目的：应用扩散峰度成像（DKI）探讨健康成人脑白质组织微观结构与年龄的相关性变化。方法：对60例正常志愿者进行常规MRI和DKI扫描，志愿者按年龄分为3组：青年组（20～＜40岁）20例、中年组（40～＜60岁）20例、老年组（≥60岁）20例，经后处理得到DKI相关参数图。于外囊、内囊前肢和后肢、胼胝体膝部和压部、半卵圆中心、额叶选取感兴趣区测定相关参数值，包括各向异性分数（FA）、平均峰度（MK）、径向峰度（RK）、轴向峰度（AK）值，并作统计学分析。结果：内囊前肢、胼胝体膝部、压部、半卵圆中心、额叶FA值与年龄呈显著负相关（P＜0.05），其中，内囊前肢、额叶FA值表现为：青年组＞老年组（P＜0.017），胼胝体膝部、压部、半卵圆中心FA值表现为：青年组＞中年组，青年组＞老年组。各选取白质感兴趣区MK值与年龄呈显著负相关，其中，外囊、内囊后肢、胼胝体膝部、压部、半卵圆中心、额叶MK值表现为：青年组＞中年组＞老年组，内囊前肢MK值表现为：青年组＞中年组，青年组＞老年组。各选取白质感兴趣区RK值与年龄呈显著负相关。其中，内囊前肢、胼胝体膝部、压部、半卵圆中心、额叶RK值表现为：青年组＞中年组＞老年组，外囊、内囊后肢RK值表现为：青年组＞中年组，青年组＞老年组。AK值与年龄无显著相关。脑白质FA平均值、MK平均值、RK平均值与年龄呈显著负相关（r值分别为-0.775、-0.933、-0.946），脑白质AK平均值与年龄无显著相关。结论：较传统DTI，DKI能更全面、更敏感地探测健康成人脑白质组织微观结构与年龄的相关性变化。
Abstract
Objective: To explore age-related changes of healthy adult white matter microstructure with diffusion kurtosis imaging(DKI). Methods: Sixty volunteers were divided into three groups according to age: 20 cases of young group(20～＜40 years), 20 cases of middle-aged group(40～＜60 years), 20 cases of elder group(≥60 years). Conventional MRI and DKI were performed. Fractional anisotropy(FA), mean kurtosis(MK), radial kurtosis(RK) and axial kurtosis(AK) were determined in the external capsule, the anterior limb of the internal capsule(ALIC), the posterior limb of the internal capsule(PLIC), the genu of the corpus callosum(CC), the splenium of the CC, the centrum semiovale, the frontal subcortical white matter(sWM). Parameter estimates were obtained and statistically analysed. Results: FA values in the ALIC, genu and splenium of the CC, centrum semiovale and frontal sWM were significant negative correlation with age(P<0.05). FA values in the ALIC and frontal sWM were shown as follows: young group>elder group(P<0.017). FA values in the genu and splenium of the CC and centrum semiovale were shown as follows: young group>middle-aged group, young group>elder group. MK values in the all selected white matter areas were significant negative correlation with age. MK values in the external capsule, PLIC, genu and splenium of the CC, centrum semiovale and frontal sWM were shown as follows: young group>middle-aged group>elder group. MK values in the ALIC were shown as follows: young group>middle-aged group, young group>elder group. RK values in the all selected white matter areas were significant negative correlation with age. RK values in the ALIC, genu and splenium of the CC, centrum semiovale and frontal sWM were shown as follows: young group>middle-aged group>elder group. RK values in the external capsule and PLIC were shown as follows: young group>middle-aged group, young group>elder group. AK values in the all selected white matter areas did not show age dependence. The average FA, MK and RK values from all selected white matter areas were significant negative correlation with age(r values were -0.775, -0.933 and -0.946, respectively). The average AK values did not show age dependence. Conclusion: DKI can offer a more comprehensive and sensitive detection of age-related changes of healthy adult white matter microstructure compared with DTI.
关键词
脑；年龄因素；磁共振成像 /
弥散
Key words
Brain /
Age factors /
Diffusion magnetic resonance imaging
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1]Hui ES, Cheung MM, Qi L, et al. Towards better MR characterization of neural tissues using directional diffusion kurtosis analysis[J]. Neuroimage, 2008, 42(1): 122-134.
[2]Tabesh A, Jensen JH, Ardekani BA, et al. Estimation of tensors and tensor-derived measures in diffusional kurtosis imaging[J]. Magn Reson Med, 2011, 65(3): 823-836.
[3]Beaulieu C. The basis of anisotropic water diffusion in the nervous system-a technical review[J]. NMR Biomedicine, 2002, 15(7-8): 435-455.
[4]Fieremans E, De Deene Y, Delputte S, et al. The design of anisotropic diffusion phantoms for the validation of diffusion weighted magnetic resonance imaging[J]. Phys Med Biol, 2008, 53(19): 5405-5419.
[5]Latt J, Nilsson M, Wirestam R, et al. Regional values of diffusional kurtosis estimates in the healthy brain[J]. J Magn Reson Imaging, 2013, 37(3): 610-618.
[6]Jensen JH, Helpern JA, Tabesh A. Leading non-Gaussian corrections for diffusion orientation distribution function[J]. NMR Biomed, 2014, 27(2): 202-211.
[7]Grieve SM, Williams LM, Paul RH, et al. Cognitive aging, executive function, and fractional anisotropy: a diffusion tensor MR imaging study[J]. AJNR, 2007, 28(2): 226-235.
[8]Madden DJ, Bennett IJ, Burzynska A, et al. Diffusion Tensor Imaging of Cerebral White Matter Integrity in Cognitive Aging[J]. Biochim Biophys Acta, 2012, 1822(3): 386-400.
[9]Cheung MM, Hui ES, Chan KC, et al. Does diffusion kurtosis imaging lead to better neural tissue characterization? A rodent brain maturation study[J]. Neuroimage, 2009, 45(2): 386-392.
[10]Blockx I, De Groof G, Verhoye M, et al. Microstructural changes observed with DKI in a transgenic Huntington rat model: evidence for abnormal neurodevelopment[J]. Neuroimage, 2011, 59(2): 957-967.
[11]Falangola MF, Jensen JH, Babb JS, et al. Age-related non-Gaussian diffusion patterns in the prefrontal brain[J]. J Magn Reson Imaging, 2008, 28(6): 1345-1350.
[12]Hsu JL, Leemans A, Bai CH, et al. Gender differences and age related white matter changes of the human brain: a diffusion tensor imaging study[J]. Neuroimage, 2008, 39(2): 566-577.
[13]Hugenschmidt CE, Peiffer AM, Kraft RA, et al. Relating imaging indices of white matter integrity and volume in healthy older adults[J]. Cereb Cortex, 2008, 18(2): 433-442.
[14]Bartzokis G. Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer’s disease[J]. Neurobiol Aging, 2004, 25(1): 5-18.
[15]Peters A. The effects of normal aging on myelin and nerve fibers: a review[J]. J Neurocytol, 2002, 31(8-9): 581-593.
[16]Andersen BB, Gundersen I-IJ, Pakkenberg B. Aging of the human cerebellum: a stereological study[J]. J Comp Neurol, 2003, 466(3): 356-365.
[17]Grossman EJ, Ge Y, Jensen JH, et al. Thalamus and cognitive impairment in mild traumatic brain injury: a diffusional kurtosis imaging study[J]. J Neurotrauma, 2012, 29(13): 2318-2327.
[18]Hui ES, Du F, Huang S, et al. Spatiotemporal dynamics of diffusional kurtosis, mean diffusivity and perfusion changes in experimental stroke[J]. Brain Res, 2012, 1451: 100-109.
[19]张顺，朱文珍，姚义好，等. 脑梗死不同时期的MR扩散峰度成像表现[J]. 中华放射学杂志，2014，48（6）：443-447.
[20]Van Cauter S, Veraat J, Sijbers J, et al. Gliomas: diffusion kurtosis MR imaging in grading[J]. Radiology, 2012, 263(2): 492-501.
[21]Zhu J, Zhuo C, Qin W, et al. Performances of diffusion kurtosis imaging and diffusion tensor imaging in detecting white matter abnormality in schizophrenia[J]. Neuroimage Clin, 2014, 7: 170-176.
[22]Kimura MC, Doring TM, Rurda FC, et al. In vivo assessment of white matter damage in neuromyelitis optica: a diffusion tensor and diffusion kurtosis MR imaging study[J]. J Neurol Sci, 2014, 345(1-2): 172-175.
[23]Lee CY, Tabesh A, Spampinato MV, et al. Diffuional kurtosis imaging reveals a distinctive pattern of microstructural alternations in idiopathic generalized epilepsy[J]. Acta Neurol Scand, 2014, 130(3): 148-155.
[24]Yoshida M, Hori M, Yokoyama K, et al. Diffusional kurtosis imaging of normal appearing white matter in multiple sclerosis: preliminary clinical experience[J]. Jpn J Radiol, 2013, 31(1): 50-55.
