Detecting structural changes in whole brain based on nonlinear deformations - Application to schizophrenia research
Detecting structural changes in whole brain based on nonlinear deformations - Application to schizophrenia research
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DOI：
10.1006/nimg.1999.0458
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发表时间：
1999-08-01
期刊：
影响因子：
5.7
通讯作者：
Sauer, H
中科院分区：
文献类型：
--
作者：
Gaser, C;Volz, HP;Sauer, H
提出了一种基于形变场分析的脑结构差异检测方法。通过基于强度的非线性配准程序将一个大脑转换为另一个大脑来获得变形。我们提出了一个通用的多元统计方法来分析不同学科的形变场。这种方法被应用于85例精神分裂症患者和75名健康志愿者的大脑，以检查低频变形是否足够敏感，以检测两组大脑中的区域偏差。我们观察到显着的变化所造成的体积减少精神分裂症患者的大脑双侧丘脑和上级颞回。左侧额上级回和中央前回改变，右侧额中回改变。此外，枕叶（左舌回）和左侧小脑也有显著变化。精神分裂症患者的脑体积增大，在右侧壳核和丘脑区域的相邻白色物质中观察到。我们的数据表明，在前额叶-丘脑-小脑电路的节点的干扰。这进一步支持了“认知辨距障碍”模型，该模型假设这些节点发生了中断。我们已经通过检测整个大脑的结构变化证明了基于变形的形态测量学的应用。该技术是全自动的，因此允许包含大样本，没有用户偏见或优先定义的感兴趣区域。(C)北京：科学出版社.
This paper describes a new method for detecting structural brain differences based on the analysis of deformation fields. Deformations are obtained by an intensity-based nonlinear registration routine that transforms one brain onto another one. We present a general multivariate statistical approach to analyze deformation fields in different subjects. This method was applied to the brains of 85 schizophrenic: patients and 75 healthy volunteers to examine whether low frequency deformations are sufficiently sensitive to detect regional deviations in the brains of both groups. We observed significant changes caused by volume reduction in brains of schizophrenics bilaterally in the thalamus and in the superior temporal gyrus. On the left side, the superior frontal gyrus and precentral gyrus are found to be changed, while on the right side, the middle frontal gyrus was altered. In addition, there were significant changes in the occipital lobe (left lingual gyrus) and in the left cerebellum. Volume enlargement in brains of schizophrenics was observed in the right putamen and in the adjacent white matter of the thalamic region. Our data suggest a disturbance in the nodes of a prefrontal-thalamic-cerebellar circuitry. This provides further support for the model of "cognitive dysmetria," which postulates a disruption in these nodes. We have demonstrated the application of deformation-based morphometry by detecting structural changes in the whole brain. This technique is fully automatic, thus allowing for the inclusion of large samples, with no user bias or a priori-defined regions of interest. (C) 1999 Academic Press.