Name: how to measure cortical folding from mr images: a step-by-step tutorial to compute local gyrification index
Uploaded: 2012-01-02T13:00:00
Description: Watch this Scientific Journal Video about How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index at JoVE.com

这项研究得到了能力的国家研究中心（NCCR）“SYNAPSY - 精神疾病的突触基地”由瑞士国家科学基金会（N ° 51AU40_125759）的资助。从瑞士国家研究基金玛丽Schaer（323500-111165）博士和博士史蒂芬Eliez（3200-063135.00 / / 1，1，3232-063134.00 PP0033 - 102864和32473B的赠款支持发展本地Gyrification指数-121996）和中心在日内瓦的洛桑大学的生物医学成像（CIBM），洛桑联邦理工学院，以及基础Leenaards和Louis - Jeantet。 FreeSurfer软件的发展提供了支持部分由国家研究资源中心（P41 - RR14075，并BIRN002 NCRR BIRN形态项目，U24 RR021382），国家生物医学成像和生物工程研究所（R01 EB001550 ，R01EB006758）美国国家神经紊乱和中风研究所（R01 ñS052585 - 01）以及精神疾病和神经科学发现（心）研究所，是全国医学影像计算联盟（NAMIC）由国立卫生研究院的资助，通过国立卫生研究院医学研究路线图，格兰特U54，的一部分EB005149。埃利森医学基金会资助自闭症及读写障碍项目提供额外的支持。

1。重建3D皮质表面这个协议的第一部分使用的标准 FreeSurfer管道，在<a href="http://surfer.nmr.mgh.harvard.edu/fswiki">Wiki</a> （http://surfer.nmr.mgh.harvard.edu/fswiki ）。请注意，在这里详细的命令说明实现皮层表面重建的方法之一，但也可以使用等效命令。 <ol class="lalpha"><li>导入FreeSurfer原始MRI DICOM和验证的图像质量（例如，方向是正确的，足够的对比度和图像不移动） 。此过...

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协议上面介绍了如何衡量当地Gyrification指数基于对脑T1加权MRI和进行统计组比较。我们的方法已被专门设计的本地化皮质膨胀过程中的早期中断，因此许多神经发育或精神状况特别感兴趣。在临床样本组比较的例子，可以发现在出版物， 由本集团1,12 或由他人13-16。这个过程是完全自动化的，只需要命令要执行，虽然两个参数可以修改。 第一次修改的参数是<em...

材质：与UNIX或Mac工作站的2GHz或更快的处理器和4GB的RAM最低FreeSurfer安装（ <a href="http://surfer.nmr.mgh.harvard.edu/fswiki">http://surfer.nmr.mgh.harvard.edu/fswiki</a> ，最好是最新版本，但年龄不比版本4.0.3）。 MATLAB是为了计算的本地Gyrification指数，还需要（ <a href="http://www.mathworks.ch/">http://www.mathworks.com/</a> ）随着图像处理工具箱。 数据：质量好的样品（高清晰度，高对比度）脑MRI T1加权数据集。您的受试者必须是最好的年龄和性别相匹配。由于个体间正常的脑形态的变化，各组的科目数应足以识别现有的组间差异（更 - 更好）。一个合理的最低样本大小将大约20名受试者每个组（虽然你也许可以少走，如果强度变化大，如果你的团体紧密性别和年龄相匹配）。 <table border="1"><tbody><tr><td> 设备名称 </td><td> 公司 </td><td> 目录编号 </td><td> 评论 </td></tr><tr><td> FreeSurfer </td><td>麻省总医院生物医学成像，Martinos中心</td><td></td><td>比4.0.3版本更新</td></tr><tr><td> MATLAB </td><td> Mathworks公司</td><td></td><td>图像处理工具箱</td></tr></tbody></table>

how to measure cortical folding from mr images: a step-by-step tutorial to compute local gyrification index

皮质折叠（gyrification）确定在生命的最初几个月，因此，在此期间发生的不良事件留下的痕迹，将在任何年龄识别。最近审查Mangin和同事2，存在的几种方法，以量化gyrification的不同特点。例如，可用于脑沟形态学如半球间的深度，长度或指数来衡量的形状描述不对称 3 。这些几何特性的优点是易于理解。然而，脑沟形态学紧紧依靠准确识别一个给定的沟，因此提供了一个支离破碎的gyrification描述。基于曲率的测量，其中平滑的绝对平均曲率通常是在皮质表面4千点计算，可以实现更细粒度的gyrification量化。曲率，但不straightforward来理解，因为它仍不清楚，如果curvedness一个生物学意义的关联，如皮质体积或表面之间有任何直接关系。为了解决测量皮质折叠提出的各种问题，我们以前开发了一种算法，量化当地gyrification一个精致的空间分辨率和简单的解释。我们的方法是启发Gyrification指数5，原本比较神经解剖学方法，用于评估跨物种的皮质折叠差异。在我们的实现，我们名升 ocal Gyrification指数（GI 1 升 ），我们衡量皮质金额埋脑沟皱褶内可见皮质的圆形区域的利益金额相比。由于皮层的增长主要是通过径向膨胀 6，我们的方法是专门设计，以确定皮质发育的早期缺陷。 在日是一篇文章中，我们详细介绍当地Gyrification指数的计算，这是目前作为 FreeSurfer软件的一部分（ <a href="http://surfer.nmr.mgh.harvard.edu/">自由</a>分布http://surfer.nmr.mgh.harvard.edu/，Martinos生物医学成像中心，马萨诸塞州总医院） 。FreeSurfer提供了一套大脑的皮质表面结构MRI数据自动重建工具。在本土与亚毫米级精度的图像空间中提取的皮质表面，然后再用于创造的外表面，这将作为一个为 l GI计算的基础上。利益的一个圆形区域，然后划定的外表面，并使用验证研究 1所述的匹配算法确定其相应区域的皮质表面上的兴趣。这个过程反复迭代很大程度上是重叠的地区利益，gyrification皮质地图ř随后的统计比较（图1）。值得注意的是，另一个地方gyrification的测量提出了类似的灵感托罗和他的同事 7，皮质区的光盘领域的划分与同一个领域中的比例计算，在每个点的折叠指数半径。这两种实现方式的不同，一个由红牛等。是基于欧几里德距离，因此认为皮质区的不连续的补丁，而我们采用了严格的测地线算法和只包括皮质区开放利益的一个圆形区域的脑表面连续补丁。

Watch this Scientific Journal Video about How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index at JoVE.com

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

（皮质折叠）在任何年龄的测量gyrification代表到早期的大脑发育的窗口。因此，我们以前开发了一种算法来衡量当地gyrification千点以上的半球<sup&gt; 1</sup&gt;。在本文中，我们详细介绍这个地方gyrification指数的计算。

如何从MR图像测量皮质折叠：一个循序渐进的教程，以计算本地Gyrification指数

Cortical folding (gyrification) is determined during the first months of life, so that adverse events occurring during this period leave traces that will ...

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