我们感谢预测高清调查员, 特别是 Pauslen 博士和爱荷华州大学的简·约翰逊博士, 他们慷慨地分享了 MRI 数据, 并对数据分析和结果进行了建设性的讨论。
这项工作由 NIH 赠款 R21 NS098018、P50 NS16375、NS40068、R01 NS086888、R01 NS084957、P41 EB015909、P41 EB015909、R01 EB000975、R01 EB008171 和 U01 NS082085 支持。

1. 基于 Atlas 的全脑分割
<ol><li>数据准备
	<ol>
<li>转换三维 (3D) T1-weighted 图像, 通常获得与 MPRAGE (磁化准备快速梯度回声) 序列, 从供应商特定的 DICOM (数字成像和通信) 格式, 以分析格式。请注意, 云计算需要将用户的数据传输到远程群集。根据《健康保险可移植性和责任法》 (HIPPA), 从图像文件中删除患者的个人身份信息。 注: MRICloud 提供了一个 DICOM 到分析转换器 (https://braingps.mricloud.org/t1prep), 用于文件格式转换以及个人健康信息的取消标识。<ol>
<li>双击打开 Dcm2Analyze.exe。将打开一个弹出窗口 (图 1A)。</li>
			<li>指定输入 DICOM 数据目录路径作为输入, 并分析图像路径和文件名作为输出。</li>
			<li>单击 "转到" 以完成转换。 注意: 需要对每个患者执行转换, 并且在一个研究文件夹中输出所有转换后的图像以进行批处理 (1.2.2.1) 是有益的。</li>
		</ol>
</li>
	</ol></li>
	<li>基于多地图集的 T1 图像分割方法, 采用 MRICloud19。
	<ol>
<li>登录 "大脑 GPS" (注册为首次用户) 从 https://mricloud.org。从主菜单中选择 "分割" 工具 (图 1B)。在 "分割" 下面有两个应用程序编程接口 (API) 选项: "T1-MultiAtlas", 用于单 T1 图像分割, 以及批处理的 "T1-MultiAtlas 批次"。改变点分析需要大量的人口数据, 因此, 批处理往往是选择。</li>
		<li>在 "T1-MultiAtlas 批处理" API 上提交作业。<ol>
<li>将多个分析图像文件压缩到 zip 文件中。单击图 1B中的 "+. zip" 以上载 zip 文件。 注意: 当前的云门户将每个 zip 文件夹中的图像数限制为30。可以将大型数据集分成多个要处理的 zip 文件夹。可以为每个 zip 文件提供特殊的请求以容纳更多图像。将来, 当有更多的远程计算资源可用时, 我们可能会增加有限的数字, 甚至取消限制。</li>
			<li>填写图 1B中所需的字段。<ol>
<li>处理服务器: 选择 "计算解剖学科学网关"。</li>
				<li>切片类型: 选择从 "矢状", "轴向", 或 "矢状转换为轴向"。 注: "矢状" 指的是在前-后和头足方向上以平面视角获得的矢状方向图像。"轴向" 指的是从左向右和前后方向的平面内视图获得的轴向方向的图像。"矢状转换为轴向" 是指最初以轴向方向获得的图像, 后来转换成矢状图像 (这些通常是长颈区的 "轴向" 图像)。</li>
				<li>多地图集库: 选择最接近年龄范围的地图集库到用户数据, 优化分割精度。我们提供了预先生成的多地图集18的不同年龄范围, 如 "儿科 4-8yr", "儿科 8-12yr", "成人 22-50", 和 "成人 50-90", 以及不同的阿特拉斯版本。有关 atlas 版本的信息, 可以在 https://braingps.mricloud.org/atlasrepo 中找到。</li>
			</ol>
</li>
		</ol>
</li>
		<li>通过 "我的作业状态" 检查作业状态 (图 1C)。完成作业后, 将出现一个 "下载结果" 按钮, 允许用户将分割结果下载为. zip 文件。</li>
		<li>可视化结果。对于单个主题, 从分割结果获得的卷可以在线可视化 (对于批处理结果来说不可行)。<ol>
<li>单击图 1C中的 "查看结果" 按钮。网页将转向可视化界面 (图 1D)。在 T1-weighted 解剖图像上, 分割图的轴向、矢状、冠状均有重叠。3D. 分段脑结构的渲染显示在左上窗。叠加分割图的颜色表示结构体积的 z 分。</li>
			<li>调整可视化选项, 包括叠加开/关、覆盖的不透明度、放大和缩小以及从图 1D右上角面板中的切片位置。</li>
			<li>把最好的分割包裹分成不同的粒度。在我们的地图集, 我们定义了五级的粒度与两种类型的本体关系18,30。层次结构多级解剖定义的树视图显示在左下面板中 (图 1D)。单击级别编号以在相应的本体级别展开结构。分割映射将同时切换到相应的本体层次。 注: 双月刊 MRICloud 研讨会是约翰霍普金斯大学医学院的帮助提供上述在线操作的亲身教程。车间信息可从 https://braingps.mricloud.org/workshops 中找到。</li>
		</ol>
</li>
		<li>下载细分结果进行后续分析。将结果解压缩到用户研究目录, 例如, 将每个研究目录中的所有主题的分割结果放在一起, 每个主题文件夹中都有它们。 注意: 结果包括</li>
	</ol>
<ul style="margin-left: 40px;">
<li>示例. img: 在轴向方向的原始 T1 图像。</li>
		<li>example_MNI: T1 图像在 MNI 空间 Talairach 坐标之后。</li>
		<li>example_7Labels. img 和 example_7Labels_MNI: 在本机和 MNI 空间, 分别有7包裹 (灰质、白质、脑脊液、侧脑室、头骨和背景) 的粗分割。</li>
		<li>example_283Labels_M2 和 example_283Labels_M2_MNI. img: 在本机和 MNI 空间分别有283个包裹 (阿特拉斯版本 V9B) 的精细分割。标签的确切数量取决于阿特拉斯版本。</li>
		<li>example_corrected_MNI_stats 和 example_MNI_stats: 本地和 MNI 空间中每个脑包裹的体积统计。</li>
		<li>multilevel_lookup_table: 多级本体定义的脑包裹。</li>
	</ul></li>
	<li>执行批处理以获得人口中的脑容量。使用内部的 Matlab (www.mathworks.com) 批处理脚本从单个结果文件夹中提取脑卷, 并将所有科目的容量数据与电子表格相结合。图形用户界面 (GUI) 用于指定输入和输出。
	<ol>
<li>打开 Matlab.exe, 运行主图, GUI 将弹出 (图 2A)。</li>
		<li>在 "从 MRICloud 的 T1 卷提取" 面板 (图 2A的上部面板) 中, 指定输入, 包括下载的分割结果保存的学习目录 (见 1.2.5);和多级查找表文件路径和文件名。</li>
		<li>指定要写入卷数据的输出电子表格文件路径和文件名。</li>
		<li>单击 "提取卷" 按钮以运行分析。可以在用户定义的电子表格中检查结果。 注意: 此外, 还开发了一个 R 包来处理 MRICloud 输出, 并进行进一步的统计分析, 由布赖恩 Caffo31提供。软件包可以从 https://github.com/bcaffo/MRIcloudT1volumetrics 下载。</li>
	</ol></li>
</ol>2. 容积数据的变点分析
注: 请将更改点模型的理论和数学细节参考到我们以前的出版物21、24、23。简单地说, 对于 HD 数据, 建立一个回归模型来定义一个关键的变化点 (在 cap 评分), 从这开始, 线性回归之间的上限和体积成为统计学意义, 而纠正的影响, 病人的年龄,性别和颅内容积。内部的 Matlab 脚本, 连同 GUI (图 2A, 下面板), 被开发来计算各个结构的变化点, 并进行统计分析。用户可根据要求使用这些脚本。
<ol><li>
计算单个脑结构的变化点。
	<ol>
<li>在图 2A的 "更改点分析" 面板中, 指定要根据1.3 生成的多级卷电子表格的文件路径和名称。</li>
		<li>指定输出文本文件的文件路径和名称, 将为其写入更改点结果。</li>
		<li>选择下拉框 (级别 1-5) 中的粒度和本体定义类型的级别, 将执行更改点分析。</li>
		<li>单击 "计算更改点" 按钮执行更改点分析, 如参考23中所述, 结果更改点将保存在输出文本文件中。</li>
	</ol>
</li>
	<li>
对变化点的统计评价。
	<ol>
<li>在 Matlab GUI (图 2A、下面板) 中, 指定统计测试的参数, 包括置换的数量 (默认值 1万)、引导次数 (默认值 1万) 和 p 值阈值 (罗斯福更正后, 默认为 0.05)。</li>
		<li>单击 "统计测试" 按钮运行测试。在此步骤之后, p 值 (由置换测试), 在错误发现率 (罗斯福) 更正之前和之后, 以及标准偏差和95% 置信区间 (通过引导) 的变化点将被写入输出文本文件作为额外的列.请参阅23、24中统计测试程序的详细信息。</li>
	</ol>
</li>
	<li>生成更改点映射 (可选)。在 Matlab GUI (图 2A, 下面板) 中, 单击 "映射更改点" 按钮生成更改点映射。统计学意义上的变化点值将映射到 MNI 空间解剖图像, 以可视化空间格局。此映射可以在不同的粒度级别进行, 具体取决于2.1 中指定的解剖级别。更改点映射可以用 MRIcro (图 2B) (http://www.cabi.gatech.edu/mricro/mricro/) 覆盖在 T1-weighted 图像上。</li>
</ol>

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S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prediction+of+manifest+Huntington's+disease+with+clinical+and+imaging+measures:+a+prospective+observational+study.">Prediction of manifest Huntington's disease with clinical and imaging measures: a prospective observational study.</a> Lancet Neurol. 13 (12), 1193-1201 (2014).</li><li>Djamanakova, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tools+for+multiple+granularity+analysis+of+brain+MRI+data+for+individualized+image+analysis.">Tools for multiple granularity analysis of brain MRI data for individualized image analysis.</a> Neuroimage. 101, 168-176 (2014).</li><li>. A package for T1 volumetric analysis of MRIcloud output. 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V., Rueckert, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multi-atlas+based+segmentation+of+brain+images:+atlas+selection+and+its+effect+on+accuracy.">Multi-atlas based segmentation of brain images: atlas selection and its effect on accuracy.</a> Neuroimage. 46 (3), 726-738 (2009).</li><li>Huntington Study Group. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Unified+Huntington's+Disease+Rating+Scale:+reliability+and+consistency.">Unified Huntington's Disease Rating Scale: reliability and consistency.</a> Mov Disord. 11 (2), 136-142 (1996).</li><li>Liang, Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+Cross-Protocol+Stability+of+a+Fully+Automated+Brain+Multi-Atlas+Parcellation+Tool.">Evaluation of Cross-Protocol Stability of a Fully Automated Brain Multi-Atlas Parcellation Tool.</a> PLoS One. 10 (7), e0133533 (2015).</li></ol>

作者没有什么可透露的。

如本文所示, 使用我们的在线平台 MRICloud 可以方便地实现脑 MRI 的全脑分割。T1-weighted MRI 为基础的容积标记已表明是强健和敏感的一系列神经退行性疾病1,2,3。容积测量用于各种下游分析, 如数学建模、特征选择和分类分析, 以协助临床诊断和预后。脑容量的变化点分析可以定量描述疾病进展过程中的脑萎缩。这种统计分析采用了一个带有非线性分量的回归模型来定义脑萎缩过程中疾病指数的变化点,例如HD 评分. 与传统的群体分析相比, 在大多数情况下广泛采用现有的研究, 改变点模型寻求确切的发病点的脑萎缩, 因此, 提供了更多的具体信息的脑变性。结合自动全脑分割管线, 可以得到变化点的空间图, 揭示了 HD 疾病进展的时空格局。这在 HD 的 premanifest 阶段尤为重要, 因为治疗干预是最有效的。
在基于多地图集的图像分割中, 提供了多粒的脑分割, 使容量分析具有灵活性和可伸缩性。例如, 对于阿尔茨海默氏症, 几个小的大脑结构是特别感兴趣的, 如海马, 杏仁核, 或颞皮层的细分;而对于额颞部痴呆症, 大脑的检查在相对较粗的尺度, 如整个额叶和颞叶。根据我们以前的研究33, 分割精度和重现性可能会在高粒度下被破坏。此外, 多重比较的统计挑战将以更高的粒度增加, 如图 5所示。此外, 根据研究的年龄范围和疾病类型, 对 atlas 库进行适当的选择, 对于分割精度18、32非常重要。更改点分析需要相对大量的数据来执行回归分析,例如, 通常需要基于经验经验的 n > 50。对变化点结果的解释很大程度上依赖于统计测试, 因为模型将为任何动态数据系列产生一个变化点, 这有时是微不足道的。我们使用置换测试来评估加法的变化点是否能显著降低模型的残差, 并利用引导操作来减轻异常的影响。
根据特定的应用程序, 更改点模型可以有变化。例如, 疾病指数, 这是 HD 患者的 CAP 评分, 可以取代其他临床变量, 或简单的年龄。其他变量也可以包括在模型中, 如成像协议23和其他需要核算的因素。此外, 该模型适用于各种类型的生物标志物以外的容量标记, 包括其他成像标记 (从不同的对比机制, 如扩散, 灌注, 或功能磁共振) 和非成像标记。此外, 该模型的数学公式可以根据不同的假设和假设进行调整。举例来说, 模型可能涉及基线线性回归之前的变化点和一个额外的线性回归后发生的变化点, 如建议在参考24。
在神经退行性疾病的临床和基础研究中, 采用基于 atlas 的全脑分割的改变点分析方法, 可广泛应用。然而, 所提出的技术还是有局限性的。生物标志物的动态变化可能不是线性的, 因此, 在目前的变化点模型中使用的线性分量可能不是最优的。广义线性模型有可能被集成来处理非线性情况。其次, 改变点分析需要大量的纵向和/或横断面数据, 例如多中心预测-HD 数据在本研究中使用。不同的图像采集协议, 从多中心研究或纵向研究, 可能会强加偏差的体积测量。与生物效应 (如年龄和病理34) 相比, 我们的多地图集图像分割管线显示出相对于协议差异的鲁棒性。不过, 可能需要事先删除协议差异, 或者将协议效果作为23中描述的更改点模型中的变量之一。目前, 下游容量分析不包括在 MRICloud 中, 用户将需要从分割映射中提取卷, 或者使用我们的 Matlab 工具箱来执行多粒度卷分析。如果将此脱机处理步骤确定为用户的常见请求, 我们将来可能会将其集成到云管道中。
在神经退行性疾病的临床和基础研究中, 采用基于 atlas 的全脑分割的改变点分析方法, 可广泛应用。

磁共振成像 (MRI) 大大提高了我们的能力, 检查大脑解剖和功能的神经退行性疾病1,2,3。T1-weighted 结构 MRI 是常规临床实践中应用最广泛的影像学工具之一, 用于评估脑解剖学及相关病理学。对高分辨率 T1-weighted 图像进行定量分析, 为测量脑变性过程中的解剖变化提供了有用的标志。特别是, 基于分割的量化方法有效地将图像维数从体素水平 ((106)) 降低到解剖结构水平 ((102)), 用于高通量神经信息学4,5. 利用基于 atlas 的方法6、7、8、9将预定义的解剖标签从地图集映射到患者图像, 可以实现自动脑分割。.在基于地图集的方法中, 多地图集算法10、11、12、13、14具有较高的分割精度和鲁棒性。我们集团开发了一个全自动 T1 多地图集分割管线, 具有先进的 diffeomorphic 图像配准算法15, 多阿特拉斯融合方法16,17, 丰富的多地图集库18. 自2015年以来, 该管道已分布在一个云计算平台上, MRICloud19, 并已用于研究神经退行性疾病, 如阿尔茨海默病 (AD)20、21、初级渐进性失语症22, 亨廷顿氏病23。
一旦高分辨率图像被分割成脑结构, 区域特征, 如体积, 可以用来建立数学模型来表征神经解剖学的变化。本文以纵向和/或横断面 MRI 资料为基础, 对时间顺序进行了分析, 并对其进行了统计学意义上的变化。这一统计模型是第一次开发, 以量化基于形状的 diffeomorphometry 年龄在 AD 患者21,24;它后来被改编为研究亨廷顿氏病 (HD) 的大脑结构变化, 以及描述新生儿大脑的发育变化25。在 HD 患者中, 对 cag 年龄产品 (CAP) 评分的变化点进行了界定, 以此作为HTT 26中 cag 扩张程度的指标。众所周知, 巴萎缩是 HD 最早的标志之一, 其次是苍白27。然而, 纹状体的变化与大脑中其他的灰质和白质结构有关, 仍然不清楚。这种关系对我们了解疾病进展至关重要。对所有脑结构的容积变化进行改变点分析, 可能会提供 HD premanifest 阶段脑萎缩的系统信息。
在这里, 我们演示了使用 MRICloud (www.mricloud.org) 进行全脑分割的过程, 以及对 premanifest HD 主题中的容量数据进行更改点分析的步骤。MRI 数据从一大群多中心预测-hd 研究28,29与大约400控制和 premanifest hd 主题收集。基于地图集的分割和变化点分析的结合, 带来了关于大脑结构变化的时空顺序和整个大脑疾病进展模式的独特信息。这些技术可能适用于一系列神经退行性疾病, 各种生物标志物可以映射脑变性。

<table border="0" cellpadding="0" cellspacing="0" width="849">
	<tbody>
		<tr height="40">
			<td height="40" style="height:40px;width:216px;">MATLAB</td>
			<td style="width:123px;">Mathworks</td>
			<td style="width:344px;">N/A</td>
			<td style="width:167px;">Version 2015b and above</td>
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		<tr height="40">
			<td height="40" style="height:40px;">Dell Workstation</td>
			<td>Dell</td>
			<td></td>
			<td>Dell Precision T5500 (Intel Xeon CPU)</td>
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whole-brain segmentation and change-point analysis of anatomical brain mri&#8212;application in premanifest huntington's disease

最近的 MRI 研究进展提供了多种有用的标记来识别神经退行性疾病。在亨廷顿氏病 (HD), 区域脑萎缩开始前许多年在马达发病之前 (在 "premanifest" 期间), 但区域萎缩的时空格局在脑子没有被充分地描绘。在这里, 我们展示了一个在线云计算平台, "MRICloud", 它提供了基于地图集的全脑分割的 T1-weighted 图像在多个粒度水平, 从而使我们能够访问的区域特征的大脑解剖学。然后, 我们描述了一个回归模型, 它检测出统计学意义上的拐点, 区域脑萎缩开始明显,即"改变点", 关于疾病进展指数。我们使用 CAG 年龄的产品 (CAP) 评分指数的疾病进展, HD 患者。因此, 从分割管道的容积测量的变化点分析, 提供了关于大脑结构萎缩的顺序和模式的重要信息。本文从一个大的多中心预测-hd 研究中, 阐述了这些技术对 premanifest HD T1-weighted MRI 数据的应用。这种设计可能在一系列神经退行性疾病中有广泛的应用, 以研究脑解剖学的动态变化。

使用 1.1-1.3 中描述的过程, 可以从 MRICloud 中获得全脑分割图。在当前版本的阿特拉斯 (V9B), 283 包裹被分割在最佳的粒度 (等级 5), 可以分组到不同的粒度级别, e., 从半球到小叶和包裹, 根据具体的本体定义。图 3显示了两种类型的多级分割在五级, 在轴向和日冕视图。例如, 在粗糙级别, I 型分段定义了前脑、间脑、中脑、后脑和 myelencephalon 的经典脑区 (图 3A), 而第二类定义了临床和放射学上使用半球、小脑和脑干的约定 (图 3B)。在这里, 我们使用 II 型定义进行以下分析, 我们平均的数量从左和右半球, 因为没有已知的偏侧在 HD 病理学。
根据 2.1-2.2 节的细分结果, 对脑容量进行了改变点分析。在图 4中, 我们以基底节为例, 检查不同粒度水平的相关变化点。对基底节的3D 层次结构定义在顶行进行了说明。在单个结构中, 变化点分析的散布图显示在下面的行中, 其中蓝色点表示 premanifest HD 患者 (规范化到控制) 的结构卷的 z 分数, 在修正了年龄、性别和颅内容积;黑色曲线为拟合体积 z 分数, 回归模型23中的变点分量;红色线条指示检测到的更改点的位置。在1级, 只有半球分离是可利用的, 并且相应的散点图显示整个半球有逐渐萎缩, 当盖帽比分增加, 以在360和95% 信心间隔的 a 的 a 的 a 的 a 的 a 的 a 的 a 的 a 的水平的一个变分在 [352.8, 367.2] (更正)。在2级, 基底神经节是大脑细胞核的一部分, 大脑细胞核在 232 [227.7、236.3] (罗斯福之后的 p < 0.01) 上显示一个变化点。在3级, 基底节是一个独立的结构, 它显示一个变化点在 233 [228.6, 237.4] (p < 0.01 后, 罗斯福) 的上限。在4级, 基底节分为纹状体和球苍白, 在 230 [225.6, 234.4] 和 243 [238.6, 247.4] 分别有改变点 (在罗斯福以后的 p < 0.01)。在5级, 纹状体进一步分为尾状和壳核, 在 240 [234.9, 245.1] 和 211 [206.8, 215.2] 分别显示变化点 (在罗斯福之后的 p < 0.01)。
一旦个体的变化点被计算为所有脑子结构, 变动点的全脑空间地图可以根据2.3 获得。图 5显示了不同粒度级别的变化点映射和第二类本体定义。请注意, 只有有重大变化点的结构 (罗斯福修正后的 p < 0.05) 才会被映射。在1级, 整个脑实质 (除了小脑) 显示一个重要但相对较晚的变化点在盖帽 360 [352.8, 367.2] (p = 0.011 在罗斯福以后);而脑脊液 (包括侧脑室, III 和 IV 脑室, 沟空间) 显示稍早的变化点在盖帽 319 [313.0, 325.0] (p = 0.022 在罗斯福以后)。随着粒度水平的提高和空间方差开始揭示, 具有显著变化点的区域变得更加本地化。例如, 在等级 3, 下等白色物质陈列一个更早的变动点 (盖帽 = 305 [298.8, 311.2], p = 0.038 在罗斯福以后), 与前白色物质 (盖帽 = 371 [363.9, 378.1], p = 0.042 在罗斯福以后)。在5级, 壳核、尾状和球苍白之间的差异变得明显, 壳核显示最早的变化点, 其次是尾状和球苍白。
变化率计算为每盖帽评分的体积变化 (规范化到健康控制) 的百分比, 在变化点之后。相应结构的变化率映射在图 6中, 其中温暖的颜色表示心室和沟脑脊液的体积增加, 而寒冷的颜色表明脑实质的体积减少。在3级, 深灰色物质结构显示最高的变化率, 其次是前白质, 然后是劣质的白质。在5级, 壳核和球苍白表现出最快的萎缩 (每盖0.1% 容积损失), 后跟尾状 (每帽 0.07%)。随着粒度的提高, 在更多的本地化区域中, 变化率会变得更高。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/57256/57256fig1.jpg"> 图 1: MRICloud 上 T1-weighted 图像分割的图示.(A) 使用 Dcm2Analyzed.exe 将 DICOM 文件转换为分析格式并执行取消身份验证。(B) "T1-MultiAtlas 批处理" 网页。(C) "我的工作状况" 网页。(D) 用于可视化分割结果的网页。<a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57256/57256fig1large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/57256/57256fig2.jpg"> 图 2: 图形用户界面 (GUI) 进行卷分析和更改点分析.(A) Matlab GUI, 用于批量提取 MRICloud 分割输出 (上部面板) 和变化点分析 (下面板) 的容量数据。(B) MRICro 界面, 以可视化变化点地图。<a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57256/57256fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/57256/57256fig3.jpg"> 图 3: 基于 Atlas 的全脑分割在多个粒度级别上, 具有两种本体关系.根据 I 型 (A) 和 II 型 (B) 本体论定义, 多层分割图的轴向和日冕视图覆盖在 T1-weighted 解剖图像上。<a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57256/57256fig3large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/57256/57256fig4.jpg"> 图 4: 在多粒度水平上对基底神经节的变化点分析.在3D 渲染的顶部行显示半球 (1 级)、脑核 (2 级)、基底节 (3 级)、纹状体和球苍白 (4 级)、壳核和尾状 (水平 5) 之间的分层解剖关系。散射图显示了这些结构的变化点分析, 其中蓝色点表示在修正了年龄、性别和颅内容积后的体积数据的 z 分数 (规范化为健康的控制);黑色曲线为拟合 z 分数, 回归到变点相关的帽分量;红线表示变化点的位置。<a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57256/57256fig4large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/57256/57256fig5.jpg"> 图 5: 在多个粒度级别上的全脑变化点映射.显示重要更改点 (5% 罗斯福) 的区域映射到 T1-weighted 图像上, 颜色指示 CAP 评分单位中的更改点值。缩写: WM: 白色物质;LV: 侧脑室;AntWM: 前白物质;InfWM: 劣质的白质;BG: 基底节;ST: 纹状体;GP: 球苍白;ALIC: 内囊的前肢;PLIC: 内囊后肢;Caud: 尾状;把: 壳核。<a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57256/57256fig5large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/57256/57256fig6.jpg"> 图 6: 在多个粒度级别上的全脑变化率映射.更改率计算为每 CAP 的体积变化百分比 (规范化为健康控制) 后, 在显示显著变化点 (5% 罗斯福) 的区域中, 映射到 T1-weighted 图像。缩写: WM: 白色物质;LV: 侧脑室;AntWM: 前白物质;InfWM: 劣质的白质;BG: 基底节;ST: 纹状体;GP: 球苍白;ALIC: 内囊的前肢;PLIC: 内囊后肢;Caud: 尾状;把: 壳核。<a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57256/57256fig6large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>

Watch this Scientific Journal Video about Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRIÃ¢â‚¬â€Application in Premanifest Huntington's Disease at JoVE.com

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

本文介绍了一种容积 MRI 数据分析的统计模型, 它确定了 premanifest 亨廷顿病脑萎缩开始时的 "变化点"。利用基于地图集的 T1-weighted 图像分割管道获得的脑容量, 实现了变化点的全脑映射。

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 ...

whole-brain-segmentation-change-point-analysis-anatomical-brain

Nanyang Technological University

Research

JoVE Journal

Medicine

12.1K 次观看.  Johns Hopkins University School of Medicine. 本文介绍了一种容积 MRI 数据分析的统计模型, 它确定了 premanifest 亨廷顿病脑萎缩开始时的 "变化点"。利用基于地图集的 T1-weighted 图像分割管道获得的脑容量, 实现了变化点的全脑映射。

视频: Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease

Isolation of Soluble and Insoluble PrP Oligomers in the Normal Human Brain

The central event in the pathogenesis of prion diseases involves a conversion of the host-encoded cellular prion protein PrPC into its pathogenic isoform PrPSc 1. PrPC is detergent-soluble and sensitive to proteinase K (PK)-digestion, whereas PrPSc forms detergent-insoluble aggregates and is partially resistant to PK2-6. The conversion of PrPC to PrPSc is known to involve a conformational transition of &alpha;-helical to &beta;-sheet structures of the protein. However, the in vivo pathway is still poorly understood. A tentative endogenous PrPSc, intermediate PrP* or "silent prion", has yet to be identified in the uninfected brain7.
Using a combination of biophysical and biochemical approaches, we identified insoluble PrPC aggregates (designated iPrPC) from uninfected mammalian brains and cultured neuronal cells8, 9. Here, we describe detailed procedures of these methods, including ultracentrifugation in detergent buffer, sucrose step gradient sedimentation, size exclusion chromatography, iPrP enrichment by gene 5 protein (g5p) that specifically bind to structurally altered PrP forms10, and PK-treatment. The combination of these approaches isolates not only insoluble PrPSc and PrPC aggregates but also soluble PrPC oligomers from the normal human brain. Since the protocols described here have been used to isolate both PrPSc from infected brains and iPrPC from uninfected brains, they provide us with an opportunity to compare differences in physicochemical features, neurotoxicity, and infectivity between the two isoforms. Such a study will greatly improve our understanding of the infectious proteinaceous pathogens. The physiology and pathophysiology of iPrPC are unclear at present. Notably, in a newly-identified human prion disease termed variably protease-sensitive prionopathy, we found a new PrPSc that shares the immunoreactive behavior and fragmentation with iPrPC 11, 12. Moreover, we recently demonstrated that iPrPC is the main species that interacts with amyloid-&beta; protein in Alzheimer disease13. In the same study, these methods were used to isolate Abeta aggregates and oligomers in Alzheimer's disease13, suggesting their application to non-prion protein aggregates involved in other neurodegenerative disorders.

A new species of cellular prion protein (PrPC) has recently been identified in uninfected human brains using the methods described here. These methods can be used to isolate various PrP species, while some of them are also useful in isolating other misfolded protein aggregates from human brains.

在正常人脑分离的可溶性和不溶性朊蛋白低聚物

The central event in the pathogenesis of prion diseases involves a conversion of the host-encoded cellular prion protein PrPC into its pathogenic isoform ...

科研

医学

Identification and Isolation of Slow-Dividing Cells in Human Glioblastoma Using Carboxy Fluorescein Succinimidyl Ester (CFSE)

Tumor heterogeneity represents a fundamental feature supporting tumor robustness and presents a central obstacle to the development of therapeutic strategies1. To overcome the issue of tumor heterogeneity, it is essential to develop assays and tools enabling phenotypic, (epi)genetic and functional identification and characterization of tumor subpopulations that drive specific disease pathologies and represent clinically relevant targets. It is now well established that tumors exhibit distinct sub-fractions of cells with different frequencies of cell division, and that the functional criteria of being slow cycling is positively associated with tumor formation ability in several cancers including those of the brain, breast, skin and pancreas as well as leukemia2-8. The fluorescent dye carboxyfluorescein succinimidyl ester (CFSE) has been used for tracking the division frequency of cells in vitro and in vivo in blood-borne tumors and solid tumors such as glioblastoma2,7,8. The cell-permeant non-fluorescent pro-drug of CFSE is converted by intracellular esterases into a fluorescent compound, which is retained within cells by covalently binding to proteins through reaction of its succinimidyl moiety with intracellular amine groups to form stable amide bonds9. The fluorescent dye is equally distributed between daughter cells upon divisions, leading to the halving of the fluorescence intensity with every cell division. This enables tracking of cell cycle frequency up to eight to ten rounds of division10. CFSE retention capacity was used with brain tumor cells to identify and isolate a slow cycling subpopulation (top 5% dye-retaining cells) demonstrated to be enriched in cancer stem cell activity2. 
This protocol describes the technique of staining cells with CFSE and the isolation of individual populations within a culture of human glioblastoma (GBM)-derived cells possessing differing division rates using flow cytometry2. The technique has served to identify and isolate a brain tumor slow-cycling population of cells by virtue of their ability to retain the CFSE labeling.

Identification and Isolation of Slow-Dividing Cells in Human Glioblastoma Using Carboxy Fluorescein Succinimidyl Ester CFSE

This video protocol demonstrates the application of the fluorescent dye carboxyfluorescein succinimidyl ester (CFSE) for the identification and separation of different sub-populations of cells in human glioblastoma based on frequency of cell division.

慢分裂的细胞在人脑胶质瘤羧基荧光素琥珀酰亚胺酯（CFSE）的分离与鉴定

Tumor heterogeneity represents a fundamental feature supporting tumor robustness and presents a central obstacle to the development of therapeutic ...

The Use of Primary Human Fibroblasts for Monitoring Mitochondrial Phenotypes in the Field of Parkinson's Disease

Parkinson's disease (PD) is the second most common movement disorder and affects 1% of people over the age of 60 1. Because ageing is the most important risk factor, cases of PD will increase during the next decades 2. Next to pathological protein folding and impaired protein degradation pathways, alterations of mitochondrial function and morphology were pointed out as further hallmark of neurodegeneration in PD 3-11.
After years of research in murine and human cancer cells as in vitro models to dissect molecular pathways of Parkinsonism, the use of human fibroblasts from patients and appropriate controls as ex vivo models has become a valuable research tool, if potential caveats are considered. Other than immortalized, rather artificial cell models, primary fibroblasts from patients carrying disease-associated mutations apparently reflect important pathological features of the human disease.
Here we delineate the procedure of taking skin biopsies, culturing human fibroblasts and using detailed protocols for essential microscopic techniques to define mitochondrial phenotypes. These were used to investigate different features associated with PD that are relevant to mitochondrial function and dynamics. Ex vivo, mitochondria can be analyzed in terms of their function, morphology, colocalization with lysosomes (the organelles degrading dysfunctional mitochondria) and degradation via the lysosomal pathway. These phenotypes are highly relevant for the identification of early signs of PD and may precede clinical motor symptoms in human disease-gene carriers. Hence, the assays presented here can be utilized as valuable tools to identify pathological features of neurodegeneration and help to define new therapeutic strategies in PD.

Fibroblasts from patients carrying mutations in Parkinson's disease-causing genes represent an easily accessible ex vivo model to study disease-associated phenotypes. Live cell imaging gives the opportunity to study morphological and functional parameters in living cells. Here we describe the preparation of human fibroblasts and subsequent monitoring of mitochondrial phenotypes.

利用人类纤维原细胞线粒体表型的监测领域的帕金森氏病

Parkinson's disease (PD) is the second most  common movement disorder and affects 1% of people over the age of 60 1. Because ageing is  the most important ...

Quantitative Analysis of Chromatin Proteomes in Disease

In the nucleus reside the proteomes whose functions are most intimately linked with gene regulation. Adult mammalian cardiomyocyte nuclei are unique due to the high percentage of binucleated cells,1 the predominantly heterochromatic state of the DNA, and the non-dividing nature of the cardiomyocyte which renders adult nuclei in a permanent state of interphase.2 Transcriptional regulation during development and disease have been well studied in this organ,3-5 but what remains relatively unexplored is the role played by the nuclear proteins responsible for DNA packaging and expression, and how these proteins control changes in transcriptional programs that occur during disease.6 In the developed world, heart disease is the number one cause of mortality for both men and women.7 Insight on how nuclear proteins cooperate to regulate the progression of this disease is critical for advancing the current treatment options.
Mass spectrometry is the ideal tool for addressing these questions as it allows for an unbiased annotation of the nuclear proteome and relative quantification for how the abundance of these proteins changes with disease. While there have been several proteomic studies for mammalian nuclear protein complexes,8-13 until recently14 there has been only one study examining the cardiac nuclear proteome, and it considered the entire nucleus, rather than exploring the proteome at the level of nuclear sub compartments.15 In large part, this shortage of work is due to the difficulty of isolating cardiac nuclei. Cardiac nuclei occur within a rigid and dense actin-myosin apparatus to which they are connected via multiple extensions from the endoplasmic reticulum, to the extent that myocyte contraction alters their overall shape.16 Additionally, cardiomyocytes are 40% mitochondria by volume17 which necessitates enrichment of the nucleus apart from the other organelles. Here we describe a protocol for cardiac nuclear enrichment and further fractionation into biologically-relevant compartments. Furthermore, we detail methods for label-free quantitative mass spectrometric dissection of these fractions-techniques amenable to in vivo experimentation in various animal models and organ systems where metabolic labeling is not feasible.

Advances in mass spectrometry have allowed the high throughput analysis of protein expression and modification in a host of tissues. Combined with subcellular fractionation and disease models, quantitative mass spectrometry and bioinformatics can reveal new properties in biological systems. The method described herein analyzes chromatin-associated proteins in the setting of heart disease and is readily applicable to other in vivo models of human disease.

在疾病的染色质蛋白质组的定量分析

In the nucleus reside the proteomes whose functions are most intimately linked with gene regulation. Adult mammalian cardiomyocyte nuclei are unique due ...

Utilizing a Cranial Window to Visualize the Middle Cerebral Artery During Endothelin-1 Induced Middle Cerebral Artery Occlusion

Creation of a cranial window is a method that allows direct visualization of structures on the cortical surface of the brain1-3. This technique can be performed in many locations overlying the rat cerebrum, but is most easily carried out by creating a craniectomy over the readily accessible frontal or parietal bones. Most frequently, we have used this technique in combination with the endothelin-1 middle cerebral artery occlusion model of ischemic stroke to quantify the changes in middle cerebral artery vessel diameter that occur with injection of endothelin-1 into the brain parenchyma adjacent to the proximal MCA4, 5. In order to visualize the proximal portion of the MCA during endothelin -1 induced MCAO, we use a technique to create a cranial window through the temporal bone on the lateral aspect of the rat skull (Figure 1). Cerebral arteries can be visualized either with the dura intact or with the dura incised and retracted. Most commonly, we leave the dura intact during visualization since endothelin-1 induced MCAO involves delivery of the vasoconstricting peptide into the brain parenchyma. This bypasses the need to incise the dura directly over the visualized vessels for drug delivery. This protocol will describe how to create a cranial window to visualize cerebral arteries in a step-wise fashion, as well as how to avoid many of the potential pitfalls pertaining to this method.

This article describes a method for visualizing rat cerebral arteries through a cranial window using temporal craniectomy in order to view proximal portions of the middle cerebral artery (Figure 1). This versatile method can be combined with various techniques of drug delivery to measure cerebral artery reactivity in vivo.

利用颅窗口，在可视化的大脑中动脉内皮素-1诱导大脑中动脉闭塞

Creation of a cranial window is a method that allows direct visualization of structures on the cortical surface of the brain1-3. This technique can be ...

A Simple Method of Mouse Lung Intubation

A simple procedure to intubate mice for pulmonary function measurements would have several advantages in longitudinal studies with limited numbers or expensive animal. One of the reasons that this is not done more routinely is that it is relatively difficult, despite there being several published studies that describe ways to achieve it. In this paper we demonstrate a procedure that eliminates one of the major hurdles associated with this intubation, that of visualizing the trachea during the entire time of intubation. The approach uses a 0.5 mm fiberoptic light source that serves as an introducer to direct the intubation cannula into the mouse trachea. We show that it is possible to use this procedure to measure lung mechanics in individual mice over a time course of at least several weeks. The technique can be set up with relatively little expense and expertise, and it can be routinely accomplished with relatively little training. This should make it possible for any laboratory to routinely carry out this intubation, thereby allowing longitudinal studies in individual mice, thereby minimizing the number of mice needed and increasing the statistical power by using each mouse as its own control.

This paper describes a striaghforward and efficient method of intubating mice for pulmonary function measurements or pulmonary instillation, that allows the mice to recover and be studied at later times. The procedure involves an inexpensive fiberoptic light source that directly illuminates the trachea.

一个简单的方法小鼠肺插管

A  simple procedure to intubate mice for pulmonary function measurements would  have several advantages in longitudinal studies with limited numbers or  ...

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Obtaining in vivo human brain tissue volumetrics from MRI is often complicated by various technical and biological issues. These challenges are exacerbated when significant brain atrophy and age-related white matter changes (e.g. Leukoaraiosis) are present. Lesion Explorer (LE) is an accurate and reliable neuroimaging pipeline specifically developed to address such issues commonly observed on MRI of Alzheimer's disease and normal elderly. The pipeline is a complex set of semi-automatic procedures which has been previously validated in a series of internal and external reliability tests1,2. However, LE's accuracy and reliability is highly dependent on properly trained manual operators to execute commands, identify distinct anatomical landmarks, and manually edit/verify various computer-generated segmentation outputs.
LE can be divided into 3 main components, each requiring a set of commands and manual operations: 1) Brain-Sizer, 2) SABRE, and 3) Lesion-Seg. Brain-Sizer's manual operations involve editing of the automatic skull-stripped total intracranial vault (TIV) extraction mask, designation of ventricular cerebrospinal fluid (vCSF), and removal of subtentorial structures. The SABRE component requires checking of image alignment along the anterior and posterior commissure (ACPC) plane, and identification of several anatomical landmarks required for regional parcellation. Finally, the Lesion-Seg component involves manual checking of the automatic lesion segmentation of subcortical hyperintensities (SH) for false positive errors.
While on-site training of the LE pipeline is preferable, readily available visual teaching tools with interactive training images are a viable alternative. Developed to ensure a high degree of accuracy and reliability, the following is a step-by-step, video-guided, standardized protocol for LE's manual procedures.

Lesion Explorer (LE) is a semi-automatic, image-processing pipeline developed to obtain regional brain tissue and subcortical hyperintensity lesion volumetrics from structural MRI of Alzheimer's disease and normal elderly. To ensure a high level of accuracy and reliability, the following is a video-guided, standardized protocol for LE's manual procedures.

病变资源管理器:一个视频引导，标准化为老年痴呆症准确，可靠的MRI衍生Volumetrics和正常老年人协议

Obtaining in vivo human brain tissue volumetrics from MRI is often complicated by various technical and biological issues. These challenges are ...

Controlling Parkinson's Disease With Adaptive Deep Brain Stimulation

Adaptive deep brain stimulation (aDBS) has the potential to improve the treatment of Parkinson&#39;s disease by optimizing stimulation in real time according to fluctuating disease and medication state. In the present realization of adaptive DBS we record and stimulate from the DBS electrodes implanted in the subthalamic nucleus of patients with Parkinson&#39;s disease in the early post-operative period. Local field potentials are analogue filtered between 3 and 47 Hz before being passed to a data acquisition unit where they are digitally filtered again around the patient specific beta peak, rectified and smoothed to give an online reading of the beta amplitude. A threshold for beta amplitude is set heuristically, which, if crossed, passes a trigger signal to the stimulator. The stimulator then ramps up stimulation to a pre-determined clinically effective voltage over 250 msec and continues to stimulate until the beta amplitude again falls down below threshold. Stimulation continues in this manner with brief episodes of ramped DBS during periods of heightened beta power.
Clinical efficacy is assessed after a minimum period of stabilization (5 min) through the unblinded and blinded video assessment of motor function using a selection of scores from the Unified Parkinson&#39;s Rating Scale (UPDRS). Recent work has demonstrated a reduction in power consumption with aDBS as well as an improvement in clinical scores compared to conventional DBS. Chronic aDBS could now be trialed in Parkinsonism.

Adaptive deep brain stimulation (aDBS) is effective for Parkinson&#8217;s disease, improving symptoms and reducing power consumption compared to conventional deep brain stimulation (cDBS). In aDBS we track a local field potential biomarker (beta oscillatory amplitude) in real time and use this to control the timing of stimulation.

控制帕金森氏症与自适应深部脑刺激

Adaptive deep brain stimulation (aDBS) has the potential to improve the treatment of Parkinson&#39;s disease by optimizing stimulation in real time ...

Carotid Artery Infusions for Pharmacokinetic and Pharmacodynamic Analysis of Taxanes in Mice

When proposing the use of a drug, drug combination, or drug delivery into a novel system, one must assess the pharmacokinetics of the drug in the study model. As the use of mouse models are often a vital step in preclinical drug discovery and drug development1-8, it is necessary to design a system to introduce drugs into mice in a uniform, reproducible manner. Ideally, the system should permit the collection of blood samples at regular intervals over a set time course. The ability to measure drug concentrations by mass-spectrometry, has allowed investigators to follow the changes in plasma drug levels over time in individual mice1, 9, 10. In this study, paclitaxel was introduced into transgenic mice as a continuous arterial infusion over three hours, while blood samples were simultaneously taken by retro-orbital bleeds at set time points. Carotid artery infusions are a potential alternative to jugular vein infusions, when factors such as mammary tumors or other obstructions make jugular infusions impractical. Using this technique, paclitaxel concentrations in plasma and tissue achieved similar levels as compared to jugular infusion. In this tutorial, we will demonstrate how to successfully catheterize the carotid artery by preparing an optimized catheter for the individual mouse model, then show how to insert and secure the catheter into the mouse carotid artery, thread the end of the catheter out through the back of the mouse&#8217;s neck, and hook the mouse to a pump to deliver a controlled rate of drug influx. Multiple low volume retro-orbital bleeds allow for analysis of plasma drug concentrations over time.

This method was developed with the goal of delivering a steady drug solution via the carotid artery, to assess the pharmacokinetics of novel drugs in mouse models.

颈动脉输液的紫杉烷类化合物在小鼠体内的药代动力学和药效学分析

When proposing the use of a drug, drug combination, or drug delivery into a novel system, one must assess the pharmacokinetics of the drug in the study ...

A Tissue Displacement-based Contusive Spinal Cord Injury Model in Mice

Producing a consistent and reproducible contusive spinal cord injury (SCI) is critical to minimizing behavioral and histological variabilities between experimental animals. Several contusive SCI models have been developed to produce injuries using different mechanisms. The severity of the SCI is based on the height that a given weight is dropped, the injury force, or the spinal cord displacement. In the current study, we introduce a novel mouse contusive SCI device, the Louisville Injury System Apparatus (LISA) impactor, which can create a displacement-based SCI with high injury velocity and accuracy. This system utilizes laser distance sensors combined with advanced software to produce graded and highly-reproducible injuries. We performed a contusive SCI at the 10th thoracic vertebral (T10) level in mice to demonstrate the step-by-step procedure. The model can also be applied to the cervical and lumbar spinal levels.

We introduce a tissue displacement-based contusive spinal cord injury model that can produce a consistent contusive spinal cord injury in adult mice.

基于组织位移的小鼠脊髓损伤模型

Producing a consistent and reproducible contusive spinal cord injury (SCI) is critical to minimizing behavioral and histological variabilities between ...