北京大学学报(医学版) ›› 2021, Vol. 53 ›› Issue (2): 341-347. doi: 10.19723/j.issn.1671-167X.2021.02.019
HU Di,ZHANG Miao,KANG Hui-ying,PENG Yun()
摘要:
目的: 研究0~2 岁中国正常婴幼儿大脑白质微结构发育演变过程的磁共振弥散张量特征,建立婴幼儿脑白质微结构标准模板并进行验证。方法: 应用非线性高配准精度的微分同胚非刚性配准范式(large deformation diffeomorphic metric mapping, LDDMM)对核磁弥散张量图像进行配准,选取经神经内科医师、影像科医师及Gesell发育诊断量表(Gesell developmental scale, GDS)评估临床查体、运动和认知均正常,常规核磁头颅检查未见颅内占位及先天畸形,足月顺产,无母体孕期疾病(妊高症、糖尿病等)、宫内缺血缺氧、头颅外伤、颅内感染、颅内手术病史、精神疾患家族史的0~2岁婴幼儿共120例进行头颅扩散张量成像(diffusion tension imaging, DTI)扫描,按照婴幼儿年龄将数据分为6组(A组:1 d~1.5个月,B组:1.5~4.5个月,C组:4.5~9.0个月,D组:9~15个月,E组:15~21个月,F组:21~24个月),以每组选定的独立样本为模板,应用MRlcron、DtiStudio、DiffeoMap及SPM软件结合LDDMM配准算法对所得DTI数据进行数据预处理、张量计算和图像归一化,并应用Matlab对最终图像进行平均计算构建相应组别对应的平均图谱。建立图谱包括各向异性(fractional anisotropy, FA)图、彩色编码图、T1加权像图(T1 weighted image,T1WI)、b0图以及平均弥散加权图(mean of diffusion weighted figures, DWfs)。结果: 建立0~2 岁中国婴幼儿磁共振正常大脑白质FA、T1WI、b0、DWfs以及彩色编码模板,所有模板主观评分均超过2分,客观评估参量模板均方根误差(root mean squared error, RMSE)控制在0.19以下,且根据结构T1模板建立的月龄0~2岁儿童大脑平均体积变化立方趋势图与既往文献报道结构模板变化趋势相同。结论: 应用非线性高配准精度的微分同胚非刚性配准范式建立的0~2 岁中国正常婴幼儿大脑白质微结构发育演变模板,不仅为进一步分析人类大脑发育及功能形成过程、脑发育相关疾病的机制和治疗效果提供基础数据,而且为医疗、教学、科研提供客观的影像学信息。
中图分类号:
[1] |
Jernigan TL, Baaré WF, Stiles J, et al. Postnatal brain development: Structural imaging of dynamic neurodevelopmental processes[J]. Prog Brain Res, 2011,189:77-92.
pmid: 21489384 |
[2] |
Dittrich E, Kasprian G, Prayer D, et al. Atlas learning in fetal brain development[J]. Top Magn Reson Imaging, 2011,22(3):107-111.
pmid: 23558465 |
[3] | Dubois J, Dehaene-Lambertz G, Mangin JF, et al. Brain development of infant and MRI by diffusion tensor imaging[J]. Neurophysiol Clin, 2012,42(1/2):1-9. |
[4] |
Rose J, Vassar R, Cahill-Rowley K, et al. Brain microstructural development at near-term age in very-low-birth-weight preterm infants: an atlas-based diffusion imaging study[J]. Neuroimage, 2014,86:244-256.
pmid: 24091089 |
[5] |
Silbereis JC, Pochareddy S, Zhu Y, et al. The Cellular and molecular landscapes of the developing human central nervous system[J]. Neuron, 2016,89(2):248-268.
doi: 10.1016/j.neuron.2015.12.008 pmid: 26796689 |
[6] | 刘岭岭, 孛茹婷, 杨文君, 等. 磁共振弥散张量成像技术在新生儿脑白质发育中的研究[J]. 磁共振成像, 2015,6(4):253-257. |
[7] | 侯欣, 杨健, 鱼博浪. 磁共振扩散张量成像在新生儿脑发育的应用及展望[J]. 磁共振成像, 2012,3(1):74-78. |
[8] |
Oishi K, Mori S, Donohue PK, et al. Multi-contrast human neonatal brain atlas: application to normal neonate development analysis[J]. Neuroimage, 2011,56(1):8-20.
pmid: 21276861 |
[9] | 王星, 陈楠, 李坤成. 数字标准脑研究现状和进展[J]. 中国医疗装备, 2008,23(7):56-86. |
[10] |
Mazziotta J, Toga A, Evans A, et al. A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM)[J]. Philos Trans R Soc Lond B Biol Sci, 2001,356(1412):1293-1322.
pmid: 11545704 |
[11] |
Knickmeyer RC, Gouttard S, Kang C, et al. A Structural MRI study of human brain development from birth to 2 years[J]. J Neurosci, 2008,28(47):12176-12182.
pmid: 19020011 |
[12] |
Deshpande R, Chang L, Oishi K. Construction and application of human neonatal DTI atlases[J]. Front Neuroanat, 2015,9:138.
doi: 10.3389/fnana.2015.00138 pmid: 26578899 |
[13] |
Akazawa K, Chang L, Yamakawa R, et al. Probabilistic maps of the white matter tracts with known associated functions on the neonatal brain atlas: application to evaluate longitudinal developmental trajectories in term-born and preterm-born infants[J]. Neuroimage, 2016,128:167-179.
doi: 10.1016/j.neuroimage.2015.12.026 pmid: 26712341 |
[14] |
Kochunov P, Fox P, Lancaster J, et al. Localized morphological brain differences between English-speaking Caucasians and Chinese-speaking Asians: new evidence of anatomical plasticity[J]. Neuroreport, 2003,14(7):961-964.
doi: 10.1097/01.wnr.0000075417.59944.00 pmid: 12802183 |
[15] | Michel T, Francisco JA. On human nature[M]. United Kingdom: Academic Press, 2017: 579-597. |
[16] |
Tan M, Qiu A. Multiresolution diffeomorphic mapping for cortical surfaces[J]. Inf Process Med Imaging, 2015,24:315-326.
doi: 10.1007/978-3-319-19992-4_24 pmid: 26221683 |
[17] |
Hernandez M. Gauss-Newton inspired preconditioned optimization in large deformation diffeomorphic metric mapping[J]. Phys Med Biol, 2014,59(20):6085-6115.
pmid: 25254606 |
[18] |
Hsu YC, Hsu CH, Tseng WY. A large deformation diffeomorphic metric mapping solution for diffusion spectrum imaging datasets[J]. Neuroimage, 2012,63(2):818-834.
pmid: 22836183 |
[19] | 闫德勤, 刘彩凤, 刘胜蓝, 等. 大形变微分同胚图像配准快速算法[J]. 自动化学报, 2015,41(8):1461-1470. |
[20] | 查珊珊, 王远军, 聂生东. 基于图形处理器加速的医学图像配准技术进展[J]. 计算机应用, 2015,35(9):2486-2491, 2512. |
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