该出版物由国家中医药管理局组织的第五届全国中医药临床优秀人才研究计划资助。官方网络链接是'http://www.natcm.gov.cn/renjiaosi/zhengcewenjian/2021-11-04/23082.html.'

本研究利用 3D 数字 LSD 建模重建了临床确诊肝纤维化的典型患者的肝脏。患者从中国北京著名的肝病治疗机构“佑安医院”招募，经同意后进行了常规上腹部磁共振成像（MRI）和MRE成像。由于病理检查确认肝纤维化分期，且无明显临床症状，故选择该患者作为本研究的病例，强调了本研究在早期肝纤维化患者诊断中的适用性和临床价值。本文还对该患者的肝脏与健康肝脏进行了定量比较。本研究中使用的软件工具列在 材料表中。
1. 资料收集与准备
注：参数差异对研究方法不敏感。
<ol><li>MRI 扫描策略 注：本研究利用了使用 GE 制造的磁共振成像 （MRI） 设备从临床成像中获得的实际 DICOM 数据。数据内容包括IDEAL（水和脂肪的迭代分解，回波不对称和最小二乘估计）、水脂分离成像和磁共振弹性成像（MRE）成像。<ol><li>确保 IDEAL 数据的水平分辨率为 256 x 256 像素，像素间距为 1.5625 mm，切片厚度为 10 mm。 注：扫描策略可以进一步优化，但本研究采用的方法适用于更高精度的医学成像。</li>
	</ol></li>
	<li>重命名每个序列的文件夹。 注意：由于从设备导出的DICOM数据没有明确提供序列名称，因此在预处理阶段，需要为每个序列添加显式名称，以方便后续分析和处理。<ol><li>将 所有 DICOM 数据复制到自定义工作目录。</li>
		<li>导航到 包含 MATLAB 工作目录中数据的目录。</li>
		<li>执行 Description_Name 函数，将描述性名称添加到每个序列的文件夹中。</li>
		<li>请参阅 图 1 ，了解重命名前后的比较。向每个图像序列文件夹添加描述名称，以便于识别用于各种分析目的所需的图像序列。</li>
	</ol></li>
	<li>快速检查 IDEAL 的图像。<ol><li>更改不同相文件夹的目录，包括同相、异相、水相和脂肪相，这些文件夹存储在单独的文件夹中，以便使用 IDEAL 进行成像。</li>
		<li>执行 Slice_View 函数以查看每个阶段的影响序列。</li>
		<li>有关MRI-IDEAL序列的交互式图形用户界面（GUI）的图像，请参见 图2 。使用 GUI 底部的滚动条快速浏览不同的序列。</li>
		<li>使用 MRI-IDEAL 异相 序列作为 MRI 序列的类型，以提供更清晰的肝组织边界描述。 注意：在以下操作中，重点将放在使用 IDEAL 的异相序列来描绘肝脏的 3D 区域。</li>
	</ol></li>
</ol>2.提取肝脏的3D区域
注：肝脏 3D 区域中的单个体素作为 LSD 的空间载体，每个体素的硬度值来自 MRE。提取肝组织的3D区域是融合前的必要步骤。虽然深度学习可以用来更有效地完成这项任务，但这并不是本研究的重点。因此，这里仍然使用成熟的软件工具（例如，MIMICS）来提取肝组织的3D区域。
<ol><li>要启动 MIMICS 软件，请选择“新建项目”，然后在随后的对话框中导航到包含 IDEAL 异相图像的文件夹。单击“下一步”|“转换”按钮继续，从而进入序列编辑状态。</li>
	<li>要创建空掩码，请单击右侧“掩码”对话框中的“新建”按钮，然后选择最大阈值。</li>
	<li>要在所有水平视图中划定肝脏区域，请使用位于 “线段 ”标签下方的“编辑蒙版”工具。</li>
	<li>要生成肝脏的 3D 空间部分，请选择已描绘的肝脏掩膜，然后单击“ 从掩模计算部分 ”按钮。提取的肝脏 3D 区域如图 3 所示。</li>
	<li>单击 “文件”|”出口 |选择 Dicom 命令。在弹出的对话框中，选择肝脏 掩膜，设置文件路径和文件名称，然后单击 OK 按钮完成将肝脏的 3D 区域导出到指定的 DICOM 文件。</li>
</ol>3. 肝脏硬度图序列
注意：早期纤维化患者的 MRE 硬度范围通常低于 8 kpa。要查看这一点，应选择标记为“SE27_ST8K_（Pa）”的序列图像。
<ol><li>将目录更改为“SE27_ST8K_（Pa）”文件夹，其中包含肝脏硬度图序列。</li>
	<li>要浏览每个刚度图，请在 Matlab 的工作区中执行 MRE_show 函数，该函数的参数是位于指定路径中的文件名。</li>
	<li>图 4 所示的肝脏硬度 图 是 RGB 真彩色图像，数据结构为 512 像素 x 512 像素 x 3 矩阵，其中每个像素点有三个值，分别代表三原色 RBG。观察左侧的色条，该色条显示不同颜色像素的相应刚度值。通过使用每个像素各自的相关性来计算每个像素的确切刚度。</li>
	<li>图 4 中的补充信息包括序列描述、扫描位置、时间、患者信息和图像参数等数据。使用这些数据，特别是图像参数，来建立MRE和IDEAL序列之间的空间关系。</li>
</ol>4.3D-肝脏硬度分布的体积
注：3D 肝脏刚度体积中的每个体素表示 3D 肝脏区域中相应体素的刚度值，该值来自图 4 中每个像素的刚度值。通过将图 3 中的 3D 肝脏区域与图 4 中的刚度图对齐，可以提取每个体素的刚度值，从而生成 3D 肝脏刚度体积。
<ol><li>调用 LSD_Slice 函数， 将图 3 所示的 3D 肝脏区域和图 4 中的肝脏硬度 图 作为输入参数，以获得肝脏硬度分布的 3D 体积，如图 5 所示。</li>
	<li>通过拖动图 5 所示的 GUI 下方的滚动条，查看肝脏每一层的硬度 图。 注意：然而，与 图 4 不同的是，这里只准确地保留了肝组织。</li>
	<li>观察 GUI 右上角的图标（图 5），例如放大、缩小、返回全局视图以及标记所选像素的坐标。 注意： 默认颜色条是“jet”的颜色图，这意味着从蓝色到红色的相应值（单位 kpa）从低到高。</li>
	<li>使用与LSD_Slice相同的输入执行LSD_Volume函数，以获得3D肝脏LSD的空间分布，如图6所示。通过按住鼠标左键并拖动屏幕，从任何角度查看 LSD 的 3D 体积（图 6）。</li>
</ol>5. LSD定量分析
注：本研究的一个重要定量分析重点是提供患者肝脏中不同阶段LSD体素的比例。 图6 显示，患者肝纤维化在不同空间位置的分布不均匀。临床症状尚不明显的原因主要是由于相当一部分肝组织处于正常阶段。因此，有必要精确量化患者和健康个体之间的差异。这是本研究的一个重要定量概念。
<ol><li>确定肝纤维化不同阶段的刚度值数值范围， 如图 7 所示。</li>
	<li>通过使用图6所示的LSD的3D体积的输入参数调用Hepatic_Fibrosis函数，计算患者整个肝体素在不同纤维化阶段的分布（图6）。</li>
	<li>使用相同的步骤计算和比较完全健康的肝脏与上述典型肝纤维化患者的结果（图9）。</li>
</ol>

肝脏硬度分布的定量分析

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本研究 材料表 中列出的肝纤维化定量软件工具 HepaticFibrosis V1.0是北京智能熵科技有限公司的软件工具。本软件工具的知识产权归本公司所有。

在临床实践中，准确量化和跟踪早期肝纤维化患者的病情具有挑战性。 图9 所示的比较充分反映了患者与健康肝脏相比的肝纤维化程度;当然，这个数字也可以是患者两个不同时期的比较，用于评估治疗效果。这种精确的定量方法是本研究的核心关键步骤。此外，图 5 和 图6 所示的LSD三维体积的计算方法可以准确定位患者肝脏中纤...

肝纤维化是指肝脏中形成过多的瘢痕组织，通常是由于肝损伤或疾病1,2,3,4。它经常由慢性肝损伤引起，通常与肝脏疾病有关，例如慢性病毒性肝炎、非酒精性脂肪性肝病和酒精性肝病。如果不及时治疗，肝纤维化会发展为肝硬化，这是一种可能危及生命的疾病，与严重的发病率和死亡率有关。
该领域的积极研究旨在阐明肝纤维化发病机制的细胞和分子机制，并开发新的诊断和治疗策略以改善患者的预后。另一个目标是肝纤维化阶段的无创检测，这是与疾病诊断、治疗选择和预后评估直接相关的一个关键方面。尽管准确诊断和监测肝纤维化很重要，但传统的诊断方法（如肝活检）具有侵入性且具有重大风险。相比之下，磁共振弹性成像 5,6 （MRE） 是一种很有前途的非侵入性成像技术，已通过量化肝脏硬度在诊断和监测肝纤维化方面显示出潜力。
近年来，有大量研究集中在评估MRE在肝纤维化诊断中的准确性和可靠性，以及其相对于传统诊断方法的潜在优势。MRE的肝脏硬度指标已获得美国食品药品监督管理局（FDA）的临床诊断批准，并在临床实践中与病理结果进行了广泛的对比分析。结果表明，MRE生成的硬度图与肝纤维化的各个阶段呈强正相关7、8、9、10、11、12。然而，到目前为止，通过将肝脏结构图像与MRE相匹配，通过对肝脏硬度分布（LSD）进行定量分析来准确评估和跟踪患者肝纤维化进展的工作尚未取得太大进展。
本研究引入医学影像组分析技术13、14、15，实现肝脏结构图像与MRE生成的三维空间刚度图的精确对齐，从而能够计算整个肝脏每个体素的肝脏硬度值。基于LSD的3D数字模型，可以计算和评估患者特异性肝纤维化分期的确切分布。这为早期肝纤维化的精准定量诊断奠定了坚实的基础。

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>MATLAB</td>
			<td>MathWorks&#160;</td>
			<td>2022B</td>
			<td>Computing and visualization&#160;</td>
		</tr>
		<tr>
			<td>Mimics</td>
			<td>Materialise</td>
			<td>Mimics Research V20</td>
			<td>Model format transformation</td>
		</tr>
		<tr>
			<td>Tools for 3D_LSD</td>
			<td>Intelligent&#160;Entropy</td>
			<td>HepaticFibrosis V1.0</td>
			<td>Beijing Intelligent Entropy Science &#38; Technology Co Ltd. 
			Modeling for CT/MRI fusion</td>
		</tr>
	</tbody>
</table>

a three-dimensional digital model for early diagnosis of hepatic fibrosis based on magnetic resonance elastography

肝纤维化是肝硬化的早期阶段，没有更好的非侵入性和便捷的方法来检测和评估该疾病。尽管基于磁共振弹性成像 （MRE） 的肝脏硬度图 （LSM） 取得了良好的进展，但仍有一些局限性需要克服，包括手动确定焦点、手动选择感兴趣区域 （ROI） 以及没有结构信息的不连续 LSM 数据，这使得无法评估整个肝脏。在这项研究中，我们提出了一种基于MRE的肝纤维化早期诊断的新型三维（3D）数字模型。
MRE是一种非侵入性成像技术，它采用磁共振成像（MRI）通过人机交互测量扫描部位的肝脏硬度。研究表明，通过MRE获得的LSM与肝纤维化程度之间存在显著的正相关关系。然而，出于临床目的，有必要对肝纤维化的程度进行全面和精确的量化。针对这一问题，本研究提出了肝脏硬度分布（LSD）的概念，即通过3D肝组织图像与MRE指标对齐得到的每个肝脏体素的3D硬度体积。这为肝纤维化的诊断和治疗提供了更有效的临床工具。

Hepatic fibrosis refers to the formation of excessive scar tissue in the liver, usually as a result of liver damage or disease1,2,3,4. It frequently arises as a consequence of chronic liver injury and is commonly associated with liver diseases, such as chronic viral hepatitis, non-alcoholic fatty liver disease, and alcoholic liver disease. If left untreated, hepatic fibrosis can progress to cirrhosis, a potentially life-threatening condition associated with significant morbidity and mortality.
Active research in this area aims to elucidate the cellular and molecular mechanisms underlying the pathogenesis of hepatic fibrosis, as well as to develop novel diagnostic and therapeutic strategies to improve patient outcomes. Another objective is the noninvasive detection of the hepatic fibrosis stage, which is a critical aspect that directly correlates with disease diagnosis, treatment selection, and prognosis evaluation. Despite the importance of accurate diagnosis and the monitoring of hepatic fibrosis, traditional diagnostic methods, such as liver biopsy, are invasive and associated with significant risks. In contrast, magnetic resonance elastography5,6 (MRE) is a promising non-invasive imaging technique that has demonstrated potential in the diagnosis and monitoring of hepatic fibrosis by quantifying liver stiffness.
In recent years, there has been significant research focused on evaluating the accuracy and reliability of MRE in the diagnosis of hepatic fibrosis, as well as its potential advantages over traditional diagnostic methods. The liver stiffness metric of MRE has been granted approval by the United States Food and Drug Administration (FDA) for clinical diagnosis, and extensive comparative analysis with pathological results has been conducted in clinical practice. The results have shown that the stiffness maps generated by MRE exhibit a strong positive correlation with various stages of liver fibrosis7,8,9,10,11,12. Yet so far, the work of accurately evaluating and tracking the progression of liver fibrosis in patients through quantitative analysis of liver stiffness distribution (LSD) by matching liver structure images with MRE has not made much progress.
In this study, the medical imaging group analysis technique13,14,15 is introduced to achieve accurate alignment of the liver structure images with the stiffness map generated by MRE in 3D space, enabling the calculation of liver stiffness values for each voxel of the entire liver. Based on the 3D-digital model of LSD, the exact distribution of patient-specific liver fibrosis staging can be calculated and evaluated. This lays a solid foundation for the precise quantitative diagnosis of early-stage liver fibrosis.

作者聚焦：使用磁共振弹性成像和 AI 推进肝纤维化诊断 

基于磁共振弹性成像的肝纤维化早期诊断三维数字模型

The scope of the research is to develop a three dimensional digital model for the early diagnosis of hepatic fibrosis based on magnetic resonance elastography. The research aims to address the limitations of current methods and provide a noninvasive and quantitative approach for the accurate assessment and monitoring of hepatic fibrosis. Some of the current experimental challenges in the field of hepatic fibrosis research include improving the scanning accuracy and imaging techniques of non-invasive methods like magnetic resonance elastography, standardizing computational protocols for consistent results and accumulating more comprehensive, and that was data size for accurate classification and diagnosis.The liver MRI structural images were accurately aligned with MRE images, enabling the three dimensional distribution of liver stiffness, distribution, and achieving precise quantification in 3D space. It is possible to accurately establish a liver's stiffness distribution map for a healthy liver, and conveniently utilize it for the diagnosis and the treatment of patients with different stages of liver cirrhosis. In the future, we want to address AI-driven diagnosis, treatment, and prognosis of liver diseases, as well as the development of herbal medicines related to liver diseases.

通过利用DICOM文件 Description_Name 字段中的信息，可以重命名原始MRI文件夹，以方便在成像组的分析过程中快速定位所需的成像序列。MRI-IDEAL异相序列是用于更清晰地描述肝组织边界的MRI序列类型。这是因为MRI-IDEAL异相序列可以通过特定的图像处理技术更好地区分不同组织的磁化强度和角度。
MRI-IDEAL异相序列的工作原理是使用梯度回波序列（GRE）生成图像，并在图?...

Watch this Scientific Journal Video about Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI at JoVE.com

本研究的目的是开发一种用于肝纤维化早期诊断的新型三维数字模型，该模型包括患者肝脏中每个体素的硬度，因此可用于计算患者肝脏在不同纤维化阶段的分布比例。

Hepatic fibrosis is an early stage of liver cirrhosis, and there are no better non-invasive and convenient methods for the detection and evaluation of the ...

研究范围是开发基于磁共振弹性成像的三维数字模型，用于肝纤维化的早期诊断。该研究旨在解决当前方法的局限性，并为肝纤维化的准确评估和监测提供一种无创和定量的方法。目前肝纤维化研究领域的一些实验挑战包括提高磁共振弹性成像等非侵入性方法的扫描精度和成像技术，标准化计算协议以获得一致的结果并积累更全面的数据量，这是用于准确分类和诊断的数据量。肝脏MRI结构图像与MRE图像精确对齐，实现了肝脏硬度、分布的三维分布，实现了三维空间的精确量化。可以准确地建立健康肝脏的肝脏硬度分布图，并方便地用于不同阶段肝硬化患者的诊断和治疗。未来，我们希望解决人工智能驱动的肝病诊断、治疗和预后，以及与肝病相关的草药的开发。

a-three-dimensional-digital-model-for-early-diagnosis-hepatic

Research

JoVE Journal

Medicine

A Three-Dimensional Digital Model for Early Diagnosis of Hepatic Fibrosis Based on Magnetic Resonance Elastography

809 次观看.  Capital Medical University. 研究范围是开发基于磁共振弹性成像的三维数字模型，用于肝纤维化的早期诊断。该研究旨在解决当前方法的局限性，并为肝纤维化的准确评估和监测提供一种无创和定量的方法。目前肝纤维化研究领域的一些实验挑战包括提高磁共振弹性成像等非侵入性方法的扫描精度和成像技术，标准化计算协议以获得一致的结果并积累更全面的数据量，这是用于准确分类和诊断的数据?...

视频: 作者聚焦：使用磁共振弹性成像和 AI 推进肝纤维化诊断 

Hepatic fibrosis is an early stage of liver cirrhosis, and there are no better non-invasive and convenient methods for the detection and evaluation of the disease. Despite the good progress made with the liver stiffness map (LSM) based on magnetic resonance elastography (MRE), there are still some limitations that need to be overcome, including manual focus determination, manual selection of regions of interest (ROIs), and discontinuous LSM data without structural information, which makes it impossible to evaluate the liver as a whole. In this study, we propose a novel three-dimensional (3D) digital model for the early diagnosis of hepatic fibrosis based on MRE.
MRE is a non-invasive imaging technique that employs magnetic resonance imaging (MRI) to measure the liver stiffness at the scanning site through human-computer interaction. Studies have indicated a significant positive correlation between the LSM obtained through MRE and the degree of hepatic fibrosis. However, for clinical purposes, a comprehensive and precise quantification of the degree of hepatic fibrosis is necessary. To address this, the concept of Liver Stiffness Distribution (LSD) was proposed in this study, which refers to the 3D stiffness volume of each liver voxel obtained by the alignment of 3D liver tissue images and MRE indicators. This provides a more effective clinical tool for the diagnosis and treatment of hepatic fibrosis.

The objective of this study was to develop a novel three-dimensional digital model for the early diagnosis of hepatic fibrosis, which includes the stiffness of each voxel in the patient's liver and can thus, be used to calculate the distribution ratio of the patient's liver at different fibrosis stages.

科研

医学

Extraction of 3D Region of the Liver for Hepatic Fibrosis Diagnosis

To begin, open MATLAB software. Ensure that the IDEAL data have a horizontal resolution of 256 by 256 pixels with a pixel spacing of 1.5625 millimeters and a slice thickness of 10 millimeters. Copy all DICOM data to a customized working directory, and navigate to the directory containing the data in MATLAB's working directory.Then execute the description name function to add descriptive names to the folders for each sequence. Add a description name to each image sequence folder. To check images of IDEAL, change the directory of different phase folders.Execute the slice view function to view the impact sequences for each phase. Next, quickly browse the different sequences using the scroll bar at the bottom of the GUI. Select the MRI IDEAL outphase sequence to depict liver tissue boundaries.Initiate the Mimics software. Select new project, and in the ensuing dialogue box, navigate to the folder containing the IDEAL outphase images. Click next, followed by the convert button to enter into the sequence heading state.To create an empty mask, from the mask dialogue box, click on the new button and select the maximum threshold. Using the edit masks tool located beneath the segment label, delimit the area of the liver in all horizontal views. To generate the 3D spatial part of the liver, select the outlying liver mask and click on the calculate part for mask button.Next, click file, then export, and select the DICOM command. In the pop-up dialogue box, choose the liver mask, and set the file path and names, then click the OK button to complete the export of the 3D region of the liver to the specified DICOM files.

提取肝脏3D区域用于肝纤维化诊断

Calculating the Distribution Ratio of the Patient's Liver at Different Fibrosis Stages

Calculating the Distribution Ratio of the Patient&#039;s Liver at Different Fibrosis Stages  

Begin by changing the directory to the folder SE27_ST8K_, Pa, which contains the liver stiffness map sequence. To browse through each stiffness map, execute the MRE_show function, with the function's argument being the file name located in the specified path. Observe the liver stiffness map in an RGB true color image, where each pixel point has three values representing the three primary colors.Calculate the exact stiffness for each pixel using their respective correlations. Then, establish the spatial relationship between MRE and ideal sequences. To obtain the 3D volume of liver stiffness distribution, invoke the LSD_Slice function with the 3D liver region and the liver stiffness map as input parameters.Then, drag the scroll bar below the GUI to view the stiffness map of each layer of the liver. Next, execute the LSD_Volume function with the same input as LSD_Slice to obtain the spatial distribution of the 3D liver LSD. View the 3D volume of LSD from any perspective by holding down the left mouse button.After determining the numerical ranges of stiffness values from four different stages of hepatic fibrosis, using the Hepatic_Fibrosis function with the 3D volume of LSD as the input parameter, calculate the distribution of the patient's entire liver voxels across different fibrosis stages. Then, calculate and compare the results between a completely healthy liver and the liver of a typical fibrosis patient. Quantitative results of the patient's hepatic fibrosis indicate the proportion of the patient's liver in different stages of hepatic fibrosis.Comparison of LSD fully reflects the degree of hepatic fibrosis in the patient compared to a healthy liver.