该材料是根据工作部分由美国国家科学基金会的支持下批准号：IIS0758410。卡罗来纳医疗保健系统提供的数据。

1。方法概述建议的框架创伤性脑损伤（TBI）患者的脑CT图像进行处理，自动计算在病理情况下，中线移位，使用它，以及其他提取的信息来预测颅内压（ICP）。 图1显示了整个示意图框架。自动化的中线偏移测量可以分为三个步骤。首先，理想的中线的大脑， 也就是受伤前正中线，通过分层搜索根据头骨的对称性和组织功能3。其次，脑室系统分割为每一个脑CT图像4。第三，实际中线估计从分段变形的脑室系统使用的形状匹配的方法5。水平移位的脑室系统然后基于估计了理想的中线和实际中线估计。经t他相继估计中线移位，中线结构移位，CT图像的纹理信息，以及其他人口信息的功能，包括用于预测ICP。机器学习算法用于ICP和所提取的特征6之间的关系进行建模。 2。理想的中线估计<ol><li>这一步检测的近似理想的中线对称的头骨。首先，使用灰度阈值，颅骨需要从CT图像的其余部分中的内容的分割。在这之后，进行一个彻底的搜索，以确定中心的头骨周围群众的旋转角度。的最佳旋转角被定义为角最大化的对称性颅骨所得半。的近似理想的中线是质心点的线穿过，并具有最佳相对于原始的CT图像的垂直方向上的旋转角。 </li><li>此步骤中，检测的posterior大脑镰前镰附件的矢状沟的边缘。此步骤进行细致识别的近似理想的中线。首先定义两个搜索矩形集中在两个交叉点之间的近似理想的中线和颅骨。下一步，选择大小的矩形经验，使其覆盖被检测到的解剖特点，解释如下。的棱线上的颅骨和大脑镰被检测为在后方区域3的灰线的峰值点检测到的前镰附件。 </li><li>此步骤使用以上这些功能的检测，完善的理想的中线位置。一旦峰值点的前镰附件的和最远点后大脑镰的calvarum，成品理想的中线是连接两点的线。 </li></ol> 3。心室图像的分割<ol><li>首先将低了VEL分割使用高斯混合模型（GMM）为每个CT片4,7。可以分为4种类型的组织：骨/血液，脑脊髓液（CSF），灰质和白质的CT图像。有关初始化的高斯混合模型，参数估计的基础上的CT图像的一个迭代的K-means分割结果。然后用期望最大化（EM）迭代的方法来优化GMM CT图像能够更好地代表。 CT图像分割成的基础上，每个像素属于不同的区域类型的成员的最大概率的区域，可以通过以下方式获得的硬分割结果。 </li><li>低层次分割的GMM后，将进一步限制的分割结果，以便识别心室地区。只有一定的阈值以上的大小的心室的区域被保留。应用约束心室区域的位置上，以及使用的大脑边界框和组ventriclË模板。提取的的心室模板，从一个标准的脑MR图像，然后放大它利用形态的扩张，以适应不同的主题和病理情况下的变化。 </li></ol> 4。实际中线估计<ol><li>指定的特征点上的提取心室模板，从MR。 </li><li>不要多地区之间的分割脑室和MR模板形状匹配的5,8。 </li><li>心室使用形状匹配的形状的识别上的特征点的基础上，估计实际的中线。然后使用左侧均值和右侧的平均值的平均值，这些特征点的x坐标的定义的x坐标的中线。 </li></ol> 5。更多特征提取<ol><li>测量颅内血肿/出血量高斯混合模型（GMM）从CT图像分割结果的基础上。分割结果可clude包括静脉窦血液和大脑镰的小区域，但，血肿的区域相比，它们通常可以被忽略。然后列为血液为每个切片的像素的数目进行计数，并总结起来。的最后一笔量化淤血，在CT检查量。 </li><li>提取纹理特征。首先选择6个窗口在每个CT图像捕捉到的灰质和白质，但避免血液和心室结构的CT图像， 见图6。然后提取相应的纹理特征，使用下面的方法：的灰度运行长度为9，直方图分析，傅立叶分析，偶树复小波分析10。 </li><li>还收集人口统计信息和损伤严重度评分。 </li><li>每个CT图像所提取的特征总代表整个CT检查。具体而言， 最小（F），最大（F），中位数（F），平均（F），STD（F）计算之间的人升的所选功能属于特定的CT检查， 例如 ƒ中线移位或纹理特征的特征。有关的颅内出血量功能，除了上面列出的5个运算符， 和（f）是还添加记录的总血量。 </li></ol> 6。 ICP估计。 ICP估计的主要思想是采用机器学习技术，以建立一个模型，根据一组训练样本。然后建立的模型上的其它的试验样品进行评估。由于高维提取的特征，包括那些从CT扫描和人口信息，特征选择是非常重要的，删除不相关的功能，从而稳定一个相对简单的模型。因此，有两个步骤进行ICP估计/预测。首先，选择相对的特点，预测互联网内容提供商的信息。第二个步骤是使用支持向量机（SVM）的学习算法来开发和评估的人才培养模式。软件是这项任务的理想选择，因为它是一个很好的开发工具对于大多数的机器学习算法，并提供了非常强大的培训和评估模型的接口，如RapidMiner 11。 <ol><li>分两个阶段执行的功能选择。首先，用信息增益率在第一阶段的标准，选择排名前50位的功能。在第二阶段，使用遗传算法结合SVM的特点，进一步优化选择。然后使用最后一组选定的功能在下面的步骤中建立的模型ICP预测。 </li><li>执行ICP通过机器学习技术的分类和评价。在图8所示的顶层图的培训和测试RapidMiner。应用10折交叉验证方案进行评估的最外层。为了建立一个模型具有较好的泛化，避免过度拟合吨他的训练数据，在每个训练倍嵌套另一个层的交叉验证。在这些模块中，首先应用特征选择上述过程，并与自己的参数选择模块，然后使用SVM进行分类。 </li></ol>

<ol>
	<li>Langlois, J. A., Rutland-Brown, W., Thomas, K. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Traumatic brain injury in the united states: emergency department visits, hospitalizations, and deaths. , (2006).</li><li>Moore, E. E., Feliciano, D. V., Mattox, K. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Trauma. , (2003).</li><li>Chen, W., Smith, R., Ji, S. Y., Ward, K. R., Najarian, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+Ventricular+Systems+Segmentation+in+Brain+CT+Images+by+Combining+Low-level+Segmentation+and+High-level+Template+Matching.">Automated Ventricular Systems Segmentation in Brain CT Images by Combining Low-level Segmentation and High-level Template Matching.</a> BMC Medical Informatics and Decision Making. 9, (2009).</li><li>Chen, W., Najarian, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Segmentation+of+Ventricles+in+Brain+CT+Images+Using+Gaussian+Mixture+Model+Method.">Segmentation of Ventricles in Brain CT Images Using Gaussian Mixture Model Method.</a> , 15-20 (2009).</li><li>Chen, W., Ward, K. R., Najarian, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Actual+Midline+Estimation+from+Brain+CT+Scan+Using+Multiple+Regions+Shape+Matching.">Actual Midline Estimation from Brain CT Scan Using Multiple Regions Shape Matching.</a> , 2552-2555 (2010).</li><li>Chen, W., Cockrell, C., Ward, K. R., Najarian, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Intracranial+Pressure+Level+Prediction+in+Traumatic+Brain+Injury+by+Extracting+Features+from+Multiple+Sources+and+Using+Machine+Learning+Methods.">Intracranial Pressure Level Prediction in Traumatic Brain Injury by Extracting Features from Multiple Sources and Using Machine Learning Methods.</a> , 510-515 (2010).</li><li>Greenspan, H., Ruf, A., Goldberger, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Constrained+Gaussian+mixture+model+framework+for+automatic+segmentation+of+MR+brain+images.">Constrained Gaussian mixture model framework for automatic segmentation of MR brain images.</a> IEEE Trans. Med. Imaging. 25 (9), 1233-1245 (2006).</li><li>Belongie, S., Malik, J., Puzicha, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Shape+matching+and+object+recognition+using+shape+contexts.">Shape matching and object recognition using shape contexts.</a> IEEE Trans. Pattern Anal. Mach. Intell. 24, 509-522 (2002).</li><li>Weszaka, J. S., Dyer, C. R., Rosenfeld, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+comparative+study+of+texture+measures+for+terrain+classification.">A comparative study of texture measures for terrain classification.</a> IEEE Trans. on Syst., Man, Cyber. , (1976).</li><li>Kingsbury, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Complex+wavelets+for+shift+invariant+analysis+and+filtering+of+signals.">Complex wavelets for shift invariant analysis and filtering of signals.</a> Applied and Computational Harmonic Analysis. 10 (3), 234-253 (2002).</li><li>Mierswa, I., Wurst, M., Klinkenberg, R., Scholz, M., Euler, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=+Yale:+Rapid+prototyping+for+complex+data+mining+tasks."> Yale: Rapid prototyping for complex data mining tasks.</a> , 935-940 (2006).</li></ol>

没有利益冲突的声明。

在这项研究中，直观和灵活的框架建议，以解决具有挑战性的问题：在CT图像的中线移位和ICP预测的基础上提取的特征的估计。评价结果表明，所提出的方法的有效性。据我们所知，这是第一次有系统的研究，解决了这两个问题。我们注意到，总体框架的基础上，有许多潜在的改进，可以实现。例如，在建议的分割，低层次分割和高层次的认知是分开的，目前还没有反馈，从高层次到低层次分割?...

每年有大约140万相关的创伤性脑损伤（TBI）急诊情况下，在美国，其中，超过50,000名死亡1。通常伴随着严重的脑外伤血肿和脑组织肿胀的症状，如颅内压（ICP）的增加。这些结果在脑灌注压降低，脑血流，脑损伤将额外的风险。严重ICP增长的可能是致命的，所以，监测ICP TBI患者是至关重要的。通常，这要求直接进入大脑的压力进行监测，有风险的程序只能在专门的医疗中心进行的患者的留置导管的位置。该过程还涉及风险，如感染。然而，一些迹象显示，可能是显着升高的ICP医疗成像。特别是，中线移位往往是与增加在ICP和可以捕获从脑吨omography（CT）图像。因此，这些图像提供了一个机会，ICP升高的非侵入性的检测，它可以用来作为一个预检颅环钻步骤之前。 CT成像仍然是TBI评估在所有其他的成像方式， 如 MRI初步的金标准，由于其较高的速度和相对低廉的成本2。此外，CT检查并不需要严格的病人不动，有利于揭示严重的异常如骨骨折和血肿。中线移位而CT通常用于检测的伤害在大脑中，根据目前的技术，还没有自动测量，因此医师必须评估这一重要因素，通过视觉检查。不准确或不一致CT解释往往是与人类视觉系统的性质和结构复杂的大脑。虽然小中线的变化是难以捉摸的，他们往往是非常宝贵的脑损伤评估，在P关节损伤之前，患者的病情在早期阶段会变得更加严重。在光谱的另一端，大中线移位建议高度ICP升高，更严重的TBI。然而，这是一个非常具有挑战性的任务，为人类目视检查CT图像和定量预测水平的ICP。由于在自动计算技术的进步，从CT图像，如中线结构移位，血肿量，脑CT图像和纹理特征提取，可以精确地测量并自动采用先进的图像处理方法。然而，ICP，中线移位以及其他功能，如出血程度之间的关系，从CT图像的质感没有被探索。本文的计算框架被提出来测量中线移位，测量以及其他生理/解剖特征的脑CT图像，然后预测的程度，ICP，非侵入性的使用机器学习技术。

automated midline shift and intracranial pressure estimation based on brain ct images

在本文中，我们提出了一个自动化系统主要基于计算机断层扫描（CT）图像由两个主要部分组成：中线移位估计和颅内压（ICP）的预先筛分系统。估计中线移位，首先的理想中线的对称性颅骨和脑CT扫描的解剖特征的基础上进行估计。然后，分割进行从CT扫描的心室和用作识别的实际中线通过形状匹配的导向。这些过程模仿由医师的测量过程，并已显示出了有前途的结果在评价。在第二部分中，提取相关的ICP更多的功能，如纹理信息，从CT扫描和其他记录的功能，如年龄，损伤严重度评分估计ICP血液量也成立。机器学习技术，包括特征选择和分类，如支持向量机（SVM），使用RapidMiner，建立预测模型。的预测评价显示了潜在的有用的模型。估计理想的中线结构移位及预测ICP水平，可作为一个快速预筛选步骤的医生作出决定，因此，建议或反对侵入颅内压监测。

测试CT数据集提供了卡罗来纳州医疗保健系统（CHS）根据机构审查委员会的批准。所有受试者被诊断为轻度至重度脑外伤时，首先送往医院接受治疗。对于每一个病人，被记录的ICP值每隔一小时，用ICP心室区域内之前和之后得到的CT扫描探针。要关联的的ICP价值与每一个CT扫描，CT扫描的时间平均距离最近的两个测量ICP，这两者都是在一个小时内的CT扫描。然后分配在CT扫描的时间的平均值作为估计?...

Watch this Scientific Journal Video about Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images at JoVE.com

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

一个自动化的中线移位估计和颅内压（ICP）计算机断层扫描（CT）图像与创伤性脑损伤（TBI）患者的预先筛分系统的基础上，提出一种利用图像处理和机器学习技术。

根据脑CT图像的自动中线移位和颅内压的估计

In this paper we present an automated system based mainly on the computed tomography (CT) images consisting of two main components: the midline shift ...

automated-midline-shift-intracranial-pressure-estimation-based-on

Research

JoVE Journal

Medicine

42.2K 次观看.  Virginia Commonwealth University. 一个自动化的中线移位估计和颅内压（ICP）计算机断层扫描（CT）图像与创伤性脑损伤（TBI）患者的预先筛分系统的基础上，提出一种利用图像处理和机器学习技术。

视频: Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Epidural Intracranial Pressure Measurement in Rats Using a Fiber-optic Pressure Transducer

Elevated intracranial pressure (ICP) is a significant problem in several forms of ischemic brain injury including stroke, traumatic brain injury and cardiac arrest. This elevation may result in further neurological injury, in the form of transtentorial herniation1,2,3,4, midbrain compression, neurological deficit or increased cerebral infarct2,4. Current therapies are often inadequate to control elevated ICP in the clinical setting5,6,7 . Thus there is a need for accurate methods of ICP measurement in animal models to further our understanding of the basic mechanisms and to develop new treatments for elevated ICP.
In both the clinical and experimental setting ICP cannot be estimated without direct measurement. Several methods of ICP catheter insertion currently exist. Of these the intraventricular catheter has become the clinical 'gold standard' of ICP measurement in humans8. This method involves the partial removal of skull and the instrumentation of the catheter through brain tissue. Consequently, intraventricular catheters have an infection rate of 6-11%9. For this reason, subdural and epidural cannulations have become the preferred methods in animal models of ischemic injury. 
Various ICP measurement techniques have been adapted for animal models, and of these, fluid-filled telemetry catheters10 and solid state catheters are the most frequently used11,12,13,14,15. The fluid-filled systems are prone to developing air bubbles in the line, resulting in false ICP readings. Solid state probes avoid this problem (Figure 1). An additional problem is fitting catheters under the skull or into the ventricles without causing any brain injury that might alter the experimental outcomes. Therefore, we have developed a method that places an ICP catheter contiguous with the epidural space, but avoids the need to insert it between skull and brain. 
An optic fibre pressure catheter (420LP, SAMBA Sensors, Sweden) was used to measure ICP at the epidural location because the location of the pressure sensor (at the very tip of the catheter) was found to produce a high fidelity ICP signal in this model. There are other manufacturers of similar optic fibre technologies13 that may be used with our methodology. Alternative solid state catheters, which have the pressure sensor located at the side of the catheter tip, would not be appropriate for this model as the signal would be dampened by the presence of the monitoring screw. 
Here, we present a relatively simple and accurate method to measure ICP. This method can be used across a wide range of ICP related animal models.

A novel technique to record the pressures within the skull is described. The minimally invasive method uses a fibre-optic pressure sensing system to accurately measure intracranial pressure (ICP) in anaesthetized rats without causing significant brain trauma. The technique may be used in a wide range of experimental models.

硬膜外颅内压测量中使用的光纤压力传感器的大鼠

Elevated intracranial pressure (ICP) is a significant problem in several forms of ischemic brain injury including stroke, traumatic brain injury and ...

科研

医学

A Novel High-resolution In vivo Imaging Technique to Study the Dynamic Response of Intracranial Structures to Tumor Growth and Therapeutics

We have successfully integrated previously established Intracranial window (ICW) technology 1-4 with intravital 2-photon confocal microscopy to develop a novel platform that allows for direct long-term visualization of tissue structure changes intracranially. Imaging at a single cell resolution in a real-time fashion provides supplementary dynamic information beyond that provided by standard end-point histological analysis, which looks solely at 'snap-shot' cross sections of tissue.
Establishing this intravital imaging technique in fluorescent chimeric mice, we are able to image four fluorescent channels simultaneously. By incorporating fluorescently labeled cells, such as GFP+ bone marrow, it is possible to track the fate of these cells studying their long-term migration, integration and differentiation within tissue. Further integration of a secondary reporter cell, such as an mCherry glioma tumor line, allows for characterization of cell:cell interactions. Structural changes in the tissue microenvironment can be highlighted through the addition of intra-vital dyes and antibodies, for example CD31 tagged antibodies and Dextran molecules.
Moreover, we describe the combination of our ICW imaging model with a small animal micro-irradiator that provides stereotactic irradiation, creating a platform through which the dynamic tissue changes that occur following the administration of ionizing irradiation can be assessed.
Current limitations of our model include penetrance of the microscope, which is limited to a depth of up to 900 &mu;m from the sub cortical surface, limiting imaging to the dorsal axis of the brain. The presence of the skull bone makes the ICW a more challenging technical procedure, compared to the more established and utilized chamber models currently used to study mammary tissue and fat pads 5-7. In addition, the ICW provides many challenges when optimizing the imaging.

A Novel High-resolution In vivo Imaging Technique to Study the Dynamic Response of Intracranial Structures to Tumor Growth and Therapeutics

We describe a novel in vivo imaging technique that couples fluorescent chimeric mice with intracranial windows and high-resolution 2-photon microscopy. This imaging platform aids studies of dynamic changes in brain tissue and microvasculature, at a single-cell level, following pathological insults and is adaptable to assess intracranial drug delivery and distribution.

一种新型的高分辨率<em&gt;在体内</em&gt;成像技术研究肿瘤生长及治疗颅内结构的动态响应

We have successfully integrated previously established Intracranial window (ICW) technology 1-4 with intravital 2-photon confocal microscopy to develop a ...

Creating Anatomically Accurate and Reproducible Intracranial Xenografts of Human Brain Tumors

Orthotopic tumor models are currently the best way to study the characteristics of a tumor type, with and without intervention, in the context of a live animal &#8211;&#160;particularly in sites with unique physiological and architectural qualities such as the brain. In vitro and ectopic models cannot account for features such as vasculature, blood brain barrier, metabolism, drug delivery and toxicity, and a host of other relevant factors. Orthotopic models have their limitations too, but with proper technique tumor cells of interest can be accurately engrafted into tissue that most closely mimics conditions in the human brain. By employing methods that deliver precisely measured volumes to accurately defined locations at a consistent rate and pressure, mouse models of human brain tumors with predictable growth rates can be reproducibly created and are suitable for reliable analysis of various interventions. The protocol described here focuses on the technical details of designing and preparing for an intracranial injection, performing the surgery, and ensuring successful and reproducible tumor growth and provides starting points for a variety of conditions that can be customized for a range of different brain tumor models.

The brain is a unique site with qualities that are not well represented by in vitro or ectopic analyses. Orthotopic mouse models with reproducible location and growth characteristics can be reliably created with intracranial injections using a stereotaxic fixation instrument and a low pressure syringe pump.

创建精确的解剖学和人脑肿瘤的重现性颅内移植瘤

Orthotopic tumor models are currently the best way to study the characteristics of a tumor type, with and without intervention, in the context of a live ...

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 ...

Proximal Cadaveric Femur Preparation for Fracture Strength Testing and Quantitative CT-based Finite Element Analysis

Cadaveric fracture testing is routinely used to understand factors that affect proximal femur strength. Because ex vivo biological tissues are prone to lose their mechanical properties over time, specimen preparation for experimental testing must be performed carefully to obtain reliable results that represent in vivo conditions. For that reason, we designed a protocol and a set of fixtures to prepare the femoral specimens such that their mechanical properties experienced minimal changes. The femora were kept in a frozen state except during preparation steps and mechanical testing. The relevant clinical measures of total hip and femoral neck bone mineral density (BMD) were obtained with a clinical dual X-ray absorptiometry (DXA) bone densitometer, and the 3D geometry and distribution of bone mineral were obtained using CT with a calibration phantom for quantitative estimations based on the greyscale values. Any possible bone disease, fracture, or the presence of implants or artifacts affecting the bone structure, was ruled out with X-ray scans. For preparation, all bones were carefully cleaned of excess soft tissue, and were cut and potted at the internal rotation angle of interest. A cutting fixture allowed the distal end of the bone to be cut off leaving the proximal femur at a desired length. To allow positioning of the femoral neck at prescribed angles during later CT scanning and mechanical testing, the proximal femoral shafts were potted in polymethylmethacrylate (PMMA) using a fixture designed specifically for desired orientations. The data collected from our experiments were then used for validation of quantitative computed tomography (QCT)-based finite element analysis (FEA), as described in a different protocol. In this manuscript, we present the protocol for the precise bone preparation for mechanical testing and subsequent QCT/FEA modeling. The current protocol was successfully applied to prepare about 200 cadaveric femora over a 6-year time period.

We present a robust protocol on how to carefully preserve and prepare cadaveric femora for fracture testing and quantitative computed tomography imaging. The method provides precise control over input conditions for the purpose of determining relationships between bone mineral density, fracture strength, and defining finite element model geometry and properties.

近端股骨尸制备基于CT的断裂强度测试和定量的有限元分析

Cadaveric fracture testing is routinely used to understand factors that affect proximal femur strength.  Because ex vivo biological tissues are prone to ...

Determining Glucose Metabolism Kinetics Using 18F-FDG Micro-PET/CT

This paper describes the use of 18F-FDG and micro-PET/CT imaging to determine in vivo glucose metabolism kinetics in mice (and is transferable to rats). Impaired uptake and metabolism of glucose in multiple organ systems due to insulin resistance is a hallmark of type 2 diabetes. The ability of this technique to extract an image-derived input function from the vena cava using an iterative deconvolution method eliminates the requirement of the collection of arterial blood samples. Fitting of tissue and vena cava time activity curves to a two-tissue, three compartment model permits the estimation of kinetic micro-parameters related to the 18F-FDG uptake from the plasma to the intracellular space, the rate of transport from intracellular space to plasma and the rate of 18F-FDG phosphorylation. This methodology allows for multiple measures of glucose uptake and metabolism kinetics in the context of longitudinal studies and also provides insights into the efficacy of therapeutic interventions.

Determining Glucose Metabolism Kinetics Using 18F-FDG Micro-PET/CT

This study describes a protocol that uses 18F-FDG and positron emission tomography/computed tomography (PET/CT) imaging, together with kinetic modelling, to quantify the in vivo, real-time uptake of 18F-FDG into tissues.

确定葡萄糖代谢动力学研究<sup&gt; 18</sup&gt; F-FDG微PET / CT

This paper describes the use of 18F-FDG and micro-PET/CT imaging to determine in vivo glucose metabolism kinetics in mice (and is transferable to rats). ...

Improved Method for the Establishment of an In Vitro Blood-Brain Barrier Model Based on Porcine Brain Endothelial Cells

The aim of this protocol presents an optimized procedure for the purification and cultivation of pBECs and to establish in vitro blood-brain barrier (BBB) models based on pBECs in mono-culture (MC), MC with astrocyte-conditioned medium (ACM), and non-contact co-culture (NCC) with astrocytes of porcine or rat origin. pBECs were isolated and cultured from fragments of capillaries from the brain cortices of domestic pigs 5-6 months old. These fragments were purified by careful removal of meninges, isolation and homogenization of grey matter, filtration, enzymatic digestion, and centrifugation. To further eliminate contaminating cells, the capillary fragments were cultured with puromycin-containing medium. When 60-95% confluent, pBECs growing from the capillary fragments were passaged to permeable membrane filter inserts and established in the models. To increase barrier tightness and BBB characteristic phenotype of pBECs, the cells were treated with the following differentiation factors: membrane permeant 8-CPT-cAMP (here abbreviated cAMP), hydrocortisone, and a phosphodiesterase inhibitor, RO-20-1724 (RO). The procedure was carried out over a period of 9-11 days, and when establishing the NCC model, the astrocytes were cultured 2-8 weeks in advance. Adherence to the described procedures in the protocol has allowed the establishment of endothelial layers with highly restricted paracellular permeability, with the NCC model showing an average transendothelial electrical resistance (TEER) of 1249 &#177; 80 &#937; cm2, and paracellular permeability (Papp) for Lucifer Yellow of 0.90 10-6 &#177; 0.13 10-6 cm sec-1 (mean &#177; SEM, n=55). Further evaluation of this pBEC phenotype showed good expression of the tight junctional proteins claudin 5, ZO-1, occludin and adherens junction protein p120 catenin. The model presented can be used for a range of studies of the BBB in health and disease and, with the highly restrictive paracellular permeability, this model is suitable for studies of transport and intracellular trafficking.

Improved Method for the Establishment of an In Vitro Blood-Brain Barrier Model Based on Porcine Brain Endothelial Cells

The aim of the protocol is to present an optimized procedure for the establishment of an in vitro blood-brain barrier (BBB) model based on primary porcine brain endothelial cells (pBECs). The model shows high reproducibility, high tightness, and is suitable for studies of transport and intracellular trafficking in drug discovery.

一种基于猪脑内皮细胞的体外血脑屏障模型的改进方法

The aim of this protocol presents an optimized procedure for the purification and cultivation of pBECs and to establish in vitro blood-brain barrier (BBB) ...

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

In recent years, the incidence of thyroid cancer has been increasing. Thyroid nodule detection is critical for both the detection and treatment of thyroid cancer. Convolutional neural networks (CNNs) have achieved good results in thyroid ultrasound image analysis tasks. However, due to the limited valid receptive field of convolutional layers, CNNs fail to capture long-range contextual dependencies, which are important for identifying thyroid nodules in ultrasound images. Transformer networks are effective in capturing long-range contextual information. Inspired by this, we propose a novel thyroid nodule detection method that combines the Swin Transformer backbone and Faster R-CNN. Specifically, an ultrasound image is first projected into a 1D sequence of embeddings, which are then fed into a hierarchical Swin Transformer. 
The Swin Transformer backbone extracts features at five different scales by utilizing shifted windows for the computation of self-attention. Subsequently, a feature pyramid network (FPN) is used to fuse the features from different scales. Finally, a detection head is used to predict bounding boxes and the corresponding confidence scores. Data collected from 2,680 patients were used to conduct the experiments, and the results showed that this method achieved the best mAP score of 44.8%, outperforming CNN-based baselines. In addition, we gained better sensitivity (90.5%) than the competitors. This indicates that context modeling in this model is effective for thyroid nodule detection.

Here, a new model for thyroid nodule detection in ultrasound images is proposed, which uses Swin Transformer as the backbone to perform long-range context modeling. Experiments prove that it performs well in terms of sensitivity and accuracy.

基于Swin变压器的超声图像甲状腺结节检测模型

In recent years, the incidence of thyroid cancer has been increasing. Thyroid nodule detection is critical for both the detection and treatment of thyroid ...

用于临床规模 CAR-T 细胞生产的自动化处理器

Chimeric Antigen Receptor T Cell Manufacturing on an Automated Cell Processor

Chimeric antigen receptor (CAR)-T cells represent a promising immunotherapeutic approach for the treatment of various malignant and non-malignant diseases. CAR-T cells are genetically modified T cells that express a chimeric protein that recognizes and binds to a cell surface target, resulting in the killing of the target cell. Traditional CAR-T cell manufacturing methods are labor-intensive, expensive, and may carry the risk of contamination. The CliniMACS Prodigy, an automated cell processor, allows for manufacturing cell therapy products at a clinical scale in a closed system, minimizing the risk of contamination. Processing occurs semi-automatically under the control of a computer and thus&#160;minimizes human involvement in the process, which saves time and reduces variability and errors.
This manuscript and video describes the T cell transduction (TCT) process for manufacturing CAR-T cells using this processor. The TCT process involves CD4+/CD8+ T cell enrichment, activation, transduction with a viral vector, expansion, and harvest. Using the Activity Matrix, a functionality that allows ordering and timing of these steps, the TCT process can be customized extensively. We provide a walk-through of CAR-T cell manufacturing in compliance with current Good Manufacturing Practice&#160;(cGMP) and discuss required release testing and preclinical experiments that will support an Investigational New Drug (IND) application. We demonstrate&#160;the feasibility and discuss the advantages and disadvantages of using a&#160;semi-automatic process for clinical CAR-T cell manufacturing. Finally, we describe an ongoing investigator-initiated clinical trial that targets pediatric B-cell malignancies [NCT05480449] as an example of how this manufacturing process can be applied in a clinical setting.

作者聚焦：CAR-T 细胞制造和基因治疗生产的进步 

This article details the manufacturing process for chimeric antigen receptor T cells for clinical use, specifically using an automated cell processor capable of performing viral transduction and cultivation of T cells. We provide recommendations and describe pitfalls that should be considered during the process development and implementation of an early-phase clinical trial.