超声观察胎儿大脑沟回发育及其临床意义

目的 探讨产前超声检测胎儿大脑沟回的发育过程及其临床意义.方法 经腹部超声观测692例孕19～39周胎儿大脑沟回(顶枕沟、距状沟、中央沟、扣带沟、扣带回、大脑外侧裂)发生、发展并测量其深度.结果 顶枕沟、距状沟、大脑外侧裂在19周左右可显示.中央沟在25周左右可显示.扣带沟、扣带回在26周左右可显示.1例24周胎儿顶枕沟、大脑外侧裂未见发育,考虑脑沟回发育迟缓;2例29周胎儿顶枕沟、中央沟末见发育,外侧裂发育呈圆钝状、深度变浅,考虑为脑沟凹发育迟缓.各大脑沟问深度与孕周均呈正相关(均P<0.05),各大脑沟回相对深度与孕周均呈负相关(均P<0.05).结论 经腹超声可观测到胎儿大脑沟回(顶枕沟、距状沟、中央沟、扣带回、大脑外侧裂)发生、发展,其深度与孕周相关,为产前早期评估大脑沟回发育异常如大脑发育迟缓、无脑回病提供依据.     

表面髋关节置换三维有限元模型的建立及意义

背景:目前髋关节的三维有限元模型大都是基于人体尸骨数据或通过CAD重建获得的,其效果不够理想.目的:通过64排螺旋CT扫描提供数据,建立表面髋关节置换的三维有限无模型,拟为生物力学实验提供标准数学模型.方法;选择1名行表面髋关节置换后的成年男性志愿者,经X射线检查排除健侧髋关节疾患.螺旋CT扫描表面髋关节置换后患者所得数据导入Mimics软件.采用域值法建立三维立体模型,之后导入Abaqus软件,进行网格划分.建立起表面髋关节置换术后的三维有限元模型.结果与结论:建立了表面髋关节置换术后三维几何和有限元模型.表面髋关节置换模型分为三维六面体单元165 886个,节点213 343个.可见,通过Mimics软件、Abaqus软件可以利用表面髋关节置换术后患者薄层断面图像构建出其三维几何模型与三维有限元模型.该模型具有较高的形态学及力学仿真度.     

动脉粥样硬化模型动物脑血管的拉伸力学特性

背景:脑动脉粥样硬化和脑出血的防治有必要了解正常和动脑粥样硬化模型大鼠大脑中动脉的力学特性,但以往的研究对象多为正常人尸体与正常动物脑动脉的力学特性.目的:比较正常和动脉粥样硬化动物模型大脑中动脉的拉伸力学特性.方法:SD大鼠随机分为正常对照组和模型组.模型组大鼠建立动脉粥样硬化模型.取2组大鼠的大脑中动脉以电子万能试验机对其进行5 mm/min拉伸载荷实验,观察2组大鼠脑动脉最大载荷、最大位移、最大应力以及最大应变差异及血管应力-应变关系.结果与结论:动脉粥样硬化大鼠脑动脉血管拉伸最大载荷、最大应力、最大位移及最大应变均较正常大鼠明显降低(P<0.05),大鼠脑动脉血管应力-应变曲线是以指数关系变化的.因此,说明动脉粥样硬化模型大鼠大脑中动脉和正常对照组大鼠大脑中动脉具有不同的拉伸力学特性,脑动脉粥样硬化大鼠动脉血管不能像正常大鼠脑血管一样再作较大的伸展.     

双频超声对大网膜结核的诊断价值

目的 :探讨大网膜结核的声像图表现 ,以提高结核性腹膜炎的超声诊断水平。方法 :用低频和高频超声对 43例经病理证实的大网膜结核患者网膜回声特点进行观察。结果 :1.大网膜结核内部回声可以分为 3种类型 :高回声型、高低回声间杂型 (高频超声呈“大脑沟回”状 )、结节型 ,其中“大脑沟回”状改变为大网膜结核的特征性声像图表现 ;2 .对大网膜病变内部回声的观察 ,高频超声明显优于低频超声。结论 :高频超声检查有助于大网膜结核的诊断     

股骨骨折髓内钉置入内固定后1年骨愈合有限元模型的快速建立

背景：当前判断内固定取出后正常站立情况下股骨是否断裂仅依靠X射线或CT数据。 目的：通过有限元方法对股骨骨折髓内钉置入内固定1年取出内固定后的骨愈合模型进行分析,探讨该方法是否能判定内固定取出后骨折断端断裂。 方法：运用Mimics、Geomagic Studio、Abaqus等软件采用快速个体化建模方法对股骨骨折髓内钉置入内固定1年取出内固定后的骨愈合多层螺旋CT数据进行模型快速建立,并采取4种方法处理模型,分别为不作模型简化;对骨愈合区以外的模型表面网格给予50%简化;对骨愈合区以外的模型表面网格给予20%简化;对骨愈合区以外的模型表面网格给予10%简化。对于以上4种模型进行有限元分析,施加3,9倍重力载荷和约束,观察米赛斯应力最大值及其所处部位。 结果与结论：按照材料属性进行区别显示米赛斯应力的最大值及最小值,在不同应力载荷下,术后各类型材料的米赛斯应力最大值及最小值部位相同,各类型材料中,最大值均未位于骨折断端,不同方法的最大应力值部位相近,均在中远端1/4交界处,其中表面网格简化10%模型的数值偏倚小,网格处理、材料赋值及有限元分析运算时间最短。采用适当的个体化建模方法可以对骨折内固定取出后的骨折模型进行有限元分析,快速判断内固定取出是否导致骨折断端断裂。     

基于CT图像构建的腰椎三维有限元模型

背景:与实验生物力学研究相比,有限元分析方法具有独特的优越性。如何准确地构建腰椎节段有限元模型是有限元分析的关键。目的:建立人体腰椎三维有限元模型用于生物力学分析。方法:利用GE64排螺旋CT对成年男性腰部进行扫描,得到351层DICOM格式断层图像,应用Mimics软件进行三维重建,将所得模型以.stl格式导入Solidworks,生成实体模型,最后导入Ansys赋予材料属性并划分网格,得到便于分析的有限元模型。与体外生物力学实验数据对比,完成模型验证。结果与结论:成功地建立了表面光滑、外观逼真的腰椎有限元模型。该模型共有144411个节点,88742个单元,具有较高的准确性,且可以方便地施加约束和载荷,进行有限元分析。为临床腰椎三维有限元模型建立提供了一种精确而实用的方法,所建模型可以用来模拟腰椎生物力学实验。     

7.0T静息态fMRI分析恒河猴脑默认网络

目的 分析健康恒河猴大脑的默认网络（DMN）结构。方法 采用7.0T fMRI获得麻醉状态下健康恒河猴的静息态数据;以DPARSF软件包对猴脑静息态功能像进行预处理,将其配准到恒河猴标准模板112SM-RL-T1;之后利用GIFT软件包对预处理后的功能像数据进行组独立成分分析。结果 本文方法可较准确地对猴脑静息态数据进行预处理,并获得静息态脑网络功能连接图;其中DMN包括位于中线区的后扣带回、前扣带回、内侧顶叶皮质、后压部皮质以及大脑左右半球较为对称的腹侧壁内区域、背侧颞上沟回、颞区、弓状沟回及部分视觉区域等脑区。结论 借助7.0T fMRI,本文证实恒河猴默认网络与人类默认网络在结构上具有相似性,此类模型可辅助进行药理性实验研究以及神经认知类研究。     

基于MRI图像的主动脉分割与三维建模

目的基于MRI图像序列建立主动脉的三维几何模型并进行计算网格的划分,以用于主动脉血流动力学特性的模拟。方法采用心电R波触发和呼吸控制的方式在体扫描得到心动周期20个时相760幅MRI图像,利用Mimics软件对所获取的图像序列进行图像预处理、分割和三维重建,然后将所建立的三维模型导入到ADINA软件中进行计算网格的划分。结果建立了20个主动脉三维模型,分别代表主动脉在心动周期不同时相的状态,同时,还实现了计算网格的划分。结论该方法可得到进行主动脉血流动力学仿真所需的三维几何模型和计算网格;同时,该方法也可用于人体其他组织的三维建模和网格划分。     

大脑新皮质发育的影像学研究进展

大脑新皮质（cerebral cortex）发育过程较为复杂，包括神经元细胞的增殖和移行、突触建立及大脑沟回形成等几个相互重叠的过程。以往组织学观察为大脑新皮质的主要研究方法，因此人们对大脑新皮质发育并无直观及清晰的认识；随着影像诊断技术的发展，影像学与组织学己成为大脑新皮质发育研究的重要方法。     

基于DICOM数据构建股骨三维有限元模型的精确力学分析☆

背景：有限元模型已经由二维发展到三维,由线性模型发展到非线性,由于该方法在分析不太规则物体的力学特点方面具有优越性,因此在骨科生物力学研究特别是髋关节方面得到广泛应用。目的：利用有限元方法分析人体股骨在载荷下的受力状态,探索一种快速建立股骨有限元模型并能进行精确力学分析的方法。方法：选择标准成年男性志愿者行股骨CT扫描成像,得到股骨每层横截面图像,应用DICOM数据和MIMICS软件行三维重建,结合有限元分析软件ABQUS 6.8构建股骨三维有限元模型,并分析股骨模型载荷状态下的应力分布。结果与结论：结果显示,基于DICOM数据建立的股骨三维有限元模型,划分网格后形成38636个节点,201422个单元,其中包括股骨松质骨体网格模型与皮质骨体网格模型。有限元分析结果与以往的实验数据一致性较好,能够客观实际地反映股骨真实解剖形态和生物力学行为,分析精度较高。提示运用Mimics软件提供了简单有效的建模方法,极大程度上提高了建模效率,基于 DICOM 数据的三维有限元模型几何形状较准确,可以为股骨正常力学行为研究提供精确模型。利用ABQUS 6.8分析得到的应力分布情况与临床观察一致。     

Resolution of complex tissue microarchitecture using the diffusion orientation transform (DOT)

This article describes an accurate and fast method for fiber orientation mapping using multidirectional diffusion-weighted magnetic resonance (MR) data. This novel approach utilizes the Fourier transform relationship between the water displacement probabilities and diffusion-attenuated MR signal expressed in spherical coordinates. The radial part of the Fourier integral is evaluated analytically under the assumption that MR signal attenuates exponentially. The values of the resulting functions are evaluated at a fixed distance away from the origin. The spherical harmonic transform of these functions yields the Laplace series coefficients of the probabilities on a sphere of fixed radius. Alternatively, probability values can be computed nonparametrically using Legendre polynomials. Orientation maps calculated from excised rat nervous tissue data demonstrate this technique's ability to accurately resolve crossing fibers in anatomical regions such as the optic chiasm. This proposed methodology has a trivial extension to multiexponential diffusion-weighted signal decay. The developed methods will improve the reliability of tractography schemes and may make it possible to correctly identify the neural connections between functionally connected regions of the nervous system.     

Experimentation with a transcranial magnetic stimulation system for functional brain mapping

We describe functional brain mapping experiments using a transcranial magnetic stimulation (TMS) device. This device, when placed on a subject's scalp, stimulates the underlying neurons by generating focused magnetic field pulses. A brain mapping is then generated by measuring responses of different motor and sensory functions to this stimulation. The key process in generating this mapping is the association of the 3-D positions and orientations of the TMS probe on the scalp to a 3-D brain reconstruction such as is feasible with a magnetic resonance image (MRI). We have developed a registration system which not only generates functional brain maps using such a device, but also provides real-time feedback to guide the technician in placing the probe at appropriate points on the head to achieve the desired map resolution. Functional areas we have mapped are the motor and visual cortex. Validation experiments focus on repeatability tests for mapping the same subjects several times. Applications of the technique include neuroanatomy research, surgical planning and guidance, treatment and disease monitoring, and therapeutic procedures.     

BrainSuite: an automated cortical surface identification tool

We describe a new magnetic resonance (MR) image analysis tool that produces cortical surface representations with spherical topology from MR images of the human brain. The tool provides a sequence of low-level operations in a single package that can produce accurate brain segmentations in clinical time. The tools include skull and scalp removal, image nonuniformity compensation, voxel-based tissue classification, topological correction, rendering, and editing functions. The collection of tools is designed to require minimal user interaction to produce cortical representations. In this paper we describe the theory of each stage of the cortical surface identification process. We then present classification validation results using real and phantom data. We also present a study of interoperator variability.     

Accurate prediction of V1 location from cortical folds in a surface coordinate system

Previous studies demonstrated substantial variability of the location of primary visual cortex (V1) in stereotaxic coordinates when linear volume-based registration is used to match volumetric image intensities [Amunts, K., Malikovic, A., Mohlberg, H., Schormann, T., and Zilles, K. (2000). Brodmann's areas 17 and 18 brought into stereotaxic space-where and how variable? Neuroimage, 11(1):66-84]. However, other qualitative reports of V1 location [Smith, G. (1904). The morphology of the occipital region of the cerebral hemisphere in man and the apes. Anatomischer Anzeiger, 24:436-451; Stensaas, S.S., Eddington, D.K., and Dobelle, W.H. (1974). The topography and variability of the primary visual cortex in man. J Neurosurg, 40(6):747-755; Rademacher, J., Caviness, V.S., Steinmetz, H., and Galaburda, A.M. (1993). Topographical variation of the human primary cortices: implications for neuroimaging, brain mapping, and neurobiology. Cereb Cortex, 3(4):313-329] suggested a consistent relationship between V1 and the surrounding cortical folds. Here, the relationship between folds and the location of V1 is quantified using surface-based analysis to generate a probabilistic atlas of human V1. High-resolution (about 200 microm) magnetic resonance imaging (MRI) at 7 T of ex vivo human cerebral hemispheres allowed identification of the full area via the stria of Gennari: a myeloarchitectonic feature specific to V1. Separate, whole-brain scans were acquired using MRI at 1.5 T to allow segmentation and mesh reconstruction of the cortical gray matter. For each individual, V1 was manually identified in the high-resolution volume and projected onto the cortical surface. Surface-based intersubject registration [Fischl, B., Sereno, M.I., Tootell, R.B., and Dale, A.M. (1999b). High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum Brain Mapp, 8(4):272-84] was performed to align the primary cortical folds of individual hemispheres to those of a reference template representing the average folding pattern. An atlas of V1 location was constructed by computing the probability of V1 inclusion for each cortical location in the template space. This probabilistic atlas of V1 exhibits low prediction error compared to previous V1 probabilistic atlases built in volumetric coordinates. The increased predictability observed under surface-based registration suggests that the location of V1 is more accurately predicted by the cortical folds than by the shape of the brain embedded in the volume of the skull. In addition, the high quality of this atlas provides direct evidence that surface-based intersubject registration methods are superior to volume-based methods at superimposing functional areas of cortex and therefore are better suited to support multisubject averaging for functional imaging experiments targeting the cerebral cortex.     

Focused ultrasound modulates region-specific brain activity

We demonstrated the in vivo feasibility of using focused ultrasound (FUS) to transiently modulate (through either stimulation or suppression) the function of regional brain tissue in rabbits. FUS was delivered in a train of pulses at low acoustic energy, far below the cavitation threshold, to the animal's somatomotor and visual areas, as guided by anatomical and functional information from magnetic resonance imaging (MRI). The temporary alterations in the brain function affected by the sonication were characterized by both electrophysiological recordings and functional brain mapping achieved through the use of functional MRI (fMRI). The modulatory effects were bimodal, whereby the brain activity could either be stimulated or selectively suppressed. Histological analysis of the excised brain tissue after the sonication demonstrated that the FUS did not elicit any tissue damages. Unlike transcranial magnetic stimulation, FUS can be applied to deep structures in the brain with greater spatial precision. Transient modulation of brain function using image-guided and anatomically-targeted FUS would enable the investigation of functional connectivity between brain regions and will eventually lead to a better understanding of localized brain functions. It is anticipated that the use of this technology will have an impact on brain research and may offer novel therapeutic interventions in various neurological conditions and psychiatric disorders.     

Finding parametric representations of the cortical sulci using an active contour model

The cortical sulci are brain structures resembling thin convoluted ribbons embedded in three dimensions. The importance of the sulci lies primarily in their relation to the cytoarchitectonic and functional organization of the underlying cortex and in their utilization as features in non-rigid registration methods. This paper presents a methodology for extracting parametric representations of the cerebral sulci from magnetic resonance images. The proposed methodology is based on deformable models utilizing characteristics of the cortical shape. Specifically, a parametric representation of a sulcus is determined by the motion of an active contour along the medial surface of the corresponding cortical fold. The active contour is initialized along the outer boundary of the brain and deforms toward the deep root of a sulcus under the influence of an external force field, restricting it to lie along the medial surface of the particular cortical fold. A parametric representation of the medial surface of the sulcus is obtained as the active contour traverses the sulcus. Based on the first fundamental form of this representation, the location and degree of an interruption of a sulcus can be readily quantified; based on its second fundamental form, shape properties of the sulcus can be determined. This methodology is tested on magnetic resonance images and it is applied to three medical imaging problems: quantitative morphological analysis of the central sulcus; mapping of functional activation along the primary motor cortex and non-rigid registration of brain images.     

Sparse linear regression for reconstructing muscle activity from human cortical fMRI

In humans, it is generally not possible to use invasive techniques in order to identify brain activity corresponding to activity of individual muscles. Further, it is believed that the spatial resolution of non-invasive brain imaging modalities is not sufficient to isolate neural activity related to individual muscles. However, this study shows that it is possible to reconstruct muscle activity from functional magnetic resonance imaging (fMRI). We simultaneously recorded surface electromyography (EMG) from two antagonist muscles and motor cortices activity using fMRI, during an isometric task requiring both reciprocal activation and co-activation of the wrist muscles. Bayesian sparse regression was used to identify the parameters of a linear mapping from the fMRI activity in areas 4 (M1) and 6 (pre-motor, SMA) to EMG, and to reconstruct muscle activity in an independent test data set. The mapping obtained by the sparse regression algorithm showed significantly better generalization than those obtained from algorithms commonly used in decoding, i.e., support vector machine and least square regression. The two voxel sets corresponding to the activity of the antagonist muscles were intermingled but disjoint. They were distributed over a wide area of pre-motor cortex and M1 and not limited to regions generally associated with wrist control. These results show that brain activity measured by fMRI in humans can be used to predict individual muscle activity through Bayesian linear models, and that our algorithm provides a novel and non-invasive tool to investigate the brain mechanisms involved in motor control and learning in humans.     

Robust parametrization of brain surface meshes

Complex shapes - such as the surface of the human brain - may be represented and analyzed in frequency space by means of a spherical harmonics transformation. A key step of the processing chain is introducing a suitable parametrization of the triangular mesh representing the brain surface. This problem corresponds to mapping a surface of topological genus zero on a unit sphere. An algorithm is described that produces an optimal combination of an area- and angle-preserving mapping. A multi-resolution scheme provides the robustness required to map the highly detailed and convoluted brain surface. More than 1000 datasets were successfully processed by this mature and robust approach.     

Functional MRI in the brain tumor patient

Functional magnetic resonance imaging (fMRI) has been adopted almost universally by disciplines that endeavor to understand how the brain works. As basic scientists tune the technique, clinicians are increasingly able to apply brain mapping with fMRI to their clinical practice. We present here a guide to using fMRI in a clinical setting. We discuss the basic considerations of functional brain mapping in patients with brain tumors including: patient screening and training, paradigm design, data analysis and interpretation of the fMRI scans.