基于因子分析法的超声肝灌注定量研究
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摘要
肝癌是一种影响我国人民身体健康的重大疾病，其早期发现和治疗是提高治愈率和降低死亡率的关键。超声造影成像是一种通过注入微泡造影剂来动态、清晰显示微细血管，特别是肿瘤血管的新型成像技术。利用该技术可以获得组织丰富的供血及血流灌注信息，这对临床组织病变的检查具有重要的诊断意义。与增强CT和增强MRI相比，它实时性强、安全性好和价格低。目前，该项技术已被广泛应用于局灶性肝结节（Focal Liver Lesions, FLLs）的鉴别诊断。普通超声造影诊断FLLs主要依靠诊断者对肝不同血管相的增强水平及其变化的观察和判断，这种方式容易受诊断者主观性的影响，存在观察者间差别。为了克服观察者之间的差异性，可通过采用对不同类型FLLs的超声造影数据进行定量分析方法来提高FLLs的诊断率。
本论文以为超声医生提供一种实用且准确性高的超声造影定量分析方法为目标，针对目前动态结构的因子分析法（Factor Analysis of Dynamic Structures, FADS）方法存在的问题，研究一种新型且有效的FADS方法，可从不同类型FLLs的自由呼吸的超声造影数据中自动地提取到时间一强度曲线（Time-Intensity Curves, TICs），然后利用提取到的TICs的特征参数进行参数成像，从而反映出不同类型FLLs的灌注特点，有助于超声医生鉴别FLLs。
考虑到目前所研究的临床病例数据均在病人自由呼吸运动下采集，因此，首先提出了一种基于图像的运动校正策略来快速校正图像序列中的呼吸运动。通常，商业超声机能同时显示造影和组织图像。由于组织图像中的灰度变化较低，采用绝对差值和(Sum of Absolute Differences, SAD)测度对组织图像进行模板匹配。然后，通过一种双选择法挑选相似的图像，该方法需要进行全局和局部的阈值设定。最后，通过利用组织与造影窗口之间的位置映射关系来确定造影图像。该策略只需要简单的人工操作，例如模板图像和搜索范围的选择。它不依赖肿瘤的大小，具有用户友好性，且适合于大多数被不利采样因素所影响的病例。由于省时的优点，该策略能被广泛应用于临床实践中，而且FLLs的诊断效率也会被提高。
针对目前FADS方法的不足，本论文提出一种新型的替代-近似(Replace-Approximation, RA)算法。该方法主要思想是在这些未重叠的生理结构区域中找到最佳的一个像素的TIC取代真实的因子曲线。这样RA法提取的TIC不会丢大部分的初始信息。该算法不像大多数顶点搜寻法从q-1维空间开始搜寻顶点而是将从一维空间且开始搜寻顶点。它不需要估计任何特定的参数，先验知识和传统的因子旋转。该算法首先在体模实验中进行了测试，同时与其他两种FADS方法进行了比较。
随后，在自由呼吸的FLLs病例中进一步验证RA算法。由于FADS分析中因子个数的不确定性，对临床病例分别进行了二个和三个因子的分析。实验结果发现RA法能有效提取到具有生理意义的因子曲线和因子图。然而，并不是所有的临床病例都适用于三个因子分析。相比之下，两个因子的分析结果更加稳定。
根据对临床病例进行两个因子分析中提取到的因子曲线特征参数可计算出注入时间比(Wash-In Time Ratio, WITR)值并合成相应的彩色参数图。这些参数图不仅能准确地直观反映出不同类型FLLs的灌注特点，还能提供灌注区域的血流相对速度的信息。这表明两个因子分析法在肝灌注量化分析具有一定潜力，从而有助于超声医生对肝肿瘤进行鉴别诊断。
Liver cancer is a major disease that affects the physical health of Chinese people, andits early detection and treatment is the key to improve the cure rate and to reduce themortality. Contrast-enhanced ultrasound (CEUS) imaging is a novel imaging techniquethat dynamically and clearly depicts the micro-vasculature, especially the vasculature ofthe tumor by injecting microbubble contrast agents. The rich blood supply and perfusioninformation of the tissue can be acquired by using this technique, which is importantsignificant to the clinical diagnosis of the tissue diseases. Compared withcontrast-enhanced CT and MRT, it is real-time, safety and low-cost. Now the technique iswidely applied to the differential diagnosis of focal liver lesions (FLLs). Generally, thediagnosis by using CEUS imaging mainly relies on the ultrasonographists’observationsand judgments of the enhancement level and change in different vascular phases. This wayis vulnerable to the impact of the ultrasonographists’subjectivity, and there is differencebetween the observers. To overcome it, the diagnostic rate of FLLs could be improved byusing the quantitative analysis methods for the CEUS data from different types of FLLs.
This article aims to provide a practical quantitative analysis method in CEUS imagingwith high accuracy for ultrasonographists. To solve the problems in the factor analysis ofdynamic structures (FADS）methods, a novel and effective FADS method is investigatedto automatically extract time-intensity curve（sTICs）from the CEUS data of different typesof FLLs. Then, the parametric imaging is performed by utilizing the characteristicparameters of the extracted TICs. These maps reflect the perfusion characteristics ofdifferent types of FLLs, which is helpful for ultrasonographists to differentiate FLLs.
The investigated clinical case data was collected during patients breathed freely.Therefore, an image-based motion correction strategy is proposed to quickly correct therespiratory motion in the image sequence. Usually, the commercial ultrasound machine can display contrast and tissue images simultaneously. Because of the low gray-levelvariation in the tissue images, the tissue images are registered by using template matchingwith sum of absolute differences metric. Then, the similar images are selected by adouble-selection method which requires global and local threshold setting. Finally, thecontrast images are determined by utilizing the relationship of position mapping betweenthe tissue and contrast windows. Simple manual operation is only needed, such as theselection of the template image and search space. It is independent of the tumor size anduser-friendly. Moreover, this strategy is suitable for most clinical cases affected by adversefactors of sampling. Due to the merit of the saving time, this strategy can be widelyapplied to clinical practice, and the diagnostic efficiency of FLLs will be improved.
To solve the problems in the current FADS methods, a novel replace-approximation(RA) is proposed. The main idea of the algorithm is that the true factor curve can beapproximately replaced by the optimal TIC of the pixel that is found in the un-overlappedphysiological regions. In this way, the TIC extracted by the RA method will not lose mostof the original information. This method always starts to seek the apexes fromone-dimensional space first, instead of doing it usually from q－1dimensional space. Itdoes not need the estimate of any specific parameter, a priori knowledge or factor rotation.The algorithm is tested on the phantoms, and compared with the two other FADS methods.
RA algorithm is further validated on the free-breathing clinical cases. Because thenumber of factors in the FADS is ambiguous, two-and three-factor analyses are performedon the clinical cases respectively. Experimental results show that the RA method couldextract physiological factor curves and factor images efficiently. However, all the clinicalcases are not suitable for the three-factor analysis. In contrast, the two-factor analysisperforms more stably.
The wash-in time ratio indexes are calculated from the characteristic parameters ofthe two factor curves extracted by the two-factor analysis performed on the clinical cases.Then, these values generate the corresponding parametric images. These parametric maps not only represent the perfusion characteristics of different types of FLLs, but also providethe relative speed information of blood flow in the perfusion region. It indicates thattwo-factor analysis has potential to the quantitative analysis of hepatic perfusion, whichwould be helpful to the differential diagnosis of FLLs.
本论文以为超声医生提供一种实用且准确性高的超声造影定量分析方法为目标，针对目前动态结构的因子分析法（Factor Analysis of Dynamic Structures, FADS）方法存在的问题，研究一种新型且有效的FADS方法，可从不同类型FLLs的自由呼吸的超声造影数据中自动地提取到时间一强度曲线（Time-Intensity Curves, TICs），然后利用提取到的TICs的特征参数进行参数成像，从而反映出不同类型FLLs的灌注特点，有助于超声医生鉴别FLLs。
考虑到目前所研究的临床病例数据均在病人自由呼吸运动下采集，因此，首先提出了一种基于图像的运动校正策略来快速校正图像序列中的呼吸运动。通常，商业超声机能同时显示造影和组织图像。由于组织图像中的灰度变化较低，采用绝对差值和(Sum of Absolute Differences, SAD)测度对组织图像进行模板匹配。然后，通过一种双选择法挑选相似的图像，该方法需要进行全局和局部的阈值设定。最后，通过利用组织与造影窗口之间的位置映射关系来确定造影图像。该策略只需要简单的人工操作，例如模板图像和搜索范围的选择。它不依赖肿瘤的大小，具有用户友好性，且适合于大多数被不利采样因素所影响的病例。由于省时的优点，该策略能被广泛应用于临床实践中，而且FLLs的诊断效率也会被提高。
针对目前FADS方法的不足，本论文提出一种新型的替代-近似(Replace-Approximation, RA)算法。该方法主要思想是在这些未重叠的生理结构区域中找到最佳的一个像素的TIC取代真实的因子曲线。这样RA法提取的TIC不会丢大部分的初始信息。该算法不像大多数顶点搜寻法从q-1维空间开始搜寻顶点而是将从一维空间且开始搜寻顶点。它不需要估计任何特定的参数，先验知识和传统的因子旋转。该算法首先在体模实验中进行了测试，同时与其他两种FADS方法进行了比较。
随后，在自由呼吸的FLLs病例中进一步验证RA算法。由于FADS分析中因子个数的不确定性，对临床病例分别进行了二个和三个因子的分析。实验结果发现RA法能有效提取到具有生理意义的因子曲线和因子图。然而，并不是所有的临床病例都适用于三个因子分析。相比之下，两个因子的分析结果更加稳定。
根据对临床病例进行两个因子分析中提取到的因子曲线特征参数可计算出注入时间比(Wash-In Time Ratio, WITR)值并合成相应的彩色参数图。这些参数图不仅能准确地直观反映出不同类型FLLs的灌注特点，还能提供灌注区域的血流相对速度的信息。这表明两个因子分析法在肝灌注量化分析具有一定潜力，从而有助于超声医生对肝肿瘤进行鉴别诊断。
Liver cancer is a major disease that affects the physical health of Chinese people, andits early detection and treatment is the key to improve the cure rate and to reduce themortality. Contrast-enhanced ultrasound (CEUS) imaging is a novel imaging techniquethat dynamically and clearly depicts the micro-vasculature, especially the vasculature ofthe tumor by injecting microbubble contrast agents. The rich blood supply and perfusioninformation of the tissue can be acquired by using this technique, which is importantsignificant to the clinical diagnosis of the tissue diseases. Compared withcontrast-enhanced CT and MRT, it is real-time, safety and low-cost. Now the technique iswidely applied to the differential diagnosis of focal liver lesions (FLLs). Generally, thediagnosis by using CEUS imaging mainly relies on the ultrasonographists’observationsand judgments of the enhancement level and change in different vascular phases. This wayis vulnerable to the impact of the ultrasonographists’subjectivity, and there is differencebetween the observers. To overcome it, the diagnostic rate of FLLs could be improved byusing the quantitative analysis methods for the CEUS data from different types of FLLs.
This article aims to provide a practical quantitative analysis method in CEUS imagingwith high accuracy for ultrasonographists. To solve the problems in the factor analysis ofdynamic structures (FADS）methods, a novel and effective FADS method is investigatedto automatically extract time-intensity curve（sTICs）from the CEUS data of different typesof FLLs. Then, the parametric imaging is performed by utilizing the characteristicparameters of the extracted TICs. These maps reflect the perfusion characteristics ofdifferent types of FLLs, which is helpful for ultrasonographists to differentiate FLLs.
The investigated clinical case data was collected during patients breathed freely.Therefore, an image-based motion correction strategy is proposed to quickly correct therespiratory motion in the image sequence. Usually, the commercial ultrasound machine can display contrast and tissue images simultaneously. Because of the low gray-levelvariation in the tissue images, the tissue images are registered by using template matchingwith sum of absolute differences metric. Then, the similar images are selected by adouble-selection method which requires global and local threshold setting. Finally, thecontrast images are determined by utilizing the relationship of position mapping betweenthe tissue and contrast windows. Simple manual operation is only needed, such as theselection of the template image and search space. It is independent of the tumor size anduser-friendly. Moreover, this strategy is suitable for most clinical cases affected by adversefactors of sampling. Due to the merit of the saving time, this strategy can be widelyapplied to clinical practice, and the diagnostic efficiency of FLLs will be improved.
To solve the problems in the current FADS methods, a novel replace-approximation(RA) is proposed. The main idea of the algorithm is that the true factor curve can beapproximately replaced by the optimal TIC of the pixel that is found in the un-overlappedphysiological regions. In this way, the TIC extracted by the RA method will not lose mostof the original information. This method always starts to seek the apexes fromone-dimensional space first, instead of doing it usually from q－1dimensional space. Itdoes not need the estimate of any specific parameter, a priori knowledge or factor rotation.The algorithm is tested on the phantoms, and compared with the two other FADS methods.
RA algorithm is further validated on the free-breathing clinical cases. Because thenumber of factors in the FADS is ambiguous, two-and three-factor analyses are performedon the clinical cases respectively. Experimental results show that the RA method couldextract physiological factor curves and factor images efficiently. However, all the clinicalcases are not suitable for the three-factor analysis. In contrast, the two-factor analysisperforms more stably.
The wash-in time ratio indexes are calculated from the characteristic parameters ofthe two factor curves extracted by the two-factor analysis performed on the clinical cases.Then, these values generate the corresponding parametric images. These parametric maps not only represent the perfusion characteristics of different types of FLLs, but also providethe relative speed information of blood flow in the perfusion region. It indicates thattwo-factor analysis has potential to the quantitative analysis of hepatic perfusion, whichwould be helpful to the differential diagnosis of FLLs.
引文
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