Hannoun Salem, Baalbaki Marwa, Haddad Ribal, Saaybi Stephanie, El Ayoubi Nabil K, Yamout Bassem I, Khoury Samia J, Hourani Roula
Nehme and Therese Tohme Multiple Sclerosis Center, American University of Beirut Medical Center, Beirut, Lebanon.
Abu-Haidar Neuroscience Institute, Faculty of Medicine, American University of Beirut Medical Center, Beirut, Lebanon.
Neuroradiology. 2018 Nov;60(11):1167-1173. doi: 10.1007/s00234-018-2082-5. Epub 2018 Aug 21.
Gadolinium-based contrast agent (GBCA) effect on automated segmentation algorithms of subcortical gray matter (GM) is not fully known. The aim of this study is to determine gadolinium effect on the segmentation of the thalamus and whole brain tissue using different automated segmentation techniques.
Eighty-four multiple sclerosis (MS) patients underwent an MRI acquisition of two 3DT1-weighted sequences with and without gadolinium injection among which 10 were excluded after image quality check. Manual thalamic segmentation considered as gold standard was performed on unenhanced T1 images. volBrain and FSL-Anat were used to automatically segment the thalamus on both enhanced and unenhanced T1 and the degree of similitude (DICE) values were compared between manual and automatic segmentations. Whole brain tissue segmentation (GM, white matter (WM), and lateral ventricles (LV)) was also performed using SIENAX. A paired samples t test was applied to test the significance of DICE value differences between the thalamic manual and automatic segmentations of both enhanced and unenhanced T1 images.
Significant differences (FSL-Anat 1.474% p < 0.001 and volBrain 1.990% p < 0.001) in DICE between thalamic manual and automatic segmentations on both enhanced and unenhanced images were observed. Automatic tissue segmentation showed a mean DICE of 81.5%, with LV having the lowest DICE value (74.2%). When compared to tissue segmentations, automatic thalamic segmentations by FSL-Anat or volBrain demonstrated a higher degree of similitude (FSL-Anat = 91.7% and volBrain = 90.7%).
Gadolinium has a significant effect on subcortical GM segmentation. Although significant, the observed subtle changes could be considered acceptable when used for region-based analysis in perfusion or diffusion imaging.
钆基造影剂（GBCA）对皮质下灰质（GM）自动分割算法的影响尚不完全清楚。本研究的目的是使用不同的自动分割技术确定钆对丘脑和全脑组织分割的影响。
84例多发性硬化症（MS）患者在注射钆和未注射钆的情况下分别进行了两次3DT1加权序列的MRI采集，其中10例在图像质量检查后被排除。在未增强的T1图像上进行被视为金标准的手动丘脑分割。使用volBrain和FSL-Anat在增强和未增强的T1图像上自动分割丘脑，并比较手动分割和自动分割之间的相似性（DICE）值。还使用SIENAX进行全脑组织分割（GM、白质（WM）和侧脑室（LV））。应用配对样本t检验来检验增强和未增强T1图像的丘脑手动分割和自动分割之间DICE值差异的显著性。
在增强和未增强图像上，丘脑手动分割和自动分割之间的DICE存在显著差异（FSL-Anat为1.474%，p<0.001；volBrain为1.990%，p<0.001）。自动组织分割的平均DICE为81.5%，其中LV的DICE值最低（74.2%）。与组织分割相比，FSL-Anat或volBrain的自动丘脑分割显示出更高的相似性（FSL-Anat = 91.7%，volBrain = 90.7%）。
钆对皮质下GM分割有显著影响。虽然有显著影响，但在灌注或扩散成像中用于基于区域的分析时，观察到的细微变化可被认为是可接受的。
