Name: high-resolution in vivo manual segmentation protocol for human hippocampal subfields using 3t magnetic resonance imaging
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Description: Watch this Scientific Journal Video about High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging at JoVE.com

笔者想从CAMH基金会的认可支持，感谢迈克尔和宋佳柯纳的Kimel家庭，和保罗·加芬克尔新研究员催化剂奖。该项目资金由全宗德RECHERCHES桑特魁北克健康研究加拿大学院（CIHR），自然科学和加拿大，韦斯顿脑研究所，加拿大阿尔茨海默氏症协会工程研究理事会，和迈克尔J. Fox基金会帕金森病研究（MMC），以及CIHR，安大略省精神卫生基金会，NARSAD和心理健康国家研究所（R01MH099167）（ANV）。作者还要感谢Anusha Ravichandran寻求帮助获取图像。

研究参与者 （; 29-57岁，平均37。3楼，2M）谁是自由的神经和神经精神障碍和重度​​颅脑外伤的情况下在这个手稿的协议，从健康志愿者采集的五个有代表性的高清晰度图像的开发。所有受试者入组，在该中心的成瘾和精神健康（CAMH）。这项研究是由CAMH研究伦理委员会，并符合赫尔辛基宣言进行。提供书面所有受试者知情同意进行数据采集和共享。有关用于收集这些图像采集序列的详细信息，请参阅温特伯恩等人 ，2013年和公园等，2014年26,34图片全部五科进行了检查质量和保留。海马在这些图像平均118冠状切片跨越。 1.软件设置<ol><li> 打开显示: </str翁&gt;从终端​​使用以下命令:显示image_name.mnc -label label_name.mnc。该程序将打开窗户3:三维可视化窗口，3-取向图像观察窗，和一个导航窗口。该终端也将用于运行程序。放大的冠状面，因为分割将冠进行。放大的海马。在导航窗口中选择F（分段）。选择F（XY半径:0.1）。在终端窗口会提示用户"输入XY画笔大小"。设置为0.1。这将设置你的画笔的大小。用户现在可以开始了海马绘制到MR图像。 </li></ol> 2.整个海马手动分割<ol><li> 设置:使用T1加权像，滚动到海马的最前冠状切片。为了推进切片的前方向，用"+"键;用&#39; - &#39;键在后方向上移动。 </li><li><strong&gt;的切片答:最前片:用鼠标右键单击，画的海马灰质在那里遇到周围颞叶白质最外层的边界，并使用alveus的高强度的白质以协助上缘，其中所述海马满足杏仁核12,22。使用E（标签填充）键在导航窗口中的分段菜单，以填补在边境内侧的标签。继续在整个前海马头应用这些边界。 </li><li> 切片B:海马头1（图1B）: <ol><li>上，下，外侧，内侧边框:继续绘制边框如步骤2.2中所述，使用颞叶和alveus为指导的白质。 </li><li> Supero-内侧缘:对于这一点，使用轴向图，画一条水平线从横向海马29的前部边缘，包括下面这条线作为海马什么。注:supero-内侧缘成为这些片，其中海马的灰​​质融合与杏仁核的灰质比较模糊。 </li></ol></li><li> 切片C:海马头2齿状:根据不同的主题，海马齿状可能是3-4片可见（通常情况下，他们是在T2加权相对于T1加权像更明显）。在这些切片，继续使用alveus和颞叶白质，引导边界分割12,22。有关详细信息，按照步骤2.5.1-2.5.2。 </li><li> 片D:海马头3: <ol><li>上，下，外侧，内侧边框:绘制海马的下缘在颞叶，在侧脑室，上缘的下角外侧缘的白质，继齿状的曲线，在白质的alveus /伞，而内侧缘在低信号区域选择性n个环池12,22的。 </li><li> Supero-内侧和infero-内侧边界:继续定义supero，内侧缘如步骤2.3.2描述。绘制内侧缘所在的海马变薄略，并延伸到内嗅皮层12,22的轻度高信号灰质的下部。 </li></ol></li><li> 片E:海马头4钩回:继续绘制步骤2.5.1-2.5.2描述下，横向和优越的边界。包括钩回（位于游戏币向海马的主体，并且由低强度CSF包围）在海马分割12,2 2。 </li><li> 片F:海马体:继续绘制步骤2.5.1-2.5.2描述下，外侧，内侧，和优越的边界。绘制infero，内侧缘处，其中海马变薄，因为它转换到内嗅皮质/准海马回12,22点。不要在分割的残留海马沟的低强度CSF。 </li><li> 切片G:海马尾1:开始分割海马尾型切片时，穹窿的小腿是第一个可见。通过外推束状回的捏成从更前片12,22海马尾排除在分割的束状回（一灰质结构融合与海马尾部分海马）。此外推是唯一可能为2-3片，之后，两个结构不能准确分辨;在这一点上，对待这地区如海马所有可见灰质。 </li><li> 切片H:海马尾2:段从周边高强度的白质后的海马尾部的低强度的灰质。 </li><li> 切片我:最靠后的切片:段海马灰质从小其余区域周围白质的颞叶。 </li></ol> 3.海马子字段手动分割<ol><li> 设置:使用T2加权图像，滚动到海马的最前冠状切片（如在步骤2.1）。要改变画笔的颜色，选择D（设置在导航窗口中的分割菜单上涂料的Lbl :)。该命令终端将提示:"请输入当前绘制的标签:"。输入一个数字255 1至每个号对应于不同的标签的颜色。 </li><li> 切片答:最前片:由于子部门都在最前片还没有看到，画线分割沿其最长可见轴可见海马灰质（这不一定平行于任何基本轴）成两个相等的部分，以接近真实的解剖12,22。标签上级这两部分的CA1区和下部分为下脚由choosi纳克不同颜色的标签，每个子23,35。 </li><li> 切片B:海马负责人1:海马结构为SR / SL / SM 13,37的中间标签的低烈度区。当沿着海马的下部边缘的弯曲变得清晰，使用这一具有里程碑意义从CA1 12,22分离下托的外侧缘。继续按照海马的最长轴绘制CA1，下托边境上的supero-内侧尖37。 </li><li> 切片C:海马头2齿状: <ol><li> SR / SL / SM，CA4 / DG和下托:标签的SR / SL / SM，CA4 / DG和所描述的片D下脚（步骤3.5.1）。 </li><li> CA2 / CA3和CA1:定义CA1和CA2 / CA3之间的边界为从发SR / SL / SM 12,22的最supero -外侧边缘在supero -横向方向延伸的45度角线。内侧沿上边缘延伸CA2 / CA3到登塔之间的槽系统蒸发散12,22。标签上缘为CA1 12,22的其余部分。 </li></ol></li><li> 片D:海马头3 <ol><li> SR / SL / SM，CA4 / DG和下托:第一个标签黑暗SR / SL / SM频段，这将遵循CA1 37的曲线。标签的SR / SL / SM为CA4 / DG 12,22,23,35,37内部的任何高强度的灰质。这可能不是连续的区域，如图2C所示。继续使用弯曲的劣势海马12,22定义下托-CA1边界。 </li><li> CA2 / CA3和​​CA1:继续定义CA1和CA2 / CA3边界按步骤3.4.2。延长CA2 / CA3内侧中途沿着海马12,22的上边缘和标签上缘的另一半作为CA1 12,22。 </li><li> Supero-内侧的海马头:在这片，垂直划分supero-内侧的海马头的一半。标签内侧一半SR / SL / SM 12。除以横向一半一半，这一次水平。标签上级部分为CA4 / DG和下部分为CA2 / CA3 12。 </li></ol></li><li> 片E:海马头4钩回 <ol><li>外侧海马头（下托）:在这些片的侧部，定义下托-CA1边框，从最内侧缘CA4 / DG 12,22在上下方向延伸的垂直线。 </li><li>横向海马头（CA1，CA2 / CA3，CA4 / DG，SR / SL / SM）:定义以同样的方式在CA1-CA2 / CA3边界的步骤3.4.2。继续按照CA区域的曲线SR / SL / SM标注为低强度区域。标记CA4 / DG称为SR / SL / SM内的中心腔中，如在步骤3.5.1。 </li><li> UNCAL海马头（SR / SL / SM）:标签海马钩回约10片作为海马头部过渡到海马体。在钩回，标号低强度区的中心SR / SL / SM（若这是很难看，通过分割线2-3的体素宽向上的中心钩回的）12近似解剖学。 </li><li> UNCAL海马头（CA2 / CA3，CA4 / DG）:画线的SR / SL / SM沿钩回的infero侧向/ supero-中轴部分的上边缘。标签上面这条线CA2 / CA3 12所有灰质。标签下面这条线（在SR / SL / SM的两侧）为CA4 / DG 12任何未标记的灰质。 </li></ol></li><li> 片F:海马体:继续申请步骤3.6.1-3.6.2描述的边界。 </li><li> 切片G:海马尾1:继续申请步骤3.6.1-3.6.2描述的规则。下托-CA1边界成为从内侧缘CA4 / DG 12,22的infero-内侧方向延伸的45度角行。 </li><li> 片H:海马尾2:一旦束状回中不再能够从海马formatio区分N，标签的整个外层CA1区，此的SR / SL内的低强度区/ SM（如在以前的切片），和任何剩余的灰质在中间CA4 / DG 12,22。 </li><li> 切片我:最靠后的切片:一旦黑暗SR / SL / SM是海马结构的中心不再可见，标签，整个结构CA1 12,22。 </li></ol> 4，协议的可靠性<ol><li>从执行最初分割等待约一个月之后再分割或右侧每个受试者的左海马。段一直以来，海马的整个前后长度的子场，试图按照协议规定的一致是可能的。 </li><li>计算原始和resegmented卷之间的骰子的河童: <img alt="式（1）" src="/files/ftp_upload/51861/51861eq1.jpg" /> 其中k =骰子的κ和A和B的标签卷。 </li></ol>

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The authors have no conflicts of interest to declare.

在MR图像海马子分割很好的体现在文献中。但是，现有的协议排除的海马20,23,33,35部，仅适用于定影图像37，或要求超高场扫描仪进行图像采集35,37。这个手稿提供一个分割协议，它包括海马五个主要分部（CA1，CA2 / CA3，CA4 /齿状回，SR / SL / SM，并下托），并跨越结构的整个前 - 后长度。完整的分段地图集可在公众网上（cobralab.ca/atlases/Hippocampus）来。这项工作是适用于神经影像学领域中的许多组，将有助于限制某些海马子分割现有的不符点。 该协议的可靠性测试显示了高度的原件和resegmented标签之间空间重叠，这反映了高内信度的（表2）。 0.91对整个海马κ值为媲美文献报道的35,37其他值。许多子场的帧内评价者可靠性也与其他类似的分割协议比较好;然而，某些结构具有较低的可靠性。这25,33,35,37可以是包括将SR / SL / SM子场本协议，其中其它基团不这样做，这导致相邻的子场中（下托，CA1的结果，和CA2 / CA3）更薄，因而受到骰子的卡伯指标33,35更重的处罚。此外，在该协议中使用的复检处理也许是更严格的，因此更反射比所使用的那些其它基团真协议的可靠性。每个科目一个半球的整个前-后长度resegmented，而其他群体具有较高的可靠性段只有少数冠状切片23,33,37 .The子场最低卡帕（0.64）是CA2 / CA3，这是一种小而薄的结构。先前已表明是帧内评价者误差为在这个协议中的所有子场比在每一个主方向的模拟0.3毫米的平移误差，或标签34的一个模拟1％膨胀/收缩更高。换句话说，手动重新分段误差比引入小的系统误差，它支持的协议的高手册重复性小。 专家评估者手册，详细研究每个五高分辨率图像，以确定哪些目前迪韦尔诺瓦中的组织学子场可以看出12。它被确定，这是不能够可靠区分从CA3的CA2，所以增加协议的可靠性，将它们组合成一个结构。这条规则遵循以前的组33,37的先例。它也不可能从分子层区分CA4，颗粒层，并且在图像中的齿状回的多晶层，或齿状回层本身之间进行区分。因此，CA4和所有齿状回层合并成一个标签（CA4 / DG）。还有就是，事实上，海马子分割的社区辩论的CA4区域是否应该被认为是大角ammonis的一部分，与12迪韦尔诺瓦，或齿状回中的一部分，与阿马拉尔3。在这个手稿中提出的方法，可同时对这些意见，并遵循以往的MR细分群体23,28,33,35,37的工作。地层radiatum，腔隙，和moleculare的大角ammonis也不能分开区分的，所以被组合成一个标签，与以前的组37。 神经解剖学的最准确的分析是通过组织学切片和染色，但这种类型的分析，从若干问题遭受:LIMI泰德访问固定试样（这导致非常小的样本大小）;准备样品所需的专业知识;固定后大脑的扭曲;并且在施加固定图谱到数字， 体内数据 1,2,8的困难。在离体成像 ，固定脑在MR ​​扫描器长采集时间还提供神经解剖学的详细照片，但与组织学，样本数目是有限的和有固定和体内脑37。 体内 MR之间形态的差异成像具有有限的分辨率，但呈现的可能性更大的样本大小，以及用于成像在多个时间点的单一主体的潜力。通过延长采集时间在标准磁场强度扫描器（的受试者舒适的范围内），详细地在体内图像可用的电平变为足以解决子结构级别神经解剖学。用于图像赛格收购mented在这个协议中，因此提供了样品的可用性和图像分辨率之间的合理平衡。 这个协议是用于高分辨率的MR图像，如那些用于说明在本手稿26,34的协议的步骤开发的。分别通过取长的扫描时间和图像平均优势获取上一个3T扫描器高分辨率图像。的总扫描时间为两个FSPGR-BRAVO和FSE-CUBE收购一起略低于2小时。人们认识到，这是一个令人望而却步扫描长度为临床应用:进行这里为了说明的目的对分割协议此序列。作者认为在这个手稿中描述的分割协议可适于图像以较短的扫描时间，例如一个单个3T采集（而不是3收购为每个反衬类型，所使用的温特等人，2013 34和Park等人，2014年26 </SUP&gt;）或7T图像。即使有稍低的分辨率，许多在协议的规则仍然会CA1和CA2 / CA3之间适用，如那些使用一个几何的做法（例如45°角线;垂直线从中间边缘CA4 / DG的分开下托和CA1海马体）。其它规则将也许必须适应（例如它可能无法区分的SR / SL / SM，在这种情况下，它可以被包括作为CA的一部分子场）。此外，先前已被表明高分辨率图谱 ​​可以使用自动化分割管道7,27被应用于分辨率较低的图象。 该协议被设计为与上健康受试者的图像实现的，但也可以应用于（手动或使用自动分割管线7,16,27），以患病人群的图像，如阿尔茨海默氏病的病人，对他们来说，严重萎缩使得海马特定的结构兴趣。5,30尽管如此萎缩，周围海马和强度对比图像中的地标，则意味着该分割协议仍然会基本上是可行的。然而，这样的临床图像可能会被收购上的扫描器具有低得多的场强，如1.5T，其中该分辨率会太低，以便能够看到子结构。 用于执行分割的软件的类型是相关的，因为它是能够看从多个视点（即，冠状，矢状，轴向）的结构的重要意义。另外，利用结构的表面的三维可视化的可以用来平滑海马的总体拓扑结构。常犯错误像素或不合逻辑的形状不会很明显在2 dimensionsal基本的飞机，但将在3D表面很清楚。高清晰度的图像，该协议适用于约118冠状切片，并要求40小时禾以上每个受试者RK由先前培训的专家手工评价者。这一数额体力劳动的全协议的适用范围限制在一个大的主题集。这将有可能实现该协议作为节省时间的度量的修改后的版本:例如，每隔一个冠状切片可被分段，以提供子场体积的估计，或者子场可以合并，例如所有大角ammonis子场（ CA1，CA2 / CA3和​​SR / SL / SM）。 总之，本手稿呈现的详细说明书分割协议为整个海马和五个子场海马（CA1，CA2 / CA3，CA4 /齿状回，地层radiatum /腔隙/ moleculare，和下托）。该协议已经被应用到五科，并且地图集已提供公开（cobralab.ca/atlases/Hippocampus）。这些地图集让有兴趣的海马分割其他实验室对执行海马子字段的可靠，可重复的分割新的图像数据集。

海马是与情节记忆，空间导航和其他认知功能10,31相关联的广泛研究的内侧颞叶结构。其在神经变性和神经精神障碍，如阿尔茨海默氏症，精神分裂症和双相情感障碍的作用是证据充分的4,5,18,24,30。本手稿的目标是提供额外的细节，以对在3T获得高分辨率磁共振（MR）图像对人海马子场察看34出版的手册分割协议。此外，视频分量随本手稿将提供给研究者谁希望实现自己的数据集的协议进一步的帮助。 海马可以基于观察到的在组织学制备的验尸cytoarchitectonic差异分为子场标本12,22。这种事后的标本定义GROU次为识别和海马子区研究真理。然而这种性质的制剂需要专门的技术和设备进行染色，并且通过固定的组织的可用性是有限的，尤其是在患病人群在体内成像具有主体大得多池的优点，并且还提供了机会为后续后续研究和人群观察变化。虽然它已被证明在T2加权体外的MR图像，信号强度反映蜂窝密度13，它仍然是难以确定仅仅使用MR信号强度的子场之间的无可争议的边界。因此，已经开发了许多不同的方法用于识别MR图像组织学级别的细节。 一些团体努力重建和数字化组织的数据集，然后用这些重建以及图像配准技术本地化海马子neuroanatOMY 在体内 MR 1,2,8,9,14,15,17,32。虽然这是一个有效的技术映射一个版本的病理基础事实直接到MR图像，这种性质的重建都难以完成。的项目，如这些是由完整的内侧颞叶标本，组织学技术，组织学处理期间的数据丢失，并固定和体内大脑之间的基本形态的不一致的可用性的限制。其他团体已使用高场扫描仪（7T或9.4T），以努力获得在体内或离体的影像具有足够小（0.20-0.35毫米各向同性）的体素尺寸的可视化空间定位，用于在图像对比度的差异推断子区35,37之间的界限。即使在7T-9.4T和用这样一个小的体素尺寸，海马子场cytoarchitectonic特征是不可见的。这样，手动分段协议已经开发了一pproximate对MR图像已知的组织界限。这些协议通过解释本地图像对比度的差异并限定几何规则（如直线和角），相对于可见光的结构确定的子场边界。虽然在高场强拍摄的图像能够提供详细的洞察海马子场，高场扫描仪是尚未在临床或研究设置常见，因此7T和9.4T协议目前具有有限的适用性。类似的协议已被开发用于收集在3T和4T扫描器11,20,21,23,24,25,28,33图像。许多这些协议是基于与在冠状面子1毫米体素的体素的尺寸的图像，但具有大的切片厚度（0.8-3毫米）11,20,21,23,25,28,33或大间切片的距离20,28，这两个导致各个子场的体积的估计中一个显著测量偏差。另外，许多现有的3T的协议排除的子场中的所有海马头部或尾部20,23,25,33的全部或部分，或不提供的重要子结构（即，结合 DG与CA2 / CA3或不包括地层radiatum /腔隙/ moleculare详细分割在CA）11,20,21,23,24,25,28,33。因此，有必要在该领域的协议，可以可靠地在整个头部，身体和海马的尾部是基于在临床和研究设置通常可获得的一个扫描器确定相关子场的详细描述。努力目前由海马子区组（www.hippocampalsubfields.com）正在进行协调实验室之间海马子场分割过程，类似于现有的协调工作对整个海马分割6，以及比较21的现有协议的初始纸最近发表38 。从这个小组的工作将进一步阐明最佳分割PROCE的既定程序。 这份手稿提供了详细的书面和视频指令的可靠实现高分辨率3T磁共振成像被温特和他的同事34前面所述的海马子分段协议。该协议对整个海马五个图像健康对照组和五个海马子字段（CA1，CA2 / CA3，CA4 /齿状回，地层radiatum /腔隙/ moleculare和下脚）得到落实。这些分割的图像都可以在公网上（cobralab.ca/atlases/Hippocampus）来。该协议与划分图像将是谁希望学习详细的海马神经解剖学磁共振图像组非常有用。

<table><tbody><tr><td>Discovery MR750 3T</td><td>GE</td><td></td><td>Or equivalent 3T scanner</td></tr><tr><td>Minc Tool Kit</td><td>McConnell Brain Imaging Center, Montreal Neurological Institute</td><td></td><td>Open source: http://www.bic.mni.mcgill.ca/ServicesSoftware/ServicesSoftwareMincToolKit</td></tr></tbody></table>

high-resolution in vivo manual segmentation protocol for human hippocampal subfields using 3t magnetic resonance imaging

人类海马已被广泛研究了记忆和正常脑功能及其在不同的神经精神疾病作用方面一直在大力研究。虽然许多成像研究治疗海马为单一神经解剖结构，它是，在实际上，有一个复杂的三维几何形状的几个子场组成。因此，它是已知的，这些子场执行专门的功能，并通过不同的疾病状态的过程中差异的影响。磁共振（MR）成像，可作为一种强大的工具来询问海马和其子场的形态。许多集团利用先进的成像软件和硬件（&gt; 3T），以图像的子场;然而这种类型的技术可能不是在大多数研究和临床成像中心容易获得。为了满足这一需求，该手稿提供了一个详细的一步一步的协议分割全前后长度CORNU ammonis（CA）1，CA2 / CA3，CA4 /齿状回（DG），地层radiatum /腔隙/ moleculare（SR / SL / SM）和下脚:海马及其子区。该协议已经被应用到五个主题（3F，2M; 29-57岁，平均37）。协议的可靠性是由再分割或右侧每个受试者的左海马和计算使用骰子的卡伯度量重叠评估。平均骰子的卡帕（范围）在五个主题是:整海马，0.91（0.90-0.92）; CA1，0.78（0.77-0.79）; CA2 / CA3，0.64（0.56-0.73）; CA4 /齿状回，0.83（0.81-0.85）;地层radiatum /腔隙/ moleculare，0.71（0.68-0.73）;和下托0.75（0.72-0.78）。这里提出的分割协议提供其他实验室与研究使用常用的MR工具海马和海马子场体内的可靠方法。

。结果从协议可靠性测试总结于表2对于整个双侧海马，平均空间交叠由骰子的卡伯测定为0.91和0.90的范围内- 0.92。子场卡伯值范围为0.64（CA2 / CA3）至0.83（CA4 /齿状回）。平均体积为所有子场和整个海马列于表3中。卷在整个海马范围从2456.72-3325.02毫米3。该CA2 / CA3是最小的子场在208.33毫米3，而CA1是最大的857.46毫米3。 <img alt="图1" src="/files/ftp_upload/51861/51861fig1.jpg" /> 图1.细分整个海马使用T1加权像9冠状切片（AI）的，在海马表面垂直红线说明每个冠状切片的位置。海马是存在于一个在每个五科118冠状切片verage纳入本研究。图片来自前（切片1）在底部的顶到后（片118）的进展。图像显示在左边的列没有分割，并与分割在右列。比例尺显示了3个毫米参考。罗马数字指向协议稿件确定的具体功能。一世。该alveus区分在最前片杏仁核的灰质海马灰质。二。颞叶白质定义海马头部海马的下缘。三。海马头部海马外侧缘是侧脑室下角。四。优越的边框是由alveus /伞的白质定义。诉海马头的内侧缘是环池。六。所述infero-内侧海马伸入内嗅皮质，其显示为一个轻度超激烈乐队在T1加权像。七。海马的钩回存在于海马头，可以很容易从周围CSF区分。八。在infero-内侧方向，下托和准海马回之间的边界是由海马灰质轻微变薄定义。九。的残留海马沟的脑脊液中不包含分割。的X.束状回中不包括在海马尾部分割时也能够区分开。十一。当它不再是可能的束状回和海马尾部来区分，束状回包括在分割。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/51861/51861fig1large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图2" src="/files/ftp_upload/51861/51861fig2.jpg" /> 图2。■海马子字段使用T2加权图像9冠状切片（AI）的egmentation。在海马表面垂直红线说明每个冠状切片的位置。海马是存在于每一个包含在该研究中的五个受试者的平均118个冠状切片。图片来自前（切片1）在底部的顶到后（片118）的进展。图像显示在左边的列没有分割，并与分割在右列。比例尺显示了3个毫米参考。罗马数字指向协议稿件确定的具体功能。一世。在海马头的中心的低强度区是将SR / SL / SM。二。在海马infero - 外侧边缘UNCAL形弯曲标志着CA1和下托之间的边界。三。下托-CA1边境继续在劣质海马海马头&#39;弯&#39;进行定义。四。 CA1和之间的边界CA2 / CA3被定义为在从对SR / SL / SM的最supero - 外侧边缘supero - 横向方向延伸的45°角。诉CA2 / CA3延伸中途沿着海马的上边缘，该齿状的槽，内侧其所标记为CA1。六。灰质海马头的中心被标记为CA4 / DG。七。继续定义CA1〜CA2 / CA3边界作为在从SR / SL / SM的最supero - 外侧边缘supero - 横向方向延伸的45°角。八。所述CA2 / CA3继续沿着海马的上边缘中途延伸，内侧其所标记为CA1。九。在片D中，supero-内侧的海马头分为子字段（见步骤3.5.3）。的X.下托-CA1边界被定义为从CA4 / DG的最内侧缘延伸的垂直线。十一。发SR / SL / SM仍然是低强度区以下在CA区域的曲线。十二。海马头的UNCAL部分，发SR / SL / SM是在钩回中心的低强度区域。如果这个都看不出来，再接2-3个像素宽了钩回的中心。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/51861/51861fig2large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> 表1.上，下，内侧，和海马子场用于沿着海马。边框的前-后长度9代表切片侧向边 ​​界被描述为T2加权的图像。 WM =白质; GM =灰质; MTL =内侧颞叶。 <table><tbody><tr><td> 结构体 </td><td> 一片 </td><td> 上缘 </td><td> 下缘 </td><td> 内侧缘 </td><td> 外侧缘 </td></tr> &lt;TR&gt; <td rowspan="13"> CA1 </td><td>最前片</td><td>在alveus的WM </td><td>中线海马灰质，沿长轴（边框下脚） </td><td>在alveus的WM </td><td>在alveus的WM </td></tr><tr><td>海马头1 </td><td>在alveus的WM </td><td> SR / SL / SM;在海马的&#39;弯&#39;与下脚下侧壁边界</td><td>在alveus的WM </td><td>在alveus的WM </td></tr><tr><td>海马头2（带齿状） </td><td></td><td></td><td></td><td></td></tr><tr><td>侧向</td><td>遵循SR / SL / SM的曲线;与CA2 / CA3 supero，外侧缘</td><td>在MTL的WM </td><td> SR / SL / SM;与下托内下方，在海马的&#39;弯&#39; </td><td>在alveus的WM </td></tr><tr><td>内侧</td><td> WM的alveus的;与CA2 / CA3 supero，内侧缘</td><td>低强度SR / SL / SM </td><td>低-intensity SR / SL / SM </td><td> CA2 / CA3 </td></tr><tr><td>海马头3 </td><td></td><td></td><td></td><td></td></tr><tr><td>侧向</td><td>遵循SR / SL / SM的曲线;与CA2 / CA3 supero，外侧缘</td><td>在MTL的WM </td><td> SR / SL / SM;与下托内下方，在海马的&#39;弯&#39; </td><td>在alveus的WM </td></tr><tr><td>内侧</td><td> WM的alveus的;与CA2 / CA3 supero，内侧缘</td><td>低强度SR / SL / SM </td><td>低强度SR / SL / SM </td><td> CA2 / CA3 </td></tr><tr><td>海马头部4（有钩回） </td><td>遵循SR / SL / SM的曲线;与CA2 / CA3 supero，外侧缘</td><td>在MTL的WM </td><td> SR / SL / SM;沿内侧缘CA4 / DG的下脚垂直线内下方边框</td><td>在alveus的WM </td></tr><tr><td>海马体</td><td>遵循SR / SL / SM的曲线; supero-外侧缘机智^ h CA2 / CA3 </td><td>在MTL的WM </td><td> SR / SL / SM;沿内侧缘CA4 / DG的下脚垂直线内下方边框</td><td>在alveus的WM </td></tr><tr><td>海马尾1 </td><td> SR / SL / SM;与CA2 / CA3 superolateral边界</td><td>在MTL的WM </td><td>遵循SR / SL / SM的曲线; supero中层边境沿线平行下托以CA4 / DG的边缘</td><td>在alveus的WM </td></tr><tr><td>海马尾2 </td><td>与alveus /伞的WM Supero，外侧缘</td><td>在MTL的WM </td><td>在MTL的WM </td><td>在MTL的WM </td></tr><tr><td>最靠后的切片</td><td>与alveus /伞的WM Supero，外侧缘</td><td>结构的其余由颞叶的WM镶上</td><td>在MTL的WM </td><td>在alveus /伞的WM </td></tr><tr><td rowspan="9">下脚</td><td>最前片</td><td>中线河马campal灰质，沿长轴（边界CA1） </td><td>在MTL的WM </td><td>在alveus的WM </td><td>在alveus的WM </td></tr><tr><td>海马头1 </td><td> SR / SL / SM; CA1在supero，内侧缘</td><td>在MTL的WM </td><td>在alveus的WM </td><td> CA1，在海马&#39;弯&#39; </td></tr><tr><td>海马头2（带齿状） </td><td> SR / SL / SM </td><td>在MTL的WM </td><td>内嗅皮层（低强度区内侧劣质海马） </td><td> CA1，在海马&#39;弯&#39; </td></tr><tr><td>海马头3 </td><td> SR / SL / SM </td><td>在MTL的WM </td><td>内嗅皮层（低强度区内侧劣质海马） </td><td> CA1，在海马&#39;弯&#39; </td></tr><tr><td>海马头部4（有钩回） </td><td>在环池脑脊液</td><td> WM的MTL的;在嗅皮层infero-内侧缘，其中皮质变薄带SLIghtly和信号强度下降</td><td>在环池脑脊液</td><td>沿线平行CA1至CA4 / DG的边缘</td></tr><tr><td>海马体</td><td>在环池脑脊液</td><td> WM的MTL的;在嗅皮层，其中皮质带稍微变薄和信号强度下降infero，内侧缘</td><td>在环池脑脊液</td><td>沿线平行CA1至CA4 / DG的边缘</td></tr><tr><td>海马尾1 </td><td>束状回的GM（其中可以从海马GM分开） </td><td>在MTL的WM </td><td>难以确定;从更前/后片外推</td><td>沿线平行CA1至CA4 / DG的边缘</td></tr><tr><td>海马尾2 </td><td colspan="4"> NA </td></tr><tr><td>最靠后的切片</td><td colspan="4"> NA </td></tr><tr><td rowspan="15"> CA2 / CA3 </td><td>最前片</td><td colspan="4"> NA </td></tr><tr&gt; <td>海马头1 </td><td colspan="4"> NA </td></tr><tr><td>海马头2（带齿状） </td><td></td><td></td><td></td><td></td></tr><tr><td>侧向</td><td>在alveus的WM </td><td>低强度SR / SL / SM </td><td> CA1半路沿海马的上缘;如果齿状可见，尽量估计一半</td><td>沿45°角CA1从SR / SL / SM的最supero外侧边缘Infero，外侧缘</td></tr><tr><td>内侧</td><td> CA4 / DG半路沿海马superiorinferior延伸</td><td> CA1在海马上 - 下扩展基础</td><td> SR / SL / SM半路沿宽度海马优越劣扩展</td><td> alveus的WM </td></tr><tr><td>海马头3 </td><td></td><td></td><td></td><td></td></tr><tr><td>侧向</td><td>在alveus的WM </td><td>低强度SR / SL / SM </td><td> CA1半路沿海马的上缘</td><td>沿45°角CA1从SR / SL / SM的最supero外侧边缘Infero，外侧缘</td></tr><tr><td>内侧</td><td> CA4 / DG半路沿海马superiorinferior延伸</td><td> CA1在海马上 - 下扩展基础</td><td> SR / SL / SM半路沿宽度海马优越劣扩展</td><td> alveus的WM </td></tr><tr><td>海马头部4（有钩回） </td><td></td><td></td><td></td><td></td></tr><tr><td>侧向</td><td>在alveus的WM </td><td> CA4 / DG </td><td>在环池脑脊液</td><td>沿45°角CA1从SR / SL / SM的最supero外侧边缘Infero，外侧缘</td></tr><tr><td>内侧</td><td>在环池脑脊液</td><td>线平行于SR / SL / SM的上缘</td><td>在环池脑脊液</td><td>在环池脑脊液</td></tr><tr><td> Hippocampal体</td><td>在alveus的WM </td><td> CA4 / DG </td><td>在环池脑脊液</td><td>沿45°角CA1从SR / SL / SM的最supero外侧边缘Infero，外侧缘</td></tr><tr><td>海马尾1 </td><td>在alveus的WM </td><td>下缘水平线SR / SL / SM的最外侧点，下面的更前片的模式延伸;与CA4 / DG内下方边框</td><td>伞端的WM </td><td>伞端的WM </td></tr><tr><td>海马尾2 </td><td colspan="4"> NA </td></tr><tr><td>最靠后的切片</td><td colspan="4"> NA </td></tr><tr><td rowspan="15"> CA4 / DG </td><td>最前片</td><td colspan="4"> NA </td></tr><tr><td>海马头1 </td><td colspan="4"> NA </td></tr><tr><td>海马头2（带齿状） </td><td>跟随低强度的SR / SL / SM曲线</td><td>低强度SR / SL / SM </td><td>在环池脑脊液</td><td>低强度SR / SL / SM </td></tr><tr><td>侧向</td><td>低强度SR / SL / SM </td><td>低强度SR / SL / SM </td><td>在环池脑脊液</td><td>低强度SR / SL / SM </td></tr><tr><td>内侧</td><td>使用轴向视图，从横向海马的前边缘向内侧画水平线</td><td> CA2 / CA3半路沿海马superiorinferior延伸</td><td> SR / SL / SM半路沿宽度海马优越劣扩展</td><td> alveus的WM </td></tr><tr><td>海马头3 </td><td></td><td></td><td></td><td></td></tr><tr><td>侧向</td><td>低强度SR / SL / SM </td><td>低强度SR / SL / SM </td><td>在环池脑脊液</td><td>低强度SR / SL / SM </td></tr><tr><td>内侧</td><td>在环池脑脊液</td><td> CA2 / CA3半路沿hippoca的superiorinferior延伸微处理器</td><td> SR / SL / SM半路沿宽度海马优越劣扩展</td><td> alveus的WM </td></tr><tr><td>海马头部4（有钩回） </td><td></td><td></td><td></td><td></td></tr><tr><td>侧向</td><td>低强度SR / SL / SM </td><td>低强度SR / SL / SM </td><td>在环池脑脊液</td><td>低强度SR / SL / SM </td></tr><tr><td>内侧</td><td>线平行于SR / SL / SM的上缘</td><td>环池脑脊液</td><td>环池脑脊液; lowintensity SR / SL / SM </td><td>环池脑脊液;低强度的SR / SL / SM </td></tr><tr><td>海马体</td><td> CA2 / CA3 </td><td>低强度SR / SL / SM </td><td>环池脑脊液</td><td>低强度SR / SL / SM </td></tr><tr><td>海马尾1 </td><td> CA2 / CA3和​​伞</td><td>低强度SR / SL / SM </td><td>侧脑室CSF </td><td>低强度SR / SL / S中号</td></tr><tr><td>海马尾2 </td><td colspan="4"> NA </td></tr><tr><td>最靠后的切片</td><td colspan="4"> NA </td></tr><tr><td rowspan="11"> SR / SL / SM </td><td>最前片</td><td colspan="4"> NA </td></tr><tr><td>海马头1 </td><td colspan="4">低强度SR / SL / SM的CA1和下脚中心</td></tr><tr><td>海马头2（带齿状） </td><td>使用轴向视图，从横向海马的前边缘向内侧画水平线</td><td>低强度SR / SL / SM周边CA4 / DG </td><td>环池脑脊液</td><td> CA2 / CA3和​​CA4 / DG半路沿宽度海马优越劣扩展</td></tr><tr><td>海马头3 </td><td>使用轴向视图，从横向海马的前边缘向内侧画水平线</td><td>低强度SR / SL / SM周边CA4 / DG </td><td>环池脑脊液</TD&gt; <td> CA2 / CA3和​​CA4 / DG半路沿宽度海马优越劣扩展</td></tr><tr><td>海马头部4（有钩回） </td><td></td><td></td><td></td><td></td></tr><tr><td>侧向</td><td colspan="4">低强度SR / SL / SM周边CA4 / DG </td></tr><tr><td>内侧</td><td>低强度SR / SL / Smin的中间（当很难看，大概用线203像素宽） </td><td>环池脑脊液</td><td> CA4 / DG </td><td> CA4 / DG </td></tr><tr><td>海马体</td><td colspan="4">低强度SR / SL / SM周边CA4 / DG </td></tr><tr><td>海马尾1 </td><td colspan="4">低强度SR / SL / SM周边CA4 / DG </td></tr><tr><td>海马尾2 </td><td colspan="4">低强度SR / SL / SM周边CA4 / DG </td></tr><tr><td>最靠后的切片</td><td colspan="4"> NA </td></tr></tbody></table>="1"FO:保持与- previous.within页="始终"&gt;表2.协议可靠性结果所有五个子场，并从5手工分割受试者整个海马 Resegmentations进行上无论是对还是每个科目的左侧海马。平均骰子的卡帕体现在五个科目的平均值。 <table><tbody><tr><td> 结构体 </td><td> 平均骰子的卡帕（系列） </td></tr><tr><td> CA1 </td><td> 0.78（0.77-0.79） </td></tr><tr><td> CA2 / CA3 </td><td> 0.64（0.56-0.73） </td></tr><tr><td> CA4 /齿状回</td><td> 0.83（0.81-0.85） </td></tr><tr><td> SR / SL / SM </td><td> 0.71（0.68-0.73） </td></tr><tr><td>下脚</td><td> 0.75（0.72-0.78） </td></tr><tr><td>全海马</td><td> 0.91（0.90-0.92） </td></tr></tbody></table>表3.平均子和整个海马体积。 <table><tbody><tr><td> 结构体 </td><td> 平均体积（范围）（mm 3）的 </td></tr><tr><td> CA1 </td><td> 857.46（720.17-981.68） </td></tr><tr><td> CA2 / CA3 </td><td> 208.33（155.10-281.57） </td></tr><tr><td> CA4 /齿状回</td><td> 615.50（500.16-763.01） </td></tr><tr><td> SR / SL / SM </td><td> 687.22（576.61-895.59） </td></tr><tr><td>下脚</td><td> 390.79（277.21-445.95） </td></tr><tr><td>全海马</td><td> 2759.31（2456.72-3325.02） </td></tr></tbody></table>

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High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

The goal of this manuscript is to study the hippocampus and hippocampal subfields using MRI. The manuscript describes a protocol for segmenting the hippocampus and five hippocampal substructures: cornu ammonis (CA) 1, CA2/CA3, CA4/dentate gyrus, strata radiatum/lacunosum/moleculare, and subiculum.

高分辨率<em&gt;在体内</em&gt;使用3T磁共振成像手动分割协议为人类海马子字段

The human hippocampus has been broadly studied in the context of memory and normal brain function and its role in different neuropsychiatric disorders has ...

high-resolution-vivo-manual-segmentation-protocol-for-human

Nanyang Technological University

Research

JoVE Journal

Neuroscience

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

9.2K 次观看.  University of Toronto. The goal of this manuscript is to study the hippocampus and hippocampal subfields using MRI. The manuscript describes a protocol for segmenting the hippocampus and five hippocampal substructures: cornu ammonis (CA) 1, CA2/CA3, CA4/dentate gyrus, strata radiatum/lacunosum/moleculare, and subiculum. 

视频: High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

Magnetic Resonance Spectroscopy of live Drosophila melanogaster using Magic Angle Spinning

High-Resolution Magic Angle Spinning (HRMAS) proton magnetic resonance spectroscopy (1H-MRS) is a novel non-destructive technique that improves spectral line-widths and allows high-resolution spectra to be obtained from extracts, intact cells, cell cultures, and more importantly intact tissue to investigate relationships between metabolites and cellular processes. In vivo HRMAS 1H-MRS studies have yet to be reported in the live fruit fly Drosophila melanogaster. Drosophila, as a simpler genetic organism, allows the multiple biological functions and various evolutionarily conserved signaling pathways to be examined at the whole organism level and it is a useful model for investigating genetics and physiology. To this end, we developed and implemented an in vivo HRMAS 1H-MRS method to investigate live Drosophila at 14.1 T. Here, we outline an HRMAS 1H-MRS protocol for the molecular characterization of Drosophila with a conventional MR spectrometer equipped with an HRMAS probe. This technique is a novel, in vivo, non-destructive Drosophila metabolite measurement approach, which enables the identification of disease biomarkers and thus may contribute to novel therapeutic development.

Magnetic Resonance Spectroscopy of live Drosophila melanogaster using Magic Angle Spinning

This technique enables the use of high-resolution magic angle spinning proton MR spectroscopy (HRMAS 1H-MRS) for molecular characterization of live Drosophila melanogaster with a conventional 14.1 tesla spectrometer equipped with an HRMAS probe.

生活磁共振波谱果蝇</em用魔角旋转

High-Resolution Magic Angle Spinning (HRMAS) proton magnetic resonance spectroscopy (1H-MRS) is a novel non-destructive technique that improves spectral ...

科研

神经科学

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Functional MRI (fMRI) is a widely used tool for non-invasively measuring correlates of human brain activity. However, its use has mostly been focused upon measuring activity on the surface of cerebral cortex rather than in subcortical regions such as midbrain and brainstem. Subcortical fMRI must overcome two challenges: spatial resolution and physiological noise. Here we describe an optimized set of techniques developed to perform high-resolution fMRI in human SC, a structure on the dorsal surface of the midbrain; the methods can also be used to image other brainstem and subcortical structures.
High-resolution (1.2 mm voxels) fMRI of the SC requires a non-conventional approach. The desired spatial sampling is obtained using a multi-shot (interleaved) spiral acquisition1. Since, T2* of SC tissue is longer than in cortex, a correspondingly longer echo time (TE ~ 40 msec) is used to maximize functional contrast. To cover the full extent of the SC, 8-10 slices are obtained. For each session a structural anatomy with the same slice prescription as the fMRI is also obtained, which is used to align the functional data to a high-resolution reference volume.
In a separate session, for each subject, we create a high-resolution (0.7 mm sampling) reference volume using a T1-weighted sequence that gives good tissue contrast. In the reference volume, the midbrain region is segmented using the ITK-SNAP software application2. This segmentation is used to create a 3D surface representation of the midbrain that is both smooth and accurate3. The surface vertices and normals are used to create a map of depth from the midbrain surface within the tissue4.
Functional data is transformed into the coordinate system of the segmented reference volume. Depth associations of the voxels enable the averaging of fMRI time series data within specified depth ranges to improve signal quality. Data is rendered on the 3D surface for visualization.
In our lab we use this technique for measuring topographic maps of visual stimulation and covert and overt visual attention within the SC1. As an example, we demonstrate the topographic representation of polar angle to visual stimulation in SC.

This article describes techniques to perform high-resolution functional magnetic resonance imaging with 1.2 mm sampling in human midbrain and subcortical structures using a 3T scanner. Use of these techniques to resolve topographic maps of visual stimulation in the human superior colliculus (SC) is given as an example.

高分辨率人类中脑功能磁共振成像方法

Functional MRI (fMRI) is a widely used tool for non-invasively measuring correlates of human brain activity. However, its use has mostly been focused upon ...

A Comprehensive Protocol for Manual Segmentation of the Medial Temporal Lobe Structures

The present paper describes a comprehensive protocol for manual tracing of the set of brain regions comprising the medial temporal lobe (MTL): amygdala, hippocampus, and the associated parahippocampal regions (perirhinal, entorhinal,&#160;and parahippocampal proper). Unlike most other tracing protocols available, typically focusing on certain MTL areas (e.g., amygdala and/or hippocampus), the integrative perspective adopted by the present tracing guidelines allows for clear localization of all MTL subregions. By integrating information from a variety of sources, including extant tracing protocols separately targeting various MTL structures, histological reports, and brain atlases, and with the complement of illustrative visual materials, the present protocol provides an accurate, intuitive, and convenient guide for understanding the MTL anatomy. The need for such tracing guidelines is also emphasized by illustrating possible differences between automatic and manual segmentation protocols. This knowledge can be applied toward research involving not only structural MRI investigations but also structural-functional colocalization and fMRI signal extraction from anatomically defined ROIs, in healthy and clinical groups alike.

The present work provides a comprehensive set of guidelines for manually tracing the medial temporal lobe (MTL) structures. This protocol can be applied to research involving structural and/or combined structural-functional magnetic resonance imaging (MRI) investigations of the MTL, in both healthy and clinical groups.

一个全面协议的内侧颞叶结构的手动分割

The present paper describes a comprehensive protocol for manual tracing of the set of brain regions comprising the medial temporal lobe (MTL): amygdala, ...

High-resolution Structural Magnetic Resonance Imaging of the Human Subcortex In Vivo and Postmortem

The focus of this study was to test the resolution limits of structural MRI of a postmortem brain compared to living human brains. The resolution of structural MRI in vivo is ultimately limited by physiological noise, including pulsation, respiration and head movement. Although imaging hardware continues to improve, it is still difficult to resolve structures on the millimeter scale. For example, the primary visual sensory pathways synapse at the lateral geniculate nucleus (LGN), a visual relay and control nucleus in the thalamus that normally is organized into six interleaved monocular layers. Neuroimaging studies have not been able to reliably distinguish these layers due their small size that are less than 1 mm thick.
The resolving limit of structural MRI, in a postmortem brain was tested using multiple images averaged over a long duration (~24 h). The purpose was to test whether it was possible to resolve the individual layers of the LGN in the absence of physiological noise. A proton density (PD)1 weighted pulse sequence was used with varying resolution and other parameters to determine the minimum number of images necessary to be registered and averaged to reliably distinguish the LGN and other subcortical regions. The results were also compared to images acquired in living human brains. In vivo subjects were scanned in order to determine the additional effects of physiological noise on the minimum number of PD scans needed to differentiate subcortical structures, useful in clinical applications.

High-resolution Structural Magnetic Resonance Imaging of the Human Subcortex In Vivo and Postmortem

Here we present a protocol to determine the minimum number images that needed to be registered and averaged to resolve subcortical structures and test whether the individual layers of the LGN could be resolved in the absence of physiological noise.

高分辨率结构磁共振人类皮质下的成像<I&gt;在体内</I&gt;与死亡

The focus of this study was to test the resolution limits of structural MRI of a postmortem brain compared to living human brains. The resolution of ...

Assessing Cortical Cerebral Microinfarcts on High Resolution MR Images

Cerebral microinfarcts are frequent findings in the post-mortem human brain, and are related to cognitive decline and dementia. Due to their small sizes it is challenging to study them on clinical MRI scans. It was recently demonstrated that cortical microinfarcts can be depicted with MRI scanners using high magnetic field strengths (7T). Based on this experience, a proportion of these lesions is also visible on lower resolution 3T MRI. These findings were corroborated with ex vivo imaging of post-mortem human brain tissue, accompanied by histopathological verification of possible cortical microinfarcts.
Here an ex vivo imaging protocol is presented, for the purpose of validating MR observed cerebral microvascular pathology with histological evaluation. Furthermore, guidelines are provided for the assessment of cortical microinfarcts on both in vivo 7T and 3T MR images. These guidelines provide researchers with a tool to rate cortical microinfarcts on in vivo images of larger patient samples, to further unravel their clinical relevance in cognitive decline and dementia, and establish these lesions as a novel biomarker of cerebral small vessel disease.

A high resolution ex vivo 7T MR imaging protocol is presented, to perform MR-guided histopathological validation of microvascular pathology in post-mortem human brain tissue. Furthermore, guidelines are provided for the assessment of cortical microinfarcts on in vivo 7T as well as 3T MR images.

评估皮层脑Microinfarcts高分辨率核磁共振图像

Cerebral microinfarcts are frequent findings in the post-mortem human brain, and are related to cognitive decline and dementia. Due to their small sizes ...

医学

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Within neuroimaging research, a number of recent studies have discussed the impact of between-study differences in volumetric findings that are thought to result from the use of different segmentation tools to generate brain volumes. Here, processing pipelines for seven automated tools that can be used to segment grey matter within the brain are presented. The protocol provides an initial step for researchers aiming to find the most accurate method for generating grey matter volumes from T1-weighted MRI scans. Steps to undertake detailed visual quality control are also included in the manuscript. This protocol covers a range of potential segmentation tools and encourages users to compare the performance of these tools within a subset of their data before selecting one to apply to a full cohort. Furthermore, the protocol may be further generalized to the segmentation of other brain regions.

This protocol describes the process of applying seven different automated segmentation tools to structural T1-weighted MRI scans to delineate grey matter regions that can be used for the quantification of grey matter volume.

t1 加权 mri 图像中皮质灰质的自动分割

Within neuroimaging research, a number of recent studies have discussed the impact of between-study differences in volumetric findings that are thought to ...

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI&#8212;Application in Premanifest Huntington's Disease

Recent advances in MRI offer a variety of useful markers to identify neurodegenerative diseases. In Huntington&#39;s disease (HD), regional brain atrophy begins many years prior to the motor onset (during the &#34;premanifest&#34; period), but the spatiotemporal pattern of regional atrophy across the brain has not been fully characterized. Here we demonstrate an online cloud-computing platform, &#34;MRICloud&#34;, which provides atlas-based whole-brain segmentation of T1-weighted images at multiple granularity levels, and thereby, enables us to access the regional features of brain anatomy. We then describe a regression model that detects statistically significant inflection points, at which regional brain atrophy starts to be noticeable, i.e. the &#34;change-point&#34;, with respect to a disease progression index. We used the CAG-age product (CAP) score to index the disease progression in HD patients. Change-point analysis of the volumetric measurements from the segmentation pipeline, therefore, provides important information of the order and pattern of structural atrophy across the brain. The paper illustrates the use of these techniques on T1-weighted MRI data of premanifest HD subjects from a large multicenter PREDICT-HD study. This design potentially has wide applications in a range of neurodegenerative diseases to investigate the dynamic changes of brain anatomy.

This paper describes a statistical model for volumetric MRI data analysis, which identifies the &#34;change-point&#34; when brain atrophy begins in premanifest Huntington&#39;s disease. Whole-brain mapping of the change-points is achieved based on brain volumes obtained using an atlas-based segmentation pipeline of T1-weighted images.

解剖性脑 MRI 的全脑分割及变化点分析--Premanifest 亨廷顿病的应用

Recent advances in MRI offer a variety of useful markers to identify neurodegenerative diseases. In Huntington&#39;s disease (HD), regional brain atrophy ...

3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol

The human brain, being a multiscale system, has both macroscopic electrical signals, globally flowing along thick white-matter fiber bundles, and microscopic neuronal spikes, propagating along axons and dendrites. Both scales complement different aspects of human cognitive and behavioral functions. At the macroscopic level, MRI has been the current standard imaging technology, in which the smallest spatial resolution, voxel size, is 0.1&#8211;1 mm3. Also, at the microscopic level, previous physiological studies were aware of nonuniform neuronal architectures within such voxels. This study develops a powerful way to accurately embed microscopic data into a macroscopic map by interfacing biological scientific research with technological advancements in 3D scanning technology. Since 3D scanning technology has mostly been used for engineering and industrial design until now, it is repurposed for the first time to embed microconnectomes into the whole brain while preserving natural spiking in living brain cells. In order to achieve this purpose, first, we constructed a scanning protocol to obtain accurate 3D images from living bio-organisms inherently challenging to image due to moist and reflective surfaces. Second, we trained to keep speed to prevent the degradation of living brain tissue, which is a key factor in retaining better conditions and recording more natural neuronal spikes from active neurons in the brain tissue. Two cortical surface images, independently extracted from two different imaging modules, namely MRI and 3D scanner surface images, surprisingly show a distance error of only 50 &#956;m as mode value of the histogram. This accuracy is comparable in scale to the microscopic resolution of intercellular distances; also, it is stable among different individual mice. This new protocol, the 3D novel embedding overlapping (3D-NEO) protocol, bridges macroscopic and microscopic levels derived by this integrative protocol and accelerates new scientific findings to study comprehensive connectivity architectures (i.e., microconnectome).

This article introduces an experimental protocol using 3D scanning technology bridging two spatial scales: the macroscopic spatial scale of whole-brain anatomy imaged by MRI at &#62;100 &#956;m and the microscopic spatial scale of neuronal distributions using immunohistochemistry staining and a multielectrode array system and other methods (~10 &#956;m).

3D 扫描技术在 3D 新颖嵌入重叠协议中桥接微电路和宏观大脑图像

The human brain, being a multiscale system, has both macroscopic electrical signals, globally flowing along thick white-matter fiber bundles, and ...

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Statistical shape analysis of brain structures has been used to investigate the association between their structural changes and pathological processes. We have developed a software package for accurate and robust shape modeling and group-wise analysis. Here, we introduce an pipeline for the shape analysis, from individual 3D shape modeling to quantitative group shape analysis. We also describe the pre-processing and segmentation steps using open software packages. This practical guide would help researchers save time and effort in 3D shape analysis on brain structures.

We introduce a semi-automatic protocol for shape analysis on brain structures, including image segmentation using open software, and further group-wise shape analysis using an automated modeling package. Here, we demonstrate each step of the 3D shape analysis protocol with hippocampal segmentation from brain MR images.

脑结构三维形状建模与分析

Statistical shape analysis of brain structures has been used to investigate the association between their structural changes and pathological processes. ...

加强脑部疾病的神经影像学分析

Manual Segmentation of the Human Choroid Plexus Using Brain MRI

The choroid plexus has been implicated in neurodevelopment and a range of brain disorders. Evidence demonstrates that the choroid plexus is critical for brain maturation, immune/ inflammatory regulation, and behavioral/cognitive functioning. However, current automated neuroimaging segmentation tools are poor at accurately and reliably segmenting the lateral ventricle choroid plexus. Furthermore, there is no existing tool that segments the choroid plexus located in the third and fourth ventricles of the brain. Thus, a protocol delineating how to segment the choroid plexus in the lateral, third, and fourth ventricle is needed to increase the reliability and replicability of studies examining the choroid plexus in neurodevelopmental and brain disorders. This protocol provides detailed steps to create separately labeled files in 3D Slicer for the choroid plexus based on DICOM or NIFTI images. The choroid plexus will be manually segmented using the axial, sagittal, and coronal planes of T1w images making sure to exclude voxels from gray or white matter structures bordering the ventricles. Windowing will be adjusted to assist in the localization of the choroid plexus and its anatomical boundaries. Methods for assessing accuracy and reliability will be demonstrated as part of this protocol. Gold standard segmentation of the choroid plexus using manual delineations can be used to develop better and more reliable automated segmentation tools that can be openly shared to elucidate changes in the choroid plexus across the lifespan and within various brain disorders.

作者聚焦：弥合解剖学差距并为算法研究奠定基础 

Despite the crucial role of the choroid plexus in the brain, neuroimaging studies of this structure are scarce due to the lack of reliable automated segmentation tools. The present protocol aims to ensure gold-standard manual segmentation of the choroid plexus that can inform future neuroimaging studies.

使用脑部 MRI 手动分割人脉络丛

The choroid plexus has been implicated in neurodevelopment and a range of brain disorders. Evidence demonstrates that the choroid plexus is critical for ...

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