Center for Information and Neural Networks, National Institute of Information and Communications Technology, 1-4 Yamadaoka, Suita, Osaka 565-0871, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita, Osaka 565-0871, Japan.
Siemens Healthcare K.K., Shinagawa, Tokyo 141-8644, Japan.
Neuroimage. 2020 Nov 15;222:117259. doi: 10.1016/j.neuroimage.2020.117259. Epub 2020 Aug 13.
Cerebral artery segmentation plays an important role in the direct visualization of the human brain to obtain vascular system information. On ultra-high field magnetic resonance imaging, cerebral arteries appearing hyperintense on T1 weighted (T1w) images could be segmented from brain tissues such as gray and white matter. In this study, we propose an automated method to segment the cerebral arteries using multi-contrast images including T1w images of a magnetization-prepared two rapid acquisition gradient echo (MP2RAGE) sequence at 7 T. The proposed method, termed MP2rase-CA (MP2rage based RApid SEgmentation Cerebral Artery), employed a seed-based region-growing strategy and Frangi filtering as well as our brain tissue segmentation (MP2rase Brain Tissue). Time-of-flight (TOF) magnetic resonance angiography (MRA) images were obtained as a reference to evaluate the MP2rase-CA. We successfully performed vessel segmentations, from T1w MP2RAGE images, which mostly overlapped with the segmentations of large cerebral arteries from the TOF-MRA. We also investigated the effect of the large cerebral arteries on spatial transformation of anatomical images to standard coordinate space using vessel segmentation by MP2rase-CA. As a result, the T1w image without the cerebral arteries by MP2rase-CA showed better agreement with the standard atlas compared with the T1w image containing the arteries. In addition, voxel-based morphology showed significant differences between T1w images with and without cerebral arteries in brain areas nearby large arteries. Thus, because MP2rase-CA using MP2RAGE images can obtain brain tissue anatomical information as well as relatively large cerebral artery information without need for additional structure acquisition, it is useful and time saving for functional and structural studies.
脑动脉分割在直接可视化人脑以获取血管系统信息方面起着重要作用。在超高场磁共振成像中，T1 加权（T1w）图像上呈现高信号的脑动脉可以从灰质和白质等脑组织中分割出来。在这项研究中，我们提出了一种使用多对比度图像（包括 7T 下的磁化准备双快速获取梯度回波（MP2RAGE）序列的 T1w 图像）自动分割脑动脉的方法。该方法称为 MP2rase-CA（基于 MP2rage 的快速分割脑动脉），采用基于种子的区域生长策略和 Frangi 滤波以及我们的脑组织分割（MP2rase Brain Tissue）。获得时飞（TOF）磁共振血管造影（MRA）图像作为参考来评估 MP2rase-CA。我们成功地从 T1w MP2RAGE 图像中进行了血管分割，这些分割与 TOF-MRA 中的大脑血管分割大部分重叠。我们还研究了通过 MP2rase-CA 进行血管分割对将解剖图像转换到标准坐标空间的大血管的空间变换的影响。结果表明，与包含动脉的 T1w 图像相比，MP2rase-CA 生成的无脑血管的 T1w 图像与标准图谱具有更好的一致性。此外，基于体素的形态学显示，在大动脉附近的脑区，有无脑动脉的 T1w 图像之间存在显著差异。因此，由于使用 MP2RAGE 图像的 MP2rase-CA 可以获得脑组织解剖信息以及相对较大的脑动脉信息，而无需额外的结构采集，因此对于功能和结构研究非常有用且节省时间。
