土地管理局是 EPSRC 博士李兆基的接受者, 从布里斯托尔大学实验心理学学院获得了一笔旅游补助金给芬兰东部大学。MJK 由伊丽莎白-布莱克韦尔研究所和惠康信托国际战略支持基金资助 [ISSF2: 105612/z/14/z]。KTJ 和 OHJG 由芬兰的学院、UEF 的战略资助, 由芬兰东部大学和芬兰 Biocenter 资助。这项工作得到了登喜路医疗信托基金的支持 [补助金号 R385/1114]。

动物程序是根据欧洲共同体理事会指令 86/609/欧洲经济共同体指南进行的, 并由芬兰东部芬兰库奥皮奥大学动物保育和使用委员会批准. 
 1. 动物模型 <ol> <li> 麻醉的雄性大鼠, 在 N 2 /O 2 流 (70%/30%) 中, 通过口罩在操作和 MRI 实验期间, 重度为 300-400 克与异氟醚。在通风罩内诱导麻醉。在1.5 和2.4% 之间保持异氟醚水平. 
	<ol> <li> 通过躯干下的充气枕头从呼吸频率中监控 MRI 的麻醉深度。缺乏反应的捏反射被视为足够深度的外科麻醉的标志。使用附着在磁铁孔上的异氟醚清除剂. </li>
	</ol> </li> <li> 执行永久性大脑中动脉闭塞 (MCAO) 以诱发局灶性缺血性中风。根据姜黄 et al. 给出的方法, 使用 MCAO 的腔内螺纹模型进行操作。 22 . <ol> <li> 将咬合线程 (硅 PTFE 回火 monofil 灯丝、直径 0.22 mm) 留在 MRI 实验期间. </li>
	</ol> </li> <li> 使用血液分析仪分析动脉血气和 pH 值. 
	<ol> <li> 在 MRI 期间, 使用直肠温度监测系统在躯干下放置一个充气枕头和直肠温度监测呼吸频率。保持核心温度接近37和 #176; C 使用在躯干下的水加热垫. </li>
		<li> 在 MCAO 后立即将老鼠固定在磁铁孔中心的摇篮中, 使用鼠头。在将大鼠转移到磁铁孔前注入2毫升盐水腹腔. </li>
	</ol> </li> </ol> 2。mri <ol> <li> 使用 9.4T/31 厘米 (带有12厘米渐变插入) 的水平磁铁与装有主动解耦的线性音量变送器和正交接收线圈对的控制台进行 mri 数据的采集. </li>
	<li> 扫描每只老鼠多达5小时后 MCAO。每小时间隔 (60, 120, 180, 240 分钟后 MCAO), 获得12一致取样 (0.5 毫米片隙, 切片厚度 = 1 毫米, 视野 = 2.56 厘米 x 2.56 厘米) 扩散张量 (2.2.1.), 卡尔-赛尔-Meiboom-鳃 T 2 (2.2.2) 和快速低角度拍摄 T 1 (2.2.3.) 
	<ol> <li> 获取扩散张量图像的跟踪 (d av = 1/3 跟踪 [d]), 每个轴上有三双极性渐变 (扩散渐变的持续时间 = 5 毫秒, 扩散时间 = 15 毫秒) 和三 b 值 (0、400和十五世纪年代/mm- 2 ),在哪里, #916; = 15 毫秒, #8706; = 5 毫秒, 回显时间 (TE) = 36 毫秒, 重复时间 (TR) = 4000 毫秒和获取时间 = 7.36 min. </li>
		<li> 获得卡尔-赛尔-Meiboom-鳃 t 2 序列与12回声 t 2 定量, 其中回声间距 = 10 毫秒, TR = 2000 毫秒和获取时间 = 4.20 min. </li>
		<li> 获取 T 1 的快速低角度拍摄 (FLASH) , 从反转到第一个 FLASH 序列 (t 10 ) 的时间是7.58 毫秒, 600 ms 增量为10反转, 最多为5407.58 毫秒, TR = 5.5 毫秒, 反转脉冲之间的时间 (t 放松) = 十年代和获取时间 = 8.20 分钟 </li>
	</ol> </li> </ol> 3。图像处理 <ol> <li> 计算 relaxometry 和 adc 映射: 计算 qt 2 、qt 1 和使用在布里斯托尔大学网站上提供的 Matlab 函数的 adc 映射 [我: 10.5523/割礼 1bjytiabmtwqx2kodgbzkwso0k], 用于输入是 MRI 数据位置的文件路径. 
	<ol> <li> 对于 T 2 数据, 请在重建图像之前 (或在图像域中通过卷积将汉明过滤应用于 k 空间), 具有等效结果但计算效率较低)。计算 qT 2 映射, 方法是采用每个时间序列的对数, 并通过线性最小二乘法 (a 和 #160 对 voxel-wise 的基础进行求解; 双指数拟合也可以执行到 T 2 衰变, 但 voxel-wise F 测试结果显示体在图像中, 无法为其添加其他参数. </li>
		<li> 对于 T 1 数据, 在重建图像前将汉明滤波应用于 k 空间。根据在引用 23 中给出的方法执行 T 1 管接头。为了处理未知符号的问题 (由于使用了数量级图像), 最低强度点可以被排除, 或者在拟合结果的过程中进行估计. </li>
		<li> 对于扩散加权数据, 在图像域中应用卷积进行汉明滤波 (这是由于分割的 k 空间轨迹更直接)。按 13 中的方法调整 ADC 映射. </li>
	</ol> </li> <li> 对缺血性组织的识别 <ol> <li> 在互惠 d av 图像上识别缺血性组织 (1/D av ), 因为这为病灶识别提供了清晰的对比度。为了产生缺血体积的兴趣 (VOI), 定义缺血组织作为体与价值的一个中位数绝对偏差以上的中值全脑 1/D av 分布。要确定缺半球的同源区域, 应反映垂直轴的缺血性 VOI。手动调整缺 VOIs, 以避免含体脑脊液. </li>
		<li> 为了确定 qt 之间的关系 1 和 qt 2 与时间后 MCAO, 为每一个鼠和时点, 负载缺血性和缺 VOIs qt 1 和 qt 2 地图。提取平均弛豫次数, 计算 qt 1 和 qt 2 之间的百分比差异 (#916; t 1 和 #916; t 2 ) 使用以下等式: img alt = "等式" src = "/文件/ftp_上传/55277/55277eq1. jpg "/>> 其中 T x 是所选参数, qt 1 或 qt 2 。<img alt="Equation" src="/files/ftp_upload/55277/55277eq2.jpg"/> 指的是缺血性 VOI 的平均弛豫时间和 <img alt="Equation" src="/files/ftp_upload/55277/55277eq3.jpg"/> 缺 VOI 的平均弛豫时间。缺 VOI 应使用, 使每只老鼠作为自己的控制. </li>
		<li> 使用以下条件来识别体与升高的 qt 1 和 qt 2 : 在缺血性 VOI 内的任何体, 松弛时间超过 qt 1 或 qt 2 分布的中位弛豫时。缺 VOI 在 half-maximum (HWMH) 上有超过一个半角。这些标准意味着放松时间必须在 95 th 百分点或更高的分类为和 #39; 高和 #39;。使用缺 VOI 的中位松弛时间可以让每只老鼠作为自己的控制. </li>
		<li> 图像的空间分布的松弛时间变化的区域内减少扩散, 识别和颜色代码体与高架 qt 1 或 qt 2 以及体与高架 qt 1 和 qt 2 命名和 #39; qt 1 和 qt 2 重叠和 #39;... </li>
		<li> 要根据 qt 确定病变的大小 1 和 qt 2 , 计算参数 f (由骑士 et al. 介绍 18 ) 从为每只老鼠和时点获得的 MRI 数据。f 1 和 f 2 代表t 体的数量高 qt 1 或 qt 2 (分别) 为缺血性 VOI 的大小的百分比。
		<ol> <li> 使用以下公式计算 f 1 和 f 2 : <img alt="Equation" src="/files/ftp_upload/55277/55277eq4.jpg"/> , 其中 <img alt="Equation" src="/files/ftp_upload/55277/55277eq5.jpg"/> 指松弛时间 (qt 1 或 qt 2 ), <img alt="Equation" src="/files/ftp_upload/55277/55277eq6.jpg"/> 是指 #39 的数量; 高 #39; 松弛时间体在缺血性 VOI,<img alt="Equation" src="/files/ftp_upload/55277/55277eq7.jpg"/> 是 #39 的数量; 低和 #39; 松弛时间体在缺血性 VOI 和 <img alt="Equation" src="/files/ftp_upload/55277/55277eq8.jpg"/>, 总数量的体内缺血性 VOI。在第3.2.3 节中概述了用于识别体的标准, qt 1 和 qt 2 。和 #39; 低 #39; 体是体的松弛时间小于中位 qt 1 或缺 VOI 的 qt 2 HWHM。<img alt="Equation" src="/files/ftp_upload/55277/55277eq7.jpg"/> 的减法允许因缺血或其他病症而减少松弛时间 17 . #160; </li> <li> 确定和 #39 的范围; qT 1 #160; 和 qt 2 和 #160; 重叠和 #39; 通过计算重叠升高的 qt 1 和 #160; qt 2 和 #160 的体积; 作为整个脑容量的百分比, 特此称为和 #39; V 重叠 和 #39;。使用下面的等式: <img alt="Equation" src="/files/ftp_upload/55277/55277eq9.jpg"/> Where, <img alt="Equation" src="/files/ftp_upload/55277/55277eq10.jpg"/> 指的是缺血性 VOI 内的体的数量#39; 高 #39; qt 1 和 #39; 高 #39; qt 2 和 <img alt="Equation" src="/files/ftp_upload/55277/55277eq11.jpg"/> 表示整个大鼠大脑中的体总数。通过在 qT 2 relaxometry 地图上手工创建一个围绕整个大脑的 VOI 来确定大鼠大脑中体的数量. </li>
		</ol> </li> </ol> </li> </ol> 4。Triphenyletrazolium 氯 (TTC) 对缺血性病变的验证 <ol> <li> 在斩首之后, 小心地从头骨中取出老鼠的大脑。完成此过程中, 从老鼠被斩首的时间10分钟. </li>
	<li> 储存大脑在冷冻0.01 米磷酸盐缓冲盐水 (PBS) 之前使用大鼠脑切片器矩阵, 以部分的大脑1毫米厚的冠状切片. </li>
	<li> 在切片后, 将20毫升 PBS 中的每个脑切片孵育到37和 #176; C 在黑暗中为30分钟, 如 24 中所建议的那样。虽然 1% TTC 浓度是可以接受的, 使用 0.5%, 以改善对比度. 
	<ol> <li> 用铝箔覆盖各部分的容器, 以使其保持深色. </li>
	</ol> </li> <li> 孵化后, 使用吸管移除 TTC 溶液, 并在 PBS 的三变化中清洗切片. </li>
	<li> 使用标准光学显微镜和数码相机立即拍摄切片. </li>
</ol> 5。统计分析 <ol> <li> 使用 Matlab 和统计软件进行统计分析. </li>
	<li> 确定 MR 参数与时间的关系 <ol> <li> 执行皮尔逊和 #39 对池鼠数据的相关性, 以确定与 #916 的关系; t 1 , 和 #916; t 2, f 1 和 f 2 和 V 与时间过帐 MCAO 重叠 . </li>
		<li> 对于显示显著线性关系的参数 ( p & #60; 0.05), 执行线性最小二乘回归来确定是否可以通过量化感兴趣的参数来预测笔画的起始时间。使用根均方误差 (RMSE) 来评估起始时间估计的准确性. </li>
	</ol> </li> <li> 病灶大小的量化 <ol> <li> 根据不同的 qMRI 参数来比较病变大小, 进行 one-way 相关的 ANOVAs 和 Fisher #39; 事后对体的平均数量的影响最小缺血性 VOI 和体的平均数字与高 qt 1 和 qt 2 。在 p 和 #60 中, 差异被认为是重要的; 0.05。如果度假设没有满足每莫齐利和 #39 的度测试, 正确的自由度和意义值根据温室 Geisser 估计. </li>
	</ol>
	</li>
</ol>

<ol>
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Cereb. Blood Flow Metab. 15, 1002-1011 (1995).</li><li>Longa, E. Z., Weinstein, P. R., Carlson, S., Cummins, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reversible+middle+cerebral+artery+occlusion+without+craniectomy+in+rats.">Reversible middle cerebral artery occlusion without craniectomy in rats.</a> Stroke. 20, 84-91 (1989).</li><li>Nekolla, S., Gneiting, T., Syha, J., Deichmann, R., Haase, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=T1+maps+by+K-space+reduced+snapshot-FLASH+MRI.">T1 maps by K-space reduced snapshot-FLASH MRI.</a> J Comput Assist Tomogr. 16, 327-332 (1992).</li><li>Joshi, C. N., Jain, S. K., Murthy, P. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+optimized+triphenyltetrazolium+chloride+method+for+identification+of+cerebral+infarcts.">An optimized triphenyltetrazolium chloride method for identification of cerebral infarcts.</a> Brain Res Brain Res Protoc. 13, 11-17 (2004).</li><li>McGarry, B. L., 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=Determining+stroke+onset+time+using+quantitative+MRI:+High+accuracy,+sensitivity+and+specificity+obtained+from+magnetic+resonance+relaxation+times.">Determining stroke onset time using quantitative MRI: High accuracy, sensitivity and specificity obtained from magnetic resonance relaxation times.</a> Cerebrovasc Dis Extra 6. 6, 60-65 (2016).</li><li>Fiehler, J., 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=Severe+ADC+decreases+do+not+predict+irreversible+tissue+damage+in+humans.">Severe ADC decreases do not predict irreversible tissue damage in humans.</a> Stroke. 33, 79-86 (2002).</li><li>Lestro Henriques, I., 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=Intralesional+Patterns+of+MRI+ADC+Maps+Predict+Outcome+in+Experimental+Stroke.">Intralesional Patterns of MRI ADC Maps Predict Outcome in Experimental Stroke.</a> Cerebrovasc Dis. 39, 293-301 (2015).</li><li>Kettunen, M. I., Gr&#246;hn, O. H. J., Silvennoinen, M. J., Penttonen, M., Kauppinen, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+assessment+of+the+balance+between+oxygen+delivery+and+consumption+in+the+rat+brain+after+transient+ischemia+with+T2-BOLD+magnetic+resonance+imaging.">Quantitative assessment of the balance between oxygen delivery and consumption in the rat brain after transient ischemia with T2-BOLD magnetic resonance imaging.</a> J Ceber Blood Flow Metab. 22 (3), 262-270 (2002).</li></ol>

作者没有什么可透露的。

目前对大鼠脑卒中发生时间的估计采用定量扩散和弛豫时间 MRI 数据, 而不是各自加权 mr 对比图像的信号强度19。最近的证据表明, 在估计中风发作时, 图像强度的表现较差14,25。在 ' 扩散阳性 ' 中风病变我们的 mri 协议提供中风发作时间从 qt1和 qt2 mri 数据的准确性为一个半小时左右。qt2数据优于 qt1的一般趋势。从重叠升高的 qt1和 qt2 (V重叠) 的容量中获得最佳的起始时间确定精度。
图 1中的图像显示, 当降低的扩散系数显得相当均匀时, 具有异常的 qt1和 qt2的区域异分散在缺血性病变中。这一发现符合先前的观察, 很可能是由于这些 qMRI 参数对缺血性6引起的病理生理变化的敏感性不同。这表明 qMRI 参数可能是信息的组织状态和支持的概念, DWI 估计缺血性损伤26。事实上, 最近的临床基础证据表明, 在扩散定义的病灶中, 缺血性损伤的异质性为27。因此, 扩散、qt1和 qt2的结合可能会提供有关中风发作时间和组织状态的信息, 这两种情况对于治疗决定不明的患者都有临床意义。
V重叠和 f2给出了最准确的笔画起始时间估计值。量化弛豫时间的好处是, 不同的信号强度, 他们不敏感的固有变化造成的技术因素, 如磁场均匀和质子密度6, 包括预期的磁场在缺血性病变范围内的变异18。由于 qt1对缺血的前述双相位响应, 从而导致时间 qt1的浅斜率下降, 因此与 qt1和 f1的起始时刻估计相关的不确定度可能减少。更改8,15,16。所示的 MRI 数据 (图 2) 与以前的工作是一致的13,14, 因为时间课程的松弛时间的差异, 缺血性和对侧缺脑是充分由线性函数描述。然而, 重要的是要注意, 由于缺血引起的基础流体力学变化不是线性的1,18。
利用姜黄 et al. 程序22, 对受永久性缺血影响的大鼠进行脑卒中时间的 MRI 表现。根据我们的经验, 姜黄 et al. 程序无法诱导10-20% 的大鼠 MCAO, 然而, 由于 ADC 是用来验证缺血的存在, 实验可以提前终止。导致 MCAO 的原因往往是由于封堵器螺纹不完善。另一个导致实验失败的因素是, MCAO 是一个严重的过程, 导致多达20% 的老鼠在长时间的 MRI 期间死亡。
中风发作时间协议只适用于永久性缺血。在大鼠局灶性缺血再灌注中, dav与 qt1或 qt2之间的关系将不作为 dav恢复, 但可能不为 qt1和 qt2 , 取决于缺血前的持续时间再灌注8,28。另外, 由于影响微循环的因素如年龄和疾病 (如、糖尿病、高血压、心脏病), 缺血性损伤的演变在脑卒中患者中可能会有更大的变化。这些因素将不可避免地影响 f1、f2和 V重叠在人笔画中的时间依赖性, 因此需要在临床设置中进行调查。
最后, qMRI 参数提供了中风发病时间的估计。V重叠和 f2提供了最准确的估计, 也可能是组织状态的信息。因此, qMRI 可以在临床上受益于帮助治疗的决定为未知的发病时间的病人。这里要考虑的一个问题是, 大鼠大脑中的 gray-to-white 物质比在人类中要高得多, 而这些脑组织类型的流体力学可能会有不同的18。然而, 对超急性脑卒中患者的 f2、V重叠和 qT2的时间依赖性的进一步调查是有必要的。

由于 ATP 合成和有限的能量储备的氧化磷酸化的高度依赖性, 脑组织特别容易受到缺血的影响。缺血导致的细胞内和细胞外空间的微妙的时变离子的变化, 造成脑水池的重新分布, 释放兴奋神经递质和最终启动破坏性过程1。在局灶性缺血中, 如果血流没有在一定的时间范围内恢复, 那么组织损伤就会扩散到初始核之外. 2。中风发作的时间是目前临床决策的关键标准之一的药物治疗缺血性中风, 包括再通的溶栓剂3。因此, 由于在睡眠期间发生中风 ("唤醒中风"), 缺乏证人, 或不知道症状4,5, 许多患者自动不合格的溶栓治疗。因此, 确定中风发作时间的程序是必要的, 这样病人可以考虑溶栓。
磁共振探头水在体内。动态严重扰动的急性缺血性能量衰竭6。最值得注意的是, 水分子的平移 (热) 运动所受的水的扩散在缺血的早期由于能量衰竭而减少了7。这反过来导致神经细胞缺氧去极化的神经细胞8。磁共振弥散成像 (DWI) 已成为一个金标准诊断成像模式的急性中风9。DWI 信号迅速增加, 以应对缺血, 使缺血性组织被确定, 但没有显示任何 time-dependency 在头几个小时缺血性中风10。同样地, 在缺血性组织中, 如表观扩散系数 (ADC) 或扩散张量 (Dav) 的微量扩散的定量测量, 在动物脑卒中的发生与中风的时间没有关系。模型10和患者11。
定量 MRI (qMRI) 松弛参数, qt1, qt2和 qt1ρ, 受旋转运动和水氢原子交换的控制, 并显示缺血后脑实质的复杂时变变化能量故障6。这种时间依赖性的变化, 使中风发作时估计患者12和动物模型的缺血13,14,15。在大鼠局灶性中风中, qT1ρ在缺血发作后几乎瞬时增加, 并持续线性至少6小时, 13,14。qT1松弛时间在缺血性脑组织中也会增加, 这可以用两个时间常数来描述: 一个初始的快速阶段, 接着是一个缓慢的阶段, 持续时间为小时8,16。由于这种双相增加, 使用 qt1在中风的时间可能比 qt1ρ MRI 15更复杂。qT2弛豫时间也显示大鼠局灶性中风的双期变化, 即在第一个小时内有一个初始的缩短, 其次是线性增加与时间13。最初的缩短可以解释为两个并行运行的因素, 包括: (i) 脱氧的积累导致 so-called 的负氧水平依赖性效应 ' 和 (ii), 细胞外水转移到细胞内空间17,18。qT2的随时间增加可能是由于细胞毒和/或性水肿, 随后细胞内大分子结构的破裂, 18。qt1ρ和 qt2数据都提供了在临床前模型14中准确估计中风发病时间的方法。qT2 12和 T2加权信号强度19,20也被利用在临床设置中风发作时间估计。
除了在定量松弛时间的半球差异, 在缺血区域内升高的松弛时间的空间分布也可作为中风发作时间的替身14。在大鼠脑卒中模型中, qt1ρ、qt2和 qt1松弛时间最初小于扩散定义的缺血性病变, 但随着时间的推移而增加1415, 21。因此, 将高松弛时间的空间分布量化为缺血性病变大小的百分比也能使中风发作时间估计为14,15。在这里, 我们描述的协议, 以确定中风发病时间在大鼠中风模型使用 qMRI 参数。

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td></td>
			<td></td>
			<td>Magnetic Field Strength</td>
			<td>Operation Frequency</td>
		</tr>
		<tr>
			<td>MRI scanner</td>
			<td>Agilent, Santa Clara, CA, USA</td>
			<td>9.4T</td>
			<td>400.13 MHz</td>
		</tr>
		<tr>
			<td>Linear volume transmit RF-coil</td>
			<td>RAPID Biomedical, Rimpar, Germany</td>
			<td>-</td>
			<td>400.13MHz</td>
		</tr>
		<tr>
			<td>Actively decoupled receive coil</td>
			<td>RAPID Biomedical, Rimpar, Germany</td>
			<td>-</td>
			<td>400.13MHz</td>
		</tr>
		<tr>
			<td>Rat head holder</td>
			<td>RAPID Biomedical, Rimpar, Germany</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>i-Stat handheld blood-gas analyzer</td>
			<td>i-Stat Co, East Windsor, NJ, USA</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Pneumatic pillow breathing rate monitor</td>
			<td>SA Instruments Inc, Stony Brook, NY, USA</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Rodent rectal temperarure moniring device</td>
			<td>SA Instruments Inc, Stony Brook, NY, USA</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Name</td>
			<td>Company</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Chemicals</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Isoflurane: Attane Vet 1000mg/g</td>
			<td>Piramal Healthcare UK Ltd, Northumberland, UK</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>2,3,5-Triphenyltetrazolium cholide=TTC</td>
			<td>Sigma-Aldrich, Gillinham, Dorset, UK</td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

a magnetic resonance imaging protocol for stroke onset time estimation in permanent cerebral ischemia

MRI 提供了一种敏感和特异的成像工具, 通过减少脑水的扩散系数来检测急性缺血性中风。在大鼠缺血性中风模型中, 定量 t1和 t2 MRI 松弛时间 (qt1和 qt2) 之间的缺血性病变 (由低扩散划定) 和对侧缺半球的差异增加随着时间的推移中风发作。MRI 弛豫时间差异的时间依赖性是启发式描述的线性函数, 从而提供了一个简单的中风发作时间的估计。此外, 缺血性病变 qt1和 qt2的数量随着时间的推移呈线性增加, 为中风定时提供了一种补充方法。提出了一种基于量化扩散系数的 (半) 自动计算机程序来描述急性缺血性脑卒中组织的分布。此例程还确定了 qt1和 qt2松弛时间的半球差异, 以及异常 qt1和 qt2体在病变中的位置和体积。与 qt1和 qt2 MRI 数据的起始时间估计值有关的不确定因素在第一个5小时的行程中, 从±25分钟到±47分钟不等。最准确的开始时间估计可以通过量化的重叠异常 qt1和 qt2病变卷的体积, 称为 "V重叠" (± 25 min) 或通过量化在 qt2的半球差异放松时间 (±28分钟)。总的来说, qt2派生的参数优于 qt1。目前的 MRI 协议是在超急性期的永久性局灶性缺血模型, 这可能不适用于短暂的局灶脑缺血。

在大鼠的血液气体剖面如下: 所以2 95.8 ± 3.2%, PaCO2 51.6 ±2.9 柱, 和 pH 7.30 ±0.04。
典型的 Dav, qt2和 qt1图像从代表性大鼠的中央切片在4时间点后 MCAO 显示在图 1a的前3面板中。图 1的其他面板中的图像显示了自动检测到的红色缺血性病变和高 qt1的缺血性病变区域, qt2和具有 V重叠的区域显示为绿色。高达 2 h 后 MCAO, 高 qt1内缺血性病变的地区明显大于高 qt2 (p和 #60; 0.01), 但与时间 (图 1) 聚合。缺血性病变由 Dav也大于高 qt 的区域1 (p和 #60; 0.05) 和 qT2 (p和 #60; 0.05) 在前两个小时。
qMRI 参数的时间依赖性如图 2所示。所有 qMRI 参数都是时间后 MCAO 的重要预测因子 (ΔT1: R2 = 0.71, t2: r2 = 0.75, f1: r2 = 0.53, f2: r2 = 0.82, V重叠: R2 = 0.87)。根据每个参数的 RMSE 与中风发病时间估计有关的不确定性是±37分钟的 t1, ±28分钟的 t2, ± 47 min1, ±34分钟 f2, 和±25分钟的 V重叠。因此, V重叠给出了中风发作以来最准确的时间估计。
在 MCAO 证实了在灰质 (图 1d) 中的不可逆转的缺血性损伤后, 6 小时左右大脑样本的 TTC 染色。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/55277/55277fig1.jpg"> 
图 1: 一例大鼠缺血性中风引起的 qMRI 参数变化.(a) 显示在4小时缺血期间 qMRI 图像的示例。前四列分别显示 Dav映射、qt2映射、qt1映射和 T2加权图像。剩余的列显示 Dav映射, 其中包含自动分段病灶的各种表示。自动检测到的 Dav病变显示在红色的5列中。在6列中, Dav病变以红色显示, 体以绿色显示高 qT2 。在7列中, Dav病变以红色显示, 高 qT1体以绿色显示。在8列中, Dav病变以红色显示, 体与高架的 qt1和 qt2 (V重叠) 以绿色显示。(b) 显示在 Dav病变中 qt2的分布, 作为时间后 MCAO 的函数, 以及 non-lesion qt2在时间上为零的分布。(c) 显示相应的 qT1分布, 即与两个面板 (b) 和 (c) 相关的相邻图例。(d) 在 6 h 后 MCAO 的动物被牺牲后, 显示了一个 TTC 染色的脑切片。<a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55277/55277fig1large.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/55277/55277fig2.jpg"> 
图 2: 时间后 MCAO 和 qMRI 参数之间的关系与缺血时间有关.(a) 显示 f1、b、f2、(c)、V重叠、(d)、t1和 (e)、t2。最适合每个参数 (实心红线) 和 RMSE 条 (实心黑线) 显示。虚线代表每一个 indivudual 5 大鼠受 MCAO。<a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55277/55277fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>

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A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia

介绍了一种利用定量磁共振成像 (qMRI) 参数的大鼠脑卒中发作时间估计方法。该程序利用扩散 MRI 来划定急性中风病变和定量的 t1和 t2 (qt1和 qt2) 的时间中风的时机。

脑缺血中风发作时间估计的磁共振成像协议

MRI provides a sensitive and specific imaging tool to detect acute ischemic stroke by means of a reduced diffusion coefficient of brain water. In a rat ...

a-magnetic-resonance-imaging-protocol-for-stroke-onset-time

Nanyang Technological University

Research

JoVE Journal

Neuroscience

14.0K 次观看.  University of Bristol. 介绍了一种利用定量磁共振成像 (qMRI) 参数的大鼠脑卒中发作时间估计方法。该程序利用扩散 MRI 来划定急性中风病变和定量的 t1和 t2 (qt1和 qt2) 的时间中风的时机。

视频: A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia

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

Multiple-mouse Neuroanatomical Magnetic Resonance Imaging

The field of mouse phenotyping with magnetic resonance imaging (MRI) is rapidly growing, motivated by the need for improved tools for characterizing and evaluating mouse models of human disease. MRI is an excellent modality for investigating genetically altered animals. It is capable of whole brain coverage, can be used in vivo, and provides multiple contrast mechanisms for investigating different aspects of neuranatomy and physiology. The advent of high-field scanners along with the ability to scan multiple mice simultaneously allows for rapid phenotyping of novel mutations.
Effective mouse MRI studies require attention to many aspects of experiment design. In this article, we will describe general methods to acquire quality images for mouse phenotyping using a system that images mice concurrently in shielded transmit/receive radio frequency (RF) coils in a common magnet (Bock et al., 2003). We focus particularly on anatomical phenotyping, an important and accessible application that has shown a high potential for impact in many mouse models at our imaging centre. Before we can provide the detailed steps to acquire such images, there are important practical considerations for both in vivo brain imaging (Dazai et al., 2004) and ex vivo brain imaging (Spring et al., 2007) that should be noted. These are discussed below.

Magnetic resonance imaging (MRI) has become an increasingly popular tool for examining the phenotype of genetically altered mice. This article illustrates the methods necessary to achieve high-throughput phenotyping of genetically altered mice using multiple-mouse MRI.

多鼠神经解剖学磁共振成像

The field of mouse phenotyping with magnetic resonance imaging (MRI) is rapidly growing, motivated by the need for improved tools for characterizing and ...

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 ...

The Use of Magnetic Resonance Spectroscopy as a Tool for the Measurement of Bi-hemispheric Transcranial Electric Stimulation Effects on Primary Motor Cortex Metabolism

Transcranial direct current stimulation (tDCS) is a neuromodulation technique that has been increasingly used over the past decade in the treatment of neurological and psychiatric disorders such as stroke and depression. Yet, the mechanisms underlying its ability to modulate brain excitability to improve clinical symptoms remains poorly understood 33. To help improve this understanding, proton magnetic resonance spectroscopy (1H-MRS) can be used as it allows the in vivo quantification of brain metabolites such as &#947;-aminobutyric acid (GABA) and glutamate in a region-specific manner 41. In fact, a recent study demonstrated that 1H-MRS is indeed a powerful means to better understand the effects of tDCS on neurotransmitter concentration 34. This article aims to describe the complete protocol for combining tDCS (NeuroConn MR compatible stimulator) with 1H-MRS at 3 T using a MEGA-PRESS sequence. We will describe the impact of a protocol that has shown great promise for the treatment of motor dysfunctions after stroke, which consists of bilateral stimulation of primary motor cortices 27,30,31. Methodological factors to consider and possible modifications to the protocol are also discussed.

This article aims to describe a basic protocol for combining transcranial direct current stimulation (tDCS) with proton magnetic resonance spectroscopy (1H-MRS) measurements to investigate the effects of bilateral stimulation on primary motor cortex metabolism.

磁共振波谱的用途，用于对初级运动皮层新陈代谢双半球经颅电刺激效果的测量工具一

Transcranial direct current stimulation (tDCS) is a neuromodulation technique that has been increasingly used over the past decade in the treatment of ...

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

The human hippocampus has been broadly studied in the context of memory and normal brain function and its role in different neuropsychiatric disorders has been heavily studied. While many imaging studies treat the hippocampus as a single unitary neuroanatomical structure, it is, in fact, composed of several subfields that have a complex three-dimensional geometry. As such, it is known that these subfields perform specialized functions and are differentially affected through the course of different disease states. Magnetic resonance (MR) imaging can be used as a powerful tool to interrogate the morphology of the hippocampus and its subfields. Many groups use advanced imaging software and hardware (&#62;3T) to image the subfields; however this type of technology may not be readily available in most research and clinical imaging centers. To address this need, this manuscript provides a detailed step-by-step protocol for segmenting the full anterior-posterior length of the hippocampus and its subfields: cornu ammonis (CA) 1, CA2/CA3, CA4/dentate gyrus (DG), strata radiatum/lacunosum/moleculare (SR/SL/SM), and subiculum. This protocol has been applied to five subjects (3F, 2M; age 29-57, avg. 37). Protocol reliability is assessed by resegmenting either the right or left hippocampus of each subject and computing the overlap using the Dice&#39;s kappa metric. Mean Dice&#39;s kappa (range) across the five subjects are: whole hippocampus, 0.91 (0.90-0.92); CA1, 0.78 (0.77-0.79); CA2/CA3, 0.64 (0.56-0.73); CA4/dentate gyrus, 0.83 (0.81-0.85); strata radiatum/lacunosum/moleculare, 0.71 (0.68-0.73); and subiculum 0.75 (0.72-0.78). The segmentation protocol presented here provides other laboratories with a reliable method to study the hippocampus and hippocampal subfields in vivo using commonly available MR tools.

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 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 ...

Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning

Magnetic resonance imaging (MRI) allows for the delineation between normal and abnormal tissue on a macroscopic scale, sampling an entire tissue volume three-dimensionally. While MRI is an extremely sensitive tool for detecting tissue abnormalities, association of signal changes with an underlying pathological process is usually not straightforward. In the central nervous system, for example, inflammation, demyelination, axonal damage, gliosis, and neuronal death may all induce similar findings on MRI. As such, interpretation of MRI scans depends on the context, and radiological-histopathological correlation is therefore of the utmost importance. Unfortunately, traditional pathological sectioning of brain tissue is often imprecise and inconsistent, thus complicating the comparison between histology sections and MRI. This article presents novel methodology for accurately sectioning primate brain tissues and thus allowing precise matching between histology and MRI. The detailed protocol described in this article will assist investigators in applying this method, which relies on the creation of 3D printed brain slicers. Slightly modified, it can be easily implemented for brains of other species, including humans.

The overall goal of this protocol is to accurately align magnetic resonance imaging (MRI) image volumes with histology sections via the creation of customized 3D-printed brain holders and slicer boxes.

利用3D打印技术来合并MRI与组织学:一个大脑切片协议

Magnetic resonance imaging (MRI) allows for the delineation between normal and abnormal tissue on a macroscopic scale, sampling an entire tissue volume ...

Evaluation of Bioenergetic Function in Cerebral Vascular Endothelial Cells

The integrity of the blood-brain-barrier (BBB) is critical to prevent brain injury. Cerebral vascular endothelial (CVE) cells are one of the cell types that comprise the BBB; these cells have a very high-energy demand, which requires optimal mitochondrial function. In the case of disease or injury, the mitochondrial function in these cells can be altered, resulting in disease or&#160;the opening of the BBB. In this manuscript, we introduce a method to measure mitochondrial function in CVE cells by using whole, intact cells and a bioanalyzer. A mito-stress assay is used to challenge the cells that have been perturbed, either physically or chemically, and evaluate their bioenergetic function. Additionally, this method also provides a useful way to screen new therapeutics that have direct effects on mitochondrial function. We have optimized the cell density necessary to yield oxygen consumption rates that allow for the calculation of a variety of mitochondrial parameters, including ATP production, maximal respiration, and spare capacity. We also show the sensitivity of the assay by demonstrating that the introduction of the&#160;microRNA, miR-34a, leads to a pronounced and detectable decrease in mitochondrial activity. While the data shown in this paper is optimized for the bEnd.3 cell line, we have also optimized the protocol for primary CVE cells, further suggesting the utility in preclinical and clinical models.

Endothelial cell mitochondria are critical to maintain blood-brain-barrier integrity. We introduce a protocol to measure bioenergetic function in cerebral vascular endothelial cells.

在脑血管内皮细胞生物能量功能的评价

The integrity of the blood-brain-barrier (BBB) is critical to prevent brain injury. Cerebral vascular endothelial (CVE) cells are one of the cell types ...

Online Transcranial Magnetic Stimulation Protocol for Measuring Cortical Physiology Associated with Response Inhibition

We describe the development of a reproducible, child-friendly motor response inhibition task suitable for online Transcranial Magnetic Stimulation (TMS) characterization of primary motor cortex (M1) excitability and inhibition. Motor response inhibition prevents unwanted actions and is abnormal in several neuropsychiatric conditions. TMS is a non-invasive technology that can quantify M1 excitability and inhibition using single- and paired-pulse protocols and can be precisely timed to study cortical physiology with high temporal resolution. We modified the original Slater-Hammel (S-H) stop signal task to create a &#34;racecar&#34; version with TMS pulses time-locked to intra-trial events. This task is self-paced, with each trial initiating after a button push to move the racecar towards the 800 ms target. GO trials require a finger-lift to stop the racecar just before this target. Interspersed randomly are STOP trials (25%) during which the dynamically adjusted stop signal prompts subjects to prevent finger-lift. For GO trials, TMS pulses were delivered at 650 ms after trial onset; whereas, for STOP trials, the TMS pulses occurred 150 ms after the stop signal. The timings of the TMS pulses were decided based on electroencephalography (EEG) studies showing event-related changes in these time ranges during stop signal tasks. This task was studied in 3 blocks at two study sites (n=38) and we recorded behavioral performance and event-related motor-evoked potentials (MEP). Regression modelling was used to analyze MEP amplitudes using age as a covariate with multiple independent variables (sex, study site, block, TMS pulse condition [single- vs. paired-pulse], trial condition [GO, successful STOP, failed STOP]). The analysis showed that TMS pulse condition (p&#60;0.0001) and its interaction with trial condition (p=0.009) were significant. Future applications for this online S-H/TMS paradigm include the addition of simultaneous EEG acquisition to measure TMS-evoked EEG potentials. A potential limitation is that in children, the TMS pulse sound could&#160;affect behavioral task performance.

We describe an experimental procedure to quantify excitability and inhibition of primary motor cortex during a motor response inhibition task by using Transcranial Magnetic Stimulation throughout the course of a Stop Signal Task.

在线经颅磁刺激测量与反应抑制相关的皮质生理

We describe the development of a reproducible, child-friendly motor response inhibition task suitable for online Transcranial Magnetic Stimulation (TMS) ...

Diffusion Tensor Magnetic Resonance Imaging in Chronic Spinal Cord Compression

Chronic spinal cord compression is the most common cause of spinal cord impairment in patients with nontraumatic spinal cord damage. Conventional magnetic resonance imaging (MRI) plays an important role in both confirming the diagnosis and evaluating the degree of compression. However, the anatomical detail provided by conventional MRI is not sufficient to accurately estimate neuronal damage and/or assess the possibility of neuronal recovery in chronic spinal cord compression patients. In contrast, diffusion tensor imaging (DTI) can provide quantitative results according to the detection of water molecule diffusion in tissues. In the present study, we develop a methodological framework to illustrate the application of DTI in chronic spinal cord compression disease. DTI fractional anisotropy (FA), apparent diffusion coefficients (ADCs), and eigenvector values are useful for visualizing microstructural pathological changes in the spinal cord. Decreased FA and increases in ADCs and eigenvector values were observed in chronic spinal cord compression patients compared to healthy controls. DTI could help surgeons understand spinal cord injury severity and provide important information regarding prognosis and neural functional recovery. In conclusion, this protocol provides a sensitive, detailed, and noninvasive tool to evaluate spinal cord compression.

Here, we present a protocol for the application of diffusion tensor imaging parameters to evaluate spinal cord compression.

扩散张量磁共振成像在慢性脊髓压迫中的应用

Chronic spinal cord compression is the most common cause of spinal cord impairment in patients with nontraumatic spinal cord damage. Conventional magnetic ...