多模态MRI影像在矿难创伤后应激障碍研究中的应用
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摘要
创伤后应激障碍(Post-traumatic Stress Disorder, PTSD)指由突发性、威胁性或灾难性事件引起人体延迟出现并长期持续存在的精神障碍。常常表现为再度体验创伤,易激惹和回避行为,并常伴有睡眠障碍、注意力难以集中、警觉性过高、过度惊吓反应等症状。大部分人在创伤后数天至六个月内发病,经过一段时间调整后都可以恢复正常。据报道,在美国,约有3.6%的人曾患有PTSD,而其中7.8%的患者终身患病。引发创伤的事件包括战争、暴力犯罪、性侵害、交通事故、失业、离婚、自然灾害等,PTSD患者多为直接或间接接触创伤事件的幸存者、目击者和救援者。有研究表明,不同类型的创伤可能影响PTSD严重程度和症状表现。目前,PTSD已成为流行病学、心理学、社会医学等多个学科的研究热点。尤其是,近年来,矿难、地震、海啸、恐怖袭击频发,这些突发的灾难性事件所引起的PTSD越来越受到人们的关注。
     目前,各国科学家已通过遗传、神经、生化、内分泌、心理及社会等多方面的研究,对PTSD病理、病因学机制进行了探讨,但具体机制仍不甚明晰。同时,由于对介导PTSD症状的大脑环路缺乏清晰的认识,目前仍未有针对PTSD的有效治疗方法。
     近年来,影像医学的发展为脑部疾病的研究提供了新的手段。特别是磁共振成像(Magnetic Resonance Imaging, MRI)已逐渐从结构成像扩展到功能成像,从单模态成像发展到多模态成像。从多方面来分析患者的结构变化、血流灌注、功能代谢和功能连接等信息,将MRI的多种模态相结合,并应用到脑部疾病的诊断和评价,是目前的研究热点和难点。现已有研究通过影像手段,初步发现了PTSD患者在脑部结构和功能方面不同程度的病理性损害。
     对于精神类疾病,在疾病引发实质性病变之前,往往会先出现功能代谢、血流灌注和功能区形状(如脑皮层厚度)的改变。因此,对脑皮层厚度和脑血流的分析往往可以检测出疾病发生早期对人体结构和功能的影响。各向异性分数(fractional anisotropy,FA)和表面弥散系数(apparent diffusion coefficient,ADC)可以有效反映微结构及分子水平的病理、生理学改变,能够检测早期的病变引起的脑损伤。但目前,尚未见基于MRI影像,对矿难创伤后PTSD所引起脑皮层厚度、血流及DTI指标变化的研究。
     本研究针对上述问题,利用矿难幸存者的MRI结构、灌注和弥散张量成像(Diffusion Tensor Imaging, DTI)数据,进行脑皮层厚度、脑血流及DTI指标分析,检测矿难创伤后早期PTSD(MRI扫描时间为事故发生后6个月)对脑部结构和功能的影响;并进一步研究这些结构和功能的变化与PTSD症状的严重程度的相关关系及相关程度。
     本研究被试者为2007年河南省三门峡市东风井,因河床水通过采空区涌入井下,而被困1400米深地下72小时的幸存者。参加本研究的20名幸存者中10人满足DSM-IV中描述的PTSD指标,为PTSD组;另外10人不满足,为非PTSD组。PTSD病情的严重程度通过创伤后应激障碍量表(Clinician-administered PTSD Scale, CAPS)进行评价。
     本研究主要包含以下研究内容:
     1、脑皮层厚度的准确测量及分析
     在已有研究的基础上,本文构建了基于拉普拉斯方程的脑皮层三维厚度检测流程和方法,提高了计算速度和测量的准确性。首先考虑到DARTEL标准化算法对脑部细微结构进行配准具有更高的准确性,检测细微结构的异常变化具有更高的敏感性,本研究中利用VBM-DARTEL工具包对MRI的T1序列图像进行预处理,得到分割后的脑灰质、白质和脑脊液数据。并在预处理结果的基础上,采用改进的基于拉普拉斯偏微分方程的三维厚度测量方法测量脑皮层厚度,该方法通过在脑皮层内部构建势能场,并利用垂直等势面场线的长度来定义皮层厚度,使内、外表面具有唯一可逆对应点,避免了最短欧氏距离引起的测量误差,是目前脑皮层厚度测量最准确、有效的测量方法之一。但由于大脑脑沟区域的复杂形态变化和数据采集过程中各种因素的影响,容易造成分割误差。因此,在测量脑皮层三维厚度之后,采用脑沟厚度校正方法对可能存在误分割的脑沟区域进行校正,并根据校正后的灰质图像,重新测量脑皮层厚度,从而得到更准确的三维厚度值,并构建三维脑皮层厚度图像。
     在构建脑皮层结构和三维厚度图像的基础上,利用SPM对两组间的体积及皮层厚度进行统计学分析。由于在人口学特征分析中,两组除年龄外,其他特征都不存在统计学差异,因此,本研究以年龄作为协变量,通过两样本t检验进行分析,未发现两组的体积存在统计学差异的区域。但对脑皮层厚度的统计分析表明,较非PTSD组,PTSD组在左脑顶叶、右脑额下回和右脑海马旁回区域脑皮层厚度明显变薄。
     为了探索PTSD严重程度与脑皮层厚度间的相关关系,本研究采用穿过厚度变薄区域的场线上的所有体素,作为感兴趣区域(Regional of Interest,ROI)。通过ROI分析发现,PTSD组的10名被试者的右脑额下回的平均厚度与PTSD症状的严重程度(CAPS值)明显负相关。
     2、脑血流(Cerebral Blood Flow, CBF)的准确测量及分析
     通过灌注成像扫描序列的筛选,本研究使用无创、标记效率高的脉冲式动脉自旋标记(Pulsed Artery Spin Labeling, PASL)扫描序列来分析矿难后早期PTSD患者的CBF变化。为此,本研究在已有研究的基础上,构建了PASL序列CBF准确测量方法。
     首先,由于PASL序列图像成像速度快,图像分辨率较低,本研究利用SPM分别对PASL序列图像和T1序列结构图像进行预处理,并将结构像信息应用到功能像当中,提高标准化的准确性和功能图像的分辨率。经过预处理后,图像分辨率有所提高,但仍受到部分容积效应(Partial Volume Effect,PVE)的严重影响。为此,本研究首次利用PASL序列的时间信息,构建了PASL时间序列,并使用MAP-EM算法分析时间序列中每个体素点中的混合组织参数,并结合CBF的测量方法,在对图像进行部分容积校正的基础上,获得更准确的CBF分布图。
     获得CBF分布图后,通过分析,未发现两组的平均CBF统计学差异。但考虑到年龄对CBF的影响,本研究以年龄作为协变量,采用SPM进行两样本t检验,发现PTSD组,较非PTSD组,在右脑额叶区域CBF明显增高。但通过ROI分析,未发现PTSD组在该区域的平均CBF值与PTSD症状严重程度(CAPS值)存在相关关系。
     3、DTI数据分析
     本研究使用DTI Studio和SPM联合分析了矿难幸存者的DTI序列数据,发现PTSD组,较非PTSD组,在右脑侧脑室、右脑梭状回、右脑颞上回和右脑颞中回区域FA值明显降低,在右脑颞上回和右脑胼胝体区域ADC值明显增高。但通过ROI分析,未发现PTSD组在这些区域的平均FA值或ADC值与PTSD症状严重程度(CAPS值)存在相关关系。这可能是由于PTSD早期引起的结构及功能变化不明显,FA和ADC指标尚无显著变化所导致的。
     4、小结
     本研究首先构建了基于拉普拉斯方程的脑皮层厚度检测流程和方法,提高了计算速度和测量的准确性;考虑到灌注成像的分辨率低及PVE对CBF测量的影响,将基于MAP-EM算法的部分容积校正理论与CBF测量方法相结合,得到更准确的CBF分布图,上述方法为研究神经系统或脑部疾病引起的脑皮层厚度和血流变化提供了有效的手段。
     基于提出的方法,本研究对经历矿难的20名幸存者构成的PTSD组和对照组的脑皮层厚度和CBF分布进行了统计分析,发现了多个厚度或CBF存在差异的的区域。同时,使用DTI Studio和SPM联合分析了DTI序列数据,发现了多个FA和ADC值异常的脑区。以上结果一方面可为进一步理解PTSD病理、病因学机制奠定基础,另一方面,提出的区域或指标,有望进一步成为早期PTSD临床诊断和评价的依据。
Post-traumatic stress disorder (PTSD) is an anxiety disorder that developsafter exposure to a terrifying event or ordeal in which grave physical harmoccurred or was threatened. Its features persist for a long duration. The commonsymptoms of PTSD are re-experience trauma, irritability, and avoidance behavior,accompanied by sleep disorders, lack of concentration, high alertness, excessivescare, etc. In general, the symptom is occurred in several days to six months afterexposure to the trauma. It’s reported that about3.6%Americans have sufferedfrom PTSD, and7.8%of them cannot be cured. The PTSD may be induced bywarfare, violent crime, sexual abuse, traffic accident, unemployment, divorce,natural disaster, etc. The patients of PTSD are the survivors, witnesses, andrescue workers of the trauma. At present, PTSD is hot topic of epidemiology,psychology, social medicine. A recent study reported that different types oftraumatic experiences may result in different levels of PTSD severity and displaydistinct PTSD symptom patterns. Especially, in recent years, the coal minedisaster, earthquakes, tsunamis, terrorist attack occur frequently. Therefore, thekind of PTSD induced by the sudden disaster is more and more concerned.
     Currently, many researches have investigated the pathological andetiological mechanism, according to genetics, nerve, biochemistry, incretion,psychology and sociology studies. However, the detailed mechanism of PTSDremains unclear. Due to lack of clear understanding the alteration of braininduced by PTSD, there is no effectively therapeutic method for PTSD.
     With the development of medical imaging, it provides a new method to thestudy of brain diseases. Especially, Magnetic Resonance Imaging (MRI) hasgradually developed from structural imaging to functional imaging, fromsingle-modality to multi-modality imaging. To analyze the alteration of structure,blood perfusion, metabolism and connection information in patients with PTSDfrom a range of directions, and combine multi-modality of MRI to diagnosis andevaluate the brain disease, is the hot and difficult topic at present. It is reportedthat different degree of pathological damage was preliminary found in thepatients with PTSD, based on the medical imaging.
     For psychiatric diseases, the alterations of metabolism, perfusion and theshape of cortical cortex (cortical thickness) are usually occurred before thesubstantive lesions. So the cortical thickness and cerebral blood flow (CBF)analysis are often used to detect the effect of brain disease on the structure andfunction at early stage of disease. Fractional anisotropy (FA) and apparentdiffusion coefficient (ADC) are thought to reflect the microstructural alteration,physiological and pathological changes at the molecular level. However, to ourknowledge, no studies have investigated the effect of PTSD induced by coal minedisaster on the cortical thickness, CBF, FA and ADC value.
     In view of above questions, the present study analyzed the difference incortical thickness, CBF, FA and ADC of whole brain in patient with recent onsetPTSD due to a mining disaster. The elapsed time between the traumatic event and MRI scans was ranged from187to190days. After the comparison of corticalthickness and CBF between subjects with and without PTSD, the relationship ofcortical thickness and CBF of identified regions with the PTSD symptom severitywas investigated.
     In2007, a severe coalmine-flooded disaster occurred at Sanmenxia of HenanProvince. Sixty-nine male miners were trapped in a nearly1400m undergroundcoal pit. All the twenty subjects in this study are the survivors from this suddendisaster. Ten of them met the diagnostic criteria for PTSD, while the other tenpersons didn’t meet. With the constructed PTSD and non-PTSD groups in thisstudy, each group had10male subjects. The severity of their symptoms wasassessed with the Chinese version of the Clinician-Administered PTSD Scale(CAPS)
     1. Cortical thickness measurement and analysis
     In this study, the pipeline for cortical thickness measurement and analysiswas proposed, which improved computation speed and the accuracy of thicknessmeasurement. Considering DARTEL has a higher sensitivity in detecting subtleabnormalities of structures and accurate realignment of subtle structure, in thisstudy, the VBM-DARTEL was used to preprocess the T1sequence of MRI andsegment the normalized data into gray matter, white matter and cerebrospinalfluid (CSF) with signal intensity and prior probability information. Based on thesegmented gray matter, white matter and CSF, the3D cortical thickness wasestimated by the Laplacian approach. According to building series ofequipotential surfaces, the cortical thickness is defined as the arc length of thestreamlines which is perpendicular to the equipotential surfaces. This methodavoided the measurement error from Euclidean distance with unique andreversible corresponding points between two surfaces, and is regarded as one of most accurate and efficient thickness measurement method currently. Due to thetopological shell of the cerebral cortex and various influence factors in dataacquisition, it is hard to classify the tissues perfectly, especially in sulci regions.In this study, the algorithm developed for sulci detection and thickness correctionwas employed to further improve the brain segmentation after the thicknessestimation. After the correction of the segmentation, the cortical thickness wasre-calculated accordingly and more accurate result was obtained for the wholebrain.
     Based on the image of cortical thickness, the difference of thickness can beanalyzed with statistical parametric mapping (SPM). Group differences indemographic variables were examined with independent t-tests. All subjects inthis study came from the same community and did not differ significantly insocioeconomic status. The two groups (PTSD and non-PTSD) significantlydiffered in age. Thus, group comparisons of cortical thickness were performedusing analysis of two sample t-test in SPM8with age as covariates to account forthe age effect. Comparisons of cortical thickness in survivors experienced miningdisaster indicated that in left parietal lobe, right inferior frontal gyrus, and rightparahippocampal gyrus, cortical thickness of subjects with PTSD was obviouslythinner than those without PTSD.
     To investigate the relation between thickness and s PTSD symptom severity,the region that consists of all the voxels on the streamline across the significantlythinner region was used for ROI analysis in this study. ROI-based correlationalanalysis was performed in the patients with PTSD. The mean cortical thickness ofright inferior frontal gyrus tended to correlate negatively with the CAPS score inthe identified regions from thickness analysis.
     2. CBF measurement and analysis
     According to selection of MRI perfusion sequences, in this study, the pulsedartery spin labeling (PASL) sequence was used to investigate the alteration ofCBF for the patients of PTSD induced by coal mine disaster, which isnon-invasive with high efficiency. In this study, an accurate CBF measurementmethod of PASL sequence was proposed.
     Due to fast imaging of PASL, the resolution of image is relative low. For thisreason, SPM was used to preprocess the PASL and T1sequences, respectively.With the information of structural images applied to the functional images, theaccuracy of normalization and resolution of functional images were improved.Though the resolution of images had been improved, the images were stillaffected by partial volume effect (PVE). In this study, the acquired time of PASLsequence was used to construct the time sequence, and the MAP-EM algorithmwas used to estimate the mixed tissue model parameters. Moreover, combinedwith this PVE correction, the CBF measurement method was used to acquire thedistribution image of CBF.
     Based on the CBF image, no significant difference of mean CBF was foundbetween the PTSD and non-PTSD groups. Considering the effect of age on theCBF, group comparisons of CBF were performed using analysis of two samplet-test in SPM8with age as covariates to account for the age effect. Comparisonsof CBF in survivors experienced mining disaster indicated that in right frontallobe, CBF of subjects with PTSD was obviously higher than those without PTSD.However, based on ROI analysis in patients with PTSD, no significant correlationof the CAPS score with mean CBF in right frontal lobe was observed.
     3. DTI analysis
     Based on the software of DTI studio and SPM, the DTI sequence wasanalyzed. Comparisons of FA and ADC in survivors experienced mining disaster indicated that in the right lateral ventricle, right fusiform gyrus, right superiortemporal gyrus, and right middle temporal gyrus, FA value of subjects with PTSDwas obviously lower than those without PTSD, and ADC value of subjects withPTSD was obviously higher in the right superior temporal gyrus and right corpuscallosum. However, based on ROI analysis in patients with PTSD, no significantcorrelation of the CAPS score with mean FA and/or ADC in above identifiedregions was observed. That may be due to subtle alteration of cortical thicknesscaused by early stage of PTSD.
     4. Summary
     In this study, the pipeline for cortical thickness measurement and analysiswas proposed, which improved computation speed and the accuracy of thicknessmeasurement. Meanwhile, considering the relatively low resolution and the effectof PVE on images, the PVE correction method based on MAP-EM algorithm wascombined with CBF measurement method to keep the accuracy of the CBF.These proposed methods may provide an efficient method for the corticalthickness and CBF analysis for nerve system or brain diseases.
     Based on proposed methods, in this study, a series of regions withsignificant difference between PTSD and non-PTSD groups were identified.Meanwhile, based on the software of DTI studio and SPM, the DTI sequence wasanalyzed. According to multiple regression analysis, the advantage ofmulti-modality image analysis is preliminarily confirmed. These results lay asolid foundation for the further study of pathological and etiological mechanism.Furthermore, the identified regions or indexes are hopeful to be the objective andquantitative indexes to diagnosis and evaluate PTSD in clinic.
引文
[1] Kessler RC, Sonnega A, Bromet E, Hughes M, Nelson CB. Posttraumaticstress disorder in the National Comorbidity Survey. Arch Gen Psychiatry.1995;52(12):1048–1060.
    [2] Breslau N. Epidemiologic studies of trauma, posttraumatic stress disorder,and other psychiatric disorders. Can J Psychiatry.2002;47(10):923–929.
    [3] Smith MY, Redd WH, Peyser C, Vogl D. Post-traumatic stress disorder incancer: a review. Psychooncology.1999;8(6):521–537.
    [4] Gon alves SI. Multimodality in Brain Imaging: Methodologic Aspects andApplications. Advances in Computational Vision and Medical ImageProcessing.2009;13:93–103.
    [5] Raichle ME. Behind the scenes of functional brain imaging: A historicaland physiological perspective. Proc. Natl. Acad. Sci. USA.1998;95(3):765–772
    [6] Le Bihan D. Looking into the functional architecture of the brain withdiffusion MRI. Nat Rev Neurosci.2003;4(6):469–480.
    [7] Heeger DJ, Huk AC, Geisler WS, Albrecht DG. Spikes versus BOLD: whatdoes neuroimaging tell us about neuronal activity? Nat Neurosci.2000;3(7):631–633.
    [8] Haberg A, Kvistad KA, and Unsgard G. Preoperative blood oxygenlevel-dependent functional magnetic resonance imaging in patients withprimary brain tumors: clinical application and outcome. Neurosurgery.2004,54(4):902–914.
    [9] Damoiseaux JS, Rombouts SA, Barkhof F, Scheltens P, Stam CJ, Smith SM,Beckmann CF. Consistent resting-state networks across healthy subjects.Proc Natl Acad Sci U S A.2006;103(37):13848–13853.
    [10] Petrella JR, Provenzale JM. MR perfusion Imaging of the brain: techniquesand applications. AJR Am J Roentgenol.2000;175(1):207–219.
    [11] Bendszus M, Warmuth-Metz M, Klein R, Burger R, Schichor C, Tonn JC,Solymosi L. MR spectroscopy in gliomatosis cerebri. AJNR Am JNeuroradiol.2000;21(2):375–380.
    [12] Chen Z, Li L, Sun J, Ma L. Mapping the brain in type II diabetes:Voxel-based morphometry using DARTEL. Eur J Radiol.2011May3.
    [13] Yassa MA, Stark CE. A quantitative evaluation of cross-participantregistration techniques for MRI studies of the medial temporal lobe.Neuroimage.2009;44(2):319–327.
    [14] Bergouignan L, Chupin M, Czechowska Y, Kinkingnéhun S, Lemogne C,Le Bastard G, Lepage M, Garnero L, Colliot O, Fossati P. Can voxel basedmorphometry, manual segmentation and automated segmentation equallydetect hippocampal volume differences in acute depression? Neuroimage.2009Mar1;45(1):29–37.
    [15] Song XW, Dong ZY, Long XY, Li SF, Zuo XN, Zhu CZ, He Y, Yan CG,Zang YF. REST: a toolkit for resting-state functional magnetic resonanceimaging data processing. PLoS One.2011;6(9):e25031.
    [16] Hou C, Liu J, Wang K, Li L, Liang M, He Z, Liu Y, Zhang Y, Li W, Jiang T.Brain responses to symptom provocation and trauma-related short-termmemory recall in coal mining accident survivors with acute severe PTSD.Brain Res.2007;1144:165–174
    [17] Bremner JD, Randall P, Scott TM, Bronen RA, Seibyl JP, Southwick SM,Delaney RC, McCarthy G, Charney DS, Innis RB. MRI-basedmeasurement of hippocampal volume in patients with combat-relatedposttraumatic stress disorder. Am J Psychiatry.1995;152(7):973–981.
    [18] Rogers MA, Yamasue H, Abe O, Yamada H, Ohtani T, Iwanami A, Aoki S,Kato N, Kasai K. Smaller amygdala volume and reduced anterior cingulategray matter density associated with history of post-traumatic stress disorder.Psychiatry Res.2009;174(3):210–216.
    [19] Woodward SH, Kaloupek DG, Streeter CC, Kimble MO, Reiss AL, Eliez S,Wald LL, Renshaw PF, Frederick BB, Lane B, Sheikh JI, Stegman WK,Kutter CJ, Stewart LP, Prestel RS, Arsenault NJ. Hippocampal volume,PTSD, and alcoholism in combat veterans. Am J Psychiatry.2006;163(4):674–681.
    [20] Chen S, Xia W, Li L, Liu J, He Z, Zhang Z, Yan L, Zhang J, Hu D. Graymatter density reduction in the insula in fire survivors with posttraumaticstress disorder: a voxel-based morphometric study. Psychiatry Res.2006;146(1):65–72.
    [21] Kasai K, Yamasue H, Gilbertson MW, Shenton ME, Rauch SL, Pitman RK.Evidence for acquired pregenual anterior cingulate gray matter loss from atwin study of combat-related posttraumatic stress disorder. Biol Psychiatry.2008;63(6):550–556.
    [22] De Bellis MD, Kuchibhatla M. Cerebellar volumes in pediatricmaltreatment-related posttraumatic stress disorder. Biol Psychiatry.2006;60(7):697–703.
    [23] Bremner JD, Randall P, Vermetten E, Staib L, Bronen RA, Mazure C,Capelli S, McCarthy G, Innis RB, Charney DS. Magnetic resonanceimaging-based measurement of hippocampal volume in posttraumaticstress disorder related to childhood physical and sexual abuse--apreliminary report. Biol Psychiatry.1997;41(1):23–32.
    [24] Yehuda R, Golier JA, Tischler L, Harvey PD, Newmark R, Yang RK,Buchsbaum MS. Hippocampal volume in aging combat veterans with andwithout post-traumatic stress disorder: relation to risk and resilience factors.J Psychiatr Res.2007;41(5):435–445.
    [25] Robinson BL, Shergill SS. Imaging in posttraumatic stress disorder. CurrOpin Psychiatry.2011;24(1):29–33.
    [26] Carrion VG, Weems CF, Eliez S, Patwardhan A, Brown W, Ray RD, ReissAL. Attenuation of frontal asymmetry in pediatric posttraumatic stressdisorder. Biol Psychiatry.2001;50(12):943–951.
    [27] Fennema-Notestine C, Stein MB, Kennedy CM, Archibald SL, Jernigan TL.Brain morphometry in female victims of intimate partner violence with andwithout posttraumatic stress disorder. Biol Psychiatry.2002;52(11):1089–1101.
    [28] Lerch JP. In-vivo analysis of cortical thickness using magnetic resonanceimages. Montreal, Canada: McGill University,2005.
    [29] Corbo V, Clément MH, Armony JL, Pruessner JC, Brunet A. Size versusshape differences: contrasting voxel-based and volumetric analyses of theanterior cingulate cortex in individuals with acute posttraumatic stressdisorder. Biol Psychiatry.2005;58(2):119–124.
    [30] Zhang J, Tan Q, Yin H, Zhang X, Huan Y, Tang L, Wang H, Xu J, Li L.Decreased gray matter volume in the left hippocampus and bilateralcalcarine cortex in coal mine flood disaster survivors with recent onsetPTSD. Psychiatry Res.2011;192(2):84–90.
    [31] Dickerson BC, Bakkour A, Salat DH, Feczko E, Pacheco J, Greve DN,Grodstein F, Wright CI, Blacker D, Rosas HD, Sperling RA, Atri A,Growdon JH, Hyman BT, Morris JC, Fischl B, Buckner RL. The corticalsignature of Alzheimer's disease: regionally specific cortical thinningrelates to symptom severity in very mild to mild AD dementia and isdetectable in asymptomatic amyloid-positive individuals. Cereb Cortex.2009;19(3):497–510.
    [32] Thompson PM, Lee AD, Dutton RA, Geaga JA, Hayashi KM, Eckert MA,Bellugi U, Galaburda AM, Korenberg JR, Mills DL, Toga AW, Reiss AL.Abnormal cortical complexity and thickness profiles mapped in Williamssyndrome. J Neurosci.2005;25(16):4146–4158.
    [33] Guerrini R, Marini C. Genetic malformations of cortical development. ExpBrain Res.2006;173(2):322–333.
    [34] Geuze E, Westenberg HG, Heinecke A, de Kloet CS, Goebel R, VermettenE. Thinner prefrontal cortex in veterans with posttraumatic stress disorder.Neuroimage.2008;41(3):675–681.
    [35] Landré L, Destrieux C, Baudry M, Barantin L, Cottier JP, Martineau J,Hommet C, Isingrini M, Belzung C, Gaillard P, Camus V, El Hage W.Preserved subcortical volumes and cortical thickness in women with sexualabuse-related PTSD. Psychiatry Res.2010;183(3):181–186.
    [36] Hutton C, De Vita E, Ashburner J, Deichmann R, Turner R. Voxel-basedcortical thickness measurements in MRI. Neuroimage.2008;40(4):1701–1710.
    [37] Jones SE, Buchbinder BR, Aharon I. Three-dimensional mapping ofcortical thickness using Laplace's equation. Hum Brain Mapp.2000;11(1):12–32.
    [38] Norris FH, Friedman MJ, Watson PJ, Byrne CM, Diaz E, Kaniasty K.60,000disaster victims speak: Part I. An empirical review of the empiricalliterature,1981-2001. Psychiatry.2002;65(3):207–239.
    [39] Winter H, Irle E. Hippocampal volume in adult burn patients with andwithout posttraumatic stress disorder. Am J Psychiatry.2004;161(12):2194–2200.
    [40] Nardo D, H gberg G, Looi JC, Larsson S, H llstr m T, Pagani M. Graymatter density in limbic and paralimbic cortices is associated with traumaload and EMDR outcome in PTSD patients. J Psychiatr Res.2010;44(7):477–485.
    [41] Petersen ET, Zimine I, Ho YC, Golay X. Non-invasive measurement ofperfusion: a critical review of arterial spin labelling techniques. Br J Radiol.2006;79(944):688–701.
    [42] Lanius RA, Bluhm R, Lanius U, Pain C. A review of neuroimaging studiesin PTSD: heterogeneity of response to symptom provocation. J PsychiatrRes.2006;40(8):709–729.
    [43] Schuff N, Zhang Y, Zhan W, Lenoci M, Ching C, Boreta L, Mueller SG,Wang Z, Marmar CR, Weiner MW, Neylan TC. Patterns of altered corticalperfusion and diminished subcortical integrity in posttraumatic stressdisorder: an MRI study. Neuroimage.2011;54(Suppl1):S62–S628.
    [44] Freeman TW, Cardwell D, Karson CN, Komoroski RA. In vivo protonmagnetic resonance spectroscopy of the medial temporal lobes of subjectswith combat-related posttraumatic stress disorder. Magn Reson Med.1998;40(1):66–71.
    [45] De Bellis MD, Keshavan MS, Spencer S, Hall J. N-Acetylaspartateconcentration in the anterior cingulate of maltreated children andadolescents with PTSD. Am J Psychiatry.2000;157(7):1175–1177.
    [46] Seedat S, Videen JS, Kennedy CM, Stein MB. Single voxel protonmagnetic resonance spectroscopy in women with and without intimatepartner violence-related posttraumatic stress disorder. Psychiatry Res.2005;139(3):249–258.
    [47] Shin LM, Whalen PJ, Pitman RK, Bush G, Macklin ML, Lasko NB, Orr SP,McInerney SC, Rauch SL. An fMRI study of anterior cingulate function inposttraumatic stress disorder. Biol Psychiatry.2001;50(12):932–942.
    [48] Geuze E, Vermetten E, de Kloet CS, Westenberg HG. Precuneal activityduring encoding in veterans with posttraumatic stress disorder. Prog BrainRes.2008;167:293–297.
    [49] Shin LM, Wright CI, Cannistraro PA, Wedig MM, McMullin K, Martis B,Macklin ML, Lasko NB, Cavanagh SR, Krangel TS, Orr SP, Pitman RK,Whalen PJ, Rauch SL. A functional magnetic resonance imaging study ofamygdala and medial prefrontal cortex responses to overtly presentedfearful faces in posttraumatic stress disorder. Arch Gen Psychiatry.2005;62(3):273–281.
    [50] Kim MJ, Lyoo IK, Kim SJ, Sim M, Kim N, Choi N, Jeong DU, Covell J,Renshaw PF. Disrupted white matter tract integrity of anterior cingulate intrauma survivors. Neuroreport.2005;16(10):1049–1053.
    [51] Abe O, Yamasue H, Kasai K, Yamada H, Aoki S, Iwanami A, Ohtani T,Masutani Y, Kato N, Ohtomo K. Voxel-based diffusion tensor analysisreveals aberrant anterior cingulum integrity in posttraumatic stress disorderdue to terrorism. Psychiatry Res.2006;146(3):231–242.
    [52] Lyons DM, Parker KJ, Zeitzer JM, Buckmaster CL, Schatzberg AF.Preliminary evidence that hippocampal volumes in monkeys predict stresslevels of adrenocorticotropic hormone. Biol Psychiatry.2007;62(10):1171–1174.
    [53] American Psychiatric Association. Diagnostic and Statistical Manual ofMental Disorders,4th edition. APA, Washington, DC.1994.
    [54] Spitzer B, Gibbon RL, Janet M, Janet W. Structured Clinical Interview forDSMIV Axis I Disorders-Patient Edition (SCID-I/P, version2.0). AmericanPsychiatric Press, New York.1996.
    [55] Wu KK, Chan SK. Psychometric properties of the Chinese version of theimpact of event scale—revised. Hong Kong J Psychiatry.2004;14(4):2–8.
    [56]吕彬,何晖光,赵明昌,吕科,张志强,卢光明.基于磁共振图像的脑皮层厚度测量方法.中国医学影像技术.2008;24(6):955-958.
    [57] Lohmann G, Preul C, Hund-Georgiadis M. Morphology-based corticalthickness estimation. Inf Process Med Imaging.2003;18:89–100.
    [58] Miller MI, Massie AB, Ratnanather JT, Botteron KN, Csernansky JG.Bayesian construction of geometrically based cortical thickness metrics.Neuroimage.2000;12(6):676–687.
    [59] McInerney T, Terzopoulos D. Deformable models in medical imageanalysis: a survey. Med Image Anal.1996;1(2):91–108.
    [60] Fischl B, Dale AM. Measuring the thickness of the human cerebral cortexfrom magnetic resonance images. Proc Natl Acad Sci U S A.2000;97(20):11050–11055.
    [61] Haidar H, Soul JS. Measurement of cortical thickness in3D brain MRIdata: validation of the Laplacian method. J Neuroimaging.2006;16(2):146–153.
    [62] Haidar H, Egorova VS, Soul JS. New numerical solution of the Laplaceequation for tissue thickness measurement in three-dimensional MRI. JMath Model Algorithms.2005;4(1):83–97.
    [63] Yezzi AJ Jr, Prince JL. An Eulerian PDE approach for computing tissuethickness. IEEE Trans Med Imaging2003;22(10):1332–1339.
    [64] Griffin LD. The intrinsic geometry of the cerebral cortex. J Theor Biol.1994;166(3):261–273.
    [65] Diep TM, Bourgeat P, Ourselin S. Efficient use of cerebral corticalthickness to correct brain MR segmentation. IEEE InternationalSymposium on Biomedical Imaging (ISBI).2007:592–595.
    [66] MacDonald D, Kabani N, Avis D, Evans AC. Automated3-D extraction ofinner and outer surfaces of cerebral cortex from MRI. Neuroimage.2000;12(3):340–356.
    [67] Salat DH, Buckner RL, Snyder AZ, Greve DN, Desikan RS, Busa E,Morris JC, Dale AM, Fischl B. Thinning of the cerebral cortex in aging.Cereb Cortex.2004;14(7):721–730.
    [68] Lancaster JL, Woldorff MG, Parsons LM, Liotti M, Freitas CS, Rainey L,Kochunov PV, Nickerson D, Mikiten SA, Fox PT. Automated Talairachatlas labels for functional brain mapping. Hum Brain Mapp.2000;10(3):120–131.
    [69] Hutton C, Draganski B, Ashburner J, Weiskopf N. A comparison betweenvoxel-based cortical thickness and voxel-based morphometry in normalaging. Neuroimage.2009;48(2):371–380.
    [70] Fjell AM, Westlye LT, Amlien I, Espeseth T, Reinvang I, Raz N, Agartz I,Salat DH, Greve DN, Fischl B, Dale AM, Walhovd KB. High consistencyof regional cortical thinning in aging across multiple samples. CerebCortex.2009;19(9):2001–2012.
    [71] Karama S, Colom R, Johnson W, Deary IJ, Haier R, Waber DP, Lepage C,Ganjavi H, Jung R, Evans AC; Brain Development Cooperative Group.Cortical thickness correlates of specific cognitive performance accountedfor by the general factor of intelligence in healthy children aged6to18.Neuroimage.2011;55(4):1443–1453.
    [72] Narr KL, Toga AW, Szeszko P, Thompson PM, Woods RP, Robinson D,Sevy S, Wang Y, Schrock K, Bilder RM. Cortical thinning in cingulate andoccipital cortices in first episode schizophrenia. Biol Psychiatry.2005;58(1):32–40.
    [73] Liberzon I, Taylor SF, Fig LM, Koeppe RA. Alteration of corticothalamicperfusion ratios during a PTSD flashback. Depress Anxiety.1996-1997;4(3):146–150.
    [74] Peres JF, Newberg AB, Mercante JP, Sim o M, Albuquerque VE, Peres MJ,Nasello AG. Cerebral blood flow changes during retrieval of traumaticmemories before and after psychotherapy: a SPECT study. Psychol Med.2007;37(10):1481–1491.
    [75] Taylor JG, Horwitz B, Shah NJ, Fellenz WA, Mueller-Gaertner HW, KrauseJB. Decomposing memory: functional assignments and brain traffic inpaired word associate learning. Neural Netw.2000;13(8-9):923–940.
    [76] Lanius RA, Williamson PC, Densmore M, Boksman K, Neufeld RW, GatiJS, Menon RS. The nature of traumatic memories: a4-T FMRI functionalconnectivity analysis. Am J Psychiatry.2004;161(1):36–44.
    [77] Molina ME, Isoardi R, Prado MN, Bentolila S. Basal cerebral glucosedistribution in long-term post-traumatic stress disorder. World J BiolPsychiatry.2010;11(2Pt2):493–501.
    [78] Woodward SH, Schaer M, Kaloupek DG, Cediel L, Eliez S. Smaller globaland regional cortical volume in combat-related posttraumatic stressdisorder. Arch Gen Psychiatry.2009;66(12):1373–1382.
    [79] Lanius RA, Williamson PC, Boksman K, Densmore M, Gupta M, NeufeldRW, Gati JS, Menon RS. Brain activation during script-driven imageryinduced dissociative responses in PTSD: a functional magnetic resonanceimaging investigation. Biol Psychiatry.2002;52(4):305–311.
    [80] Lanius RA, Williamson PC, Hopper J, Densmore M, Boksman K, GuptaMA, Neufeld RW, Gati JS, Menon RS. Recall of emotional states inposttraumatic stress disorder: an fMRI investigation. Biol Psychiatry.2003;53(3):204–210.
    [81] Squire LR. Memory and the hippocampus: a synthesis from findings withrats, monkeys, and humans. Psychol Rev.1992Apr;99(2):195–231.
    [82] Buckner RL, Head D, Parker J, Fotenos AF, Marcus D, Morris JC, SnyderAZ. A unified approach for morphometric and functional data analysis inyoung, old, and demented adults using automated atlas-based head sizenormalization: reliability and validation against manual measurement oftotal intracranial volume. Neuroimage.2004;23(2):724–738.
    [83] Epstein R, Kanwisher N. A cortical representation of the local visualenvironment. Nature.1998;392(6676):598–601.
    [84] Thomaes K, Dorrepaal E, Draijer NP, de Ruiter MB, Elzinga BM, vanBalkom AJ, Smoor PL, Smit J, Veltman DJ. Increased activation of the lefthippocampus region in Complex PTSD during encoding and recognition ofemotional words: a pilot study. Psychiatry Res.2009;171(1):44–53.
    [85] Gurvits TV, Shenton ME, Hokama H, Ohta H, Lasko NB, Gilbertson MW,Orr SP, Kikinis R, Jolesz FA, McCarley RW, Pitman RK.Magneticresonance imaging study of hippocampal volume in chronic, combat-related posttraumatic stress disorder. Biol Psychiatry.1996;40(11):1091–1099.
    [86] Lindauer RJ, Vlieger EJ, Jalink M, Olff M, Carlier IV, Majoie CB, denHeeten GJ, Gersons BP. Smaller hippocampal volume in Dutch policeofficers with posttraumatic stress disorder. Biol Psychiatry.2004;56(5):356–363.
    [87] Bremner JD, Vythilingam M, Vermetten E, Southwick SM, McGlashan T,Staib LH, Soufer R, Charney DS. Neural correlates of declarative memoryfor emotionally valenced words in women with posttraumatic stressdisorder related to early childhood sexual abuse. Biol Psychiatry.2003;53(10):879–889.
    [88] Wager TD, Hernandez L, Jonides J, Lindquist M. Elements of FunctionalNeuroimaging. In: Cacioppo JT, Tassinary LG, Berntson GG, editors.Handbook of psychophysiology,3rd edition. Cambridge, England:Cambridge University Press.2007;19–55.
    [89] O'Donoghue FJ, Briellmann RS, Rochford PD, Abbott DF, Pell GS, ChanCH, Tarquinio N, Jackson GD, Pierce RJ. Cerebral structural changes insevere obstructive sleep apnea. Am J Respir Crit Care Med.2005;171(10):1185–1190.
    [90] Wolf RL, Detre JA. Clinical neuroimaging using arterial spin-labeledperfusion magnetic resonance imaging. Neurotherapeutics.2007;4(3):346–359.
    [91] Kwong KK, Chesler DA, Weisskoff RM, Donahue KM, Davis TL,Ostergaard L, Campbell TA, Rosen BR. MR perfusion studies withT1-weighted echo planar imaging. Magn Reson Med.1995;34(6):878–887.
    [92] Paiva FF, Tannús A and Silva AC. Measurement of cerebral perfusionterritories using arterial spin labelling. NMR Biomed.2007;20(7):633–642.
    [93] Ye FQ, Mattay VS, Jezzard P, Frank JA, Weinberger DR, McLaughlin AC.Correction for vascular artifacts in cerebral blood flow values measured byusing arterial spin tagging techniques. Magn Reson Med.1997;37(2):226–235.
    [94] Asllani I, Borogovac A, Brown TR. Regression algorithm correcting forpartial volume effects in arterial spin labeling MRI. Magn Reson Med.2008;60(6):1362–1371.
    [95] Chappell MA, Groves AR, MacIntosh BJ, Donahue MJ, Jezzard P,Woolrich MW. Partial volume correction of multiple inversion time arterialspin labeling MRI data. Magn Reson Med.2011;65(4):1173–1183.
    [96] Li X, Li L, Lu H, and Liang Z. A Partial Volume Segmentation of BrainMagnetic Resonance Images Based on Maximum a Posteriori Probability,Medical Physics,2005,32(7):2337–2345.
    [97] Liang Z, Wang S. An EM approach to MAP solution of segmenting tissuemixtures: a numerical analysis. IEEE Trans Med Imaging.2009;28(2):297–310
    [98] Van Leemput K, Maes F, Vandermeulen D, Suetens P. A unifyingframework for partial volume segmentation of brain MR images. IEEETrans Med Imaging.2003;22(1):105–119.
    [99] Lei T, Sewchand W. Statistical approach to X-ray CT imaging and itsapplications in image analysis. I. Statistical analysis of X-ray CT imaging.IEEE Trans Med Imaging.1992;11(1):53–61.
    [100] Fuderer M. The information content of MR images. IEEE Trans MedImaging.1988;7(4):368–380.
    [101] Macovski A. Noise in MRI. Magn Reson Med.1996;36(3):494–497.
    [102] Geman S, Geman D. Stochastic relaxation, Gibbs distributions, and theBayesian restoration of images,” IEEE Trans Pattern Anal Mach Intell.1984;PAMI-6:721–741.
    [103] Liang Z, Li X, Eremina D, Li L. An EM framework for segmentation oftissue mixtures from medical images. Proc. Int. Conf. IEEE Eng. Med.Biol., Cancun, Mexico,2003;682–685.
    [104] Biagi L, Abbruzzese A, Bianchi MC, Alsop DC, Del Guerra A, Tosetti M.Age dependence of cerebral perfusion assessed by magnetic resonancecontinuous arterial spin labeling. J Magn Reson Imaging.2007;25(4):696–702.
    [105] Alsop DC, Detre JA. Reduced transit-time sensitivity in noninvasivemagnetic resonance imaging of human cerebral blood flow. J Cereb BloodFlow Metab.1996;16(6):1236–1249.
    [106] Wang J, Aguirre GK, Kimberg DY, Roc AC, Li L, Detre JA. Arterial spinlabeling perfusion fMRI with very low task frequency. Magn Reson Med.2003;49(5):796–802.
    [107] Wang J, Alsop DC, Li L, Listerud J, Gonzalez-At JB, Schnall MD, DetreJA. Comparison of quantitative perfusion imaging using arterial spinlabeling at1.5and4.0Tesla. Magn Reson Med.2002;48(2):242–254.
    [108] Kim SG, Hu X, U urbil K. Accurate T1determination from inversionrecovery images: application to human brain at4Tesla. Magn Reson Med.1994;31(4):445–449.
    [109] Cavu o lu M, Pfeuffer J, U urbil K, Uluda K. Comparison of pulsedarterial spin labeling encoding schemes and absolute perfusionquantification. Magn Reson Imaging.2009;27(8):1039–1045.
    [110] Lu H, Clingman C, Golay X, van Zijl PC. Determining the longitudinalrelaxation time (T1) of blood at3.0Tesla. Magn Reson Med.2004;52(3):679–682.
    [111] Herscovitch P, Raichle ME. What is the correct value for the brain--bloodpartition coefficient for water? J Cereb Blood Flow Metab.1985;5(1):65–69.
    [112] Asllani I, Borogovac A, Wright C, Sacco R, Brown TR, Zarahn E. Aninvestigation of statistical power for continuous arterial spin labelingimaging at1.5T. Neuroimage.2008;39(3):1246–1256.
    [113] Parkes LM, Rashid W, Chard DT, Tofts PS. Normal cerebral perfusionmeasurements using arterial spin labeling: reproducibility, stability, and ageand gender effects. Magn Reson Med.2004;51(4):736–743.
    [114]张煜,彭莹莹,陈国跃,陈武凡.脑血流、脑血容量、脑氧代谢率、氧摄取率受年龄影响分析.南方医科大学学报.2010;30(6):1237–1239.
    [115] Chen JJ, Rosas HD, Salat DH. Age-associated reductions in cerebral bloodflow are independent from regional atrophy. Neuroimage.2011;55(2):468–478.
    [116] Anzola GP, Gasparotti R, Magoni M, Prandini F. Transcranial Dopplersonography and magnetic resonance angiography in the assessment ofcollateral hemispheric flow in patients with carotid artery disease. Stroke.1995;26(2):214–217.
    [117] Isaac CL, Cushway D, Jones GV. Is posttraumatic stress disorder associatedwith specific deficits in episodic memory? Clin Psychol Rev.2006;26(8):939–95.
    [118] Carrion VG, Weems CF, Watson C, Eliez S, Menon V, Reiss AL.Converging evidence for abnormalities of the prefrontal cortex andevaluation of midsagittal structures in pediatric posttraumatic stressdisorder: an MRI study. Psychiatry Res.2009;172(3):226–234.
    [119] Karl A, Schaefer M, Malta LS, D rfel D, Rohleder N, Werner A. Ameta-analysis of structural brain abnormalities in PTSD. NeurosciBiobehav Rev.2006;30(7):1004–1031.
    [120]杨春兰,吴水才,白燕萍,侯彩兰,高宏建.基于体素的形态测量学方法用于创伤后应激障碍病人脑结构的研究.生物医学工程学杂志.2009;26(1):30–33.
    [121] Shin LM, McNally RJ, Kosslyn SM, Thompson WL, Rauch SL, Alpert NM,Metzger LJ, Lasko NB, Orr SP, Pitman RK. Regional cerebral blood flowduring script-driven imagery in childhood sexual abuse-related PTSD: APET investigation. Am J Psychiatry.1999;156(4):575-84.
    [122] Bremner JD, Staib LH, Kaloupek D, Southwick SM, Soufer R, Charney DS.Neural correlates of exposure to traumatic pictures and sound in Vietnamcombat veterans with and without posttraumatic stress disorder: a positronemission tomography study. Biol Psychiatry.1999;45(7):806–816.
    [123] Lanius RA, Williamson PC, Densmore M, Boksman K, Gupta MA,Neufeld RW, Gati JS, Menon RS. Neural correlates of traumatic memoriesin posttraumatic stress disorder: a functional MRI investigation. Am JPsychiatry.2001;158(11):1920–1902.
    [124] Osuch EA, Benson B, Geraci M, Podell D, Herscovitch P, McCann UD,Post RM. Regional cerebral blood flow correlated with flashback intensityin patients with posttraumatic stress disorder. Biol Psychiatry.2001;50(4):246–253.
    [125] Jiang H, van Zijl PC, Kim J, Pearlson GD, Mori S. DtiStudio: resourceprogram for diffusion tensor computation and fiber bundle tracking.Comput Methods Programs Biomed.2006;81(2):106–116.
    [126] De Bellis MD, Keshavan MS, Clark DB, Casey BJ, Giedd JN, Boring AM,Frustaci K, Ryan ND. A.E. Bennett Research Award. Developmentaltraumatology. Part II: Brain development. Biol Psychiatry.1999;45(10):1271–1284.
    [127] Filipovic BR, Djurovic B, Marinkovic S, Stijak L, Aksic M, Nikolic V,Starcevic A, Radonjic V. Volume changes of corpus striatum, thalamus,hippocampus and lateral ventricles in posttraumatic stress disorder (PTSD)patients suffering from headaches and without therapy. Cent Eur Neurosurg.2011;72(3):133–137.
    [128] Morey RA, Dolcos F, Petty CM, Cooper DA, Hayes JP, LaBar KS,McCarthy G. The role of trauma-related distractors on neural systems forworking memory and emotion processing in posttraumatic stress disorder. JPsychiatr Res.2009;43(8):809–817.
    [129] Rhodes G, Byatt G, Michie PT, Puce A. Is the fusiform face area specializedfor faces, individuation, or expert individuation? J Cogn Neurosci.2004;16(2):189–203.
    [130] Sui SG, Wu MX, King ME, Zhang Y, Ling L, Xu JM, Weng XC, Duan L,Shan BC, Li LJ. Abnormal grey matter in victims of rape with PTSD inMainland China: a voxel-based morphometry study. ActaNeuropsychiatrica.2010;22(3):118–126.
    [131]武瑞芝,张俊然,邱昌建,孟雅婧,朱鸿儒,龚启勇,黄晓琦,张伟.地震创伤后应激障碍患者脑静息态默认网络研究.四川大学学报:医学版.2011;42(3):397–400.
    [132] Bonne O, Gilboa A, Louzoun Y, Brandes D, Yona I, Lester H, Barkai G,Freedman N, Chisin R, Shalev AY. Resting regional cerebral perfusion inrecent posttraumatic stress disorder. Biol Psychiatry.2003;54(10):1077–1086.
    [133] De Bellis MD, Keshavan MS, Frustaci K, Shifflett H, Iyengar S, Beers SR,Hall J. Superior temporal gyrus volumes in maltreated children andadolescents with PTSD. Biol Psychiatry.2002;51(7):544–552.
    [134] Lindauer RJ, Booij J, Habraken JB, Uylings HB, Olff M, Carlier IV, denHeeten GJ, van Eck-Smit BL, Gersons BP. Cerebral blood flow changesduring script-driven imagery in police officers with posttraumatic stressdisorder. Biol Psychiatry.2004;56(11):853–861.
    [135] Hedges DW, Thatcher GW, Bennett PJ, Sood S, Paulson D, Creem-RegehrS, Brown BL, Allen S, Johnson J, Froelich B, Bigler ED. Brain integrityand cerebral atrophy in Vietnam combat veterans with and withoutposttraumatic stress disorder. Neurocase.2007;13(5):402–410.
    [136] Jackowski AP, Douglas-Palumberi H, Jackowski M, Win L, Schultz RT,Staib LW, Krystal JH, Kaufman J. Corpus callosum in maltreated childrenwith posttraumatic stress disorder: a diffusion tensor imaging study.Psychiatry Res.2008;162(3):256–261.
    [137] De Bellis MD, Keshavan MS, Shifflett H, Iyengar S, Beers SR, Hall J,Moritz G. Brain structures in pediatric maltreatment-related posttraumaticstress disorder: a sociodemographically matched study. Biol Psychiatry.2002;52(11):1066–1078.
    [138] Villarreal G, Hamilton DA, Graham DP, Driscoll I, Qualls C, Petropoulos H,Brooks WM. Reduced area of the corpus callosum in posttraumatic stressdisorder. Psychiatry Res.2004;131(3):227–235.
    [139] Teicher MH, Andersen SL, Polcari A, Anderson CM, Navalta CP.Developmental neurobiology of childhood stress and trauma. PsychiatrClin North Am.2002;25(2):397–426, vii-viii.
    [140] Ma N, Li L, Shu N, Liu J, Gong G, He Z, Li Z, Tan L, Stone WS, Zhang Z,Xu L, Jiang T. White matter abnormalities in first-episode, treatment-naiveyoung adults with major depressive disorder. Am J Psychiatry.2007;164(5):823–826.
    [141] Feng Z, Dong Y, Zhao Y, Bai S, Zhou B, Bi Y, Wu G. Computer-assistedtechnique for the design and manufacture of realistic facial prostheses. Br JOral Maxillofac Surg.2010;48(2):105–109.
    [142] Al Mardini M, Ercoli C, Graser GN. A technique to produce a mirror-imagewax pattern of an ear using rapid prototyping technology. J Prosthet Dent.2005;94(2):195–198.
    [143] Wu G, Bi Y, Zhou B, Zemnick C, Han Y, Kong L, Zhao Y. Computer-aideddesign and rapid manufacture of an orbital prosthesis. Int J Prosthodont.2009;22(3):293–295.
    [144] Ciocca L, Bacci G, Mingucci R, Scotti R. CAD-CAM construction of aprovisional nasal prosthesis after ablative tumour surgery of the nose: apilot case report. Eur J Cancer Care (Engl).2009;18(1):97–101.
    [145] Kitware Inc. The VTK User’s Guide.(KitwareInc, Prentice-Hall:2002).

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