < 0.005）。此外，还发现了与肿瘤组织学和基因表达的关联——在此，将这些测量结果与增殖标志物Ki-67 [MIB]以及全基因组表达分析进行了比较。一个亚组的结果表明，点积测量可能与激活的基因通路相关。
基于局部血管取向角定义一种血管异常测量方法是可行的，该方法能够区分正常脑脉管系统和胶质母细胞瘤血管。
