中国人群帕金森病患者灰质萎缩:采用中国人脑图谱Chinese2020的基于体素的形态学研究

Gray matter atrophy in patients with Parkinson disease in Chinese population:A voxel-based morphometry study using Chinese brain template Chinese2020

目的采用基于体素的形态学测量(VBM)方法探讨中国人脑图谱Chinese2020检测中国人群帕金森病(PD)患者灰质体积改变的价值。方法收集15例PD患者(PD组)和15名性别和年龄匹配的健康志愿者为对照组。分别采用基于中国人群的脑图谱Chinese2020和基于高加索人群的脑图谱MNI152进行空间标准化,比较配准到这2种标准空间所引起的脑结构形变差异,并采用VBM方法比较2种图谱检出PD患者灰质体积萎缩的脑区以及萎缩脑区灰质占比的差异。结果采用MNI152脑图谱发现PD患者灰质萎缩脑区包括双侧颞叶并扩展至同侧脑岛/海马/海马旁回、左侧枕上回/楔叶/楔前叶及右侧壳核;采用Chinese2020图谱后,除上述脑区外,右侧额中回亦可见灰质体积萎缩。PD组和对照组受试者脑结构配准到Chinese2020空间发生形变小于配准到MNI152空间,且基于Chinese2020检测灰质萎缩脑区灰质占比高于采用MNI152图谱(t=2.502,P=0.037)。结论基于中国人群的神经影像学研究应该采用中国人脑图谱进行空间标准化,其脑结构形变更小、所识别出的脑区灰质占比更高,从而提高检测的准确性。

Objective To investigate the value of Chinese brain template Chinese2020 in detecting gray matter(GM)alterations in patients with Parkinson disease(PD)in Chinese population using voxel-based morphometry(VBM).Methods Totally 15 PD patients(PD group)and 15 gender-and age-matched healthy volunteers(control group)were enrolled.Chinese2020 based on Chinese and MNI152 based on Caucasian were used for spatial normalization,respectively.The deformations induced by spatial normalization and gray matter(GM)proportion in the identified brain areas were compared between Chinese2020 and MNI152.The differences of GM volume between PD group and control group were examined using VBM.Results Using MNI152,GM atrophies in PD patients were detected in bilateral temporal lobe extending into ipsilateral insula/parahippocampus/hippocampus,the left superior occipital cortex/cuneus/precuneus,as well as the right putamen.Besides the above mentioned regions,the right middle frontal cortex atrophy was additionally identified using Chinese2020.Particularly,fewer deformations were found when spatially normalizing Chinese population's brain to Chinese2020 than to MNI152.Moreover,GM percentages of detected regions using Chinese2020 were significantly higher than those using MNI152(t=2.502,P=0.037).Conclusion CBT should be used in neuroimaging studies of Chinese population,which may achieve fewer deformations during spatial normalization,more GM proportions in the identified clusters and improve the accuracy of detection.