【作者】 王丽会；

【导师】 朱跃敏； 刘宛予； Isabelle E. Magnin；

【作者基本信息】 哈尔滨工业大学 ， 仪器科学与技术， 2013， 博士

【摘要】 磁共振扩散成像(Diffusion Magnetic Resonance Imaging, dMRI)作为目前唯一能够对活体纤维组织结构进行无损检测的成像技术,已成为当前研究三维离体及活体心肌纤维结构的主要手段,对探索心肌纤维的微观组成与活动机理、解释心血管疾病的成因和早期诊断具有重大的科学意义和临床应用价值。然而由于心肌自身结构和功能的特殊性,目前dMRI在心肌纤维研究领域仍存在以下几个主要问题：首先,受磁共振成像设备的限制,实际采集图像空间分辨率低、易受噪声影响,在缺少对真实心肌纤维结构认知的情况下,无法解释心肌纤维中水分子扩散各向异性变化的原因、评价dMRI测量心肌纤维方向的准确性以及分析心肌纤维微观结构与dMRI测量之间的关系。其次,优化dMRI扫描序列参数是获得高质量磁共振扩散加权图像和提高复杂心肌纤维结构分析准确率的关键。然而,目前dMRI序列参数的优化选择仅能通过大量的重复扫描实验获得,缺乏理论依据、实验过程复杂且成本高。最后,由于dMRI对运动信息敏感,在活体心肌纤维成像中,心脏跳动、病人移动、心率不齐等都会产生图像伪影并引起额外的扩散信号衰减,因此,难以实现完整心脏活体心肌纤维磁共振扩散成像表征参数的定量描述。为了解决上述问题,本课题从dMRI成像机理出发,针对心肌纤维自身结构特点,提出一种基于多种成像数据融合的离体及动态心肌纤维磁共振扩散成像仿真模型,为心肌纤维dMRI测量效果评价、dMRI表征参数与心肌纤维微观结构关系研究、dMRI扫描参数优化选择以及活体心肌纤维dMRI特性定量描述提供一种有效的分析手段。本文主要研究内容如下：(1)针对临床磁共振扩散成像技术分辨率低,无法解释心肌纤维中水分子扩散各向异性的原因以及评价dMRI测量心肌纤维方向的准确性问题,建立两种局部心肌纤维模型,利用蒙特卡罗方法模拟不同分辨率下心肌纤维模型的扩散加权和扩散张量图像,通过分析心肌纤维模型的生理和结构特征对扩散各向异性的影响,确定心肌纤维中引起水分子扩散各向异性的主要因素,同时给出不同分辨率下dMRI检测心肌纤维方向的准确性。(2)针对利用实际采集图像无法分析磁共振扩散成像表征参数与心肌纤维微观结构之间的关系问题,利用偏振光成像(Polarized Light Imaging, PLI)技术获得的高分辨率心肌纤维方向分布数据,建立完整心脏的三维心肌纤维几何结构模型,使用dMRI仿真模型定量地描述不同分辨率下磁共振扩散加权及张量图像特性。通过控制心肌纤维结构模型参数,分析心肌细胞结构变化对扩散图像表征参数的影响,为研究心肌纤维微观结构与磁共振扩散成像表征参数之间的关系以及心肌疾病病理分析与诊断提供一种辅助手段。(3)针对心肌纤维dMRI扫描序列参数优化问题,提出了一种改进的dMRI信号以及扩散张量成像仿真方法。该方法考虑实际成像序列中所有梯度对水分子扩散的加权作用,模拟真实的扩散加权成像过程。利用改进的仿真方法研究成像序列中所有梯度参数对扩散图像特性的影响以实现成像参数的优化选择。(4)针对dMRI对运动敏感,无法准确分析活体心肌纤维磁共振扩散图像特性的问题,结合心脏运动信息建立动态心肌纤维模型,利用仿真获得一个心脏周期内不同时刻的心肌纤维扩散加权和扩散张量图像,并研究动态心肌纤维扩散图像表征参数随心脏运动的变化,为活体心肌纤维成像分析奠定基础。更多还原

【Abstract】 Diffusion magnetic resonance imaging (dMRI) is able to measure indirectly thetissue structures by detecting the diffusion of water molecules therein. It appearscurrently as the unique imaging technique to investigate noninvasively both ex vivoand in vivo three-dimensional fiber architectures of the human heart. However, dueto the specific structural and functional properties of the cardiac muscle, there arestill several main problems in the research of cardiac dMRI. Firstly, it is difficult toexplain the reason for the diffusion anisotropy of molecules in the cardiac fiber, toknow how well the diffusion properties calculated from diffusion images reflect themicrostructure of the myocardium and to analyze the relationship between the dMRImeasures and the microstructures of cardiac fiber, since there is no ground-truthinformation available and add to that the influence of various factors such as spatialresolution, noise and artifacts, etc. Secondly, optimizing the dMRI scanningparameters is very significant for obtaining the high-quality diffusion weightedimages and analyzing accurately the complex cardiac fiber structure. However, up tonow, the optimization of the imaging parameters can only be achieved by using therepeated scans, which is lack of the theoretical basis, such experiment process iscomplicated and expensive. Finally, since dMRI is very sensitive to the motion,during the in vivo dMRI scanning, the motion caused by the heart beating, patientmoving and arrhythmias will generate the artifacts and introduce additional signalattenuation, it is therefore difficult to describe quantitatively the properties ofdiffusion images of in vivo cardiac fibers.For solving the above problems, based on the nature of dMRI theory and takinginto account the cardiac fiber structure properties, this thesis develops a realisticmodel-based dMRI simulator to simulate diffusion-weighted images for both ex vivoand dynamic cardiac fibers by integrating different imaging modalities. Thissimulator provides an effective mean for evaluating the measurement accuracy ofdMRI for cardiac fiber structure, analyzing the relationship between dMRI measuresand the microstructure of cardiac fiber, optimizing dMRI scanning parameters anddescribing quantitatively dynamic cardiac fiber structure. The following are themain issues addressed in this thesis.The first part concerns the issue that the clinical dMRI is unable to explain thecauses of the diffusion anisotropy of water molecules in the cardiac fiber structureand to evaluate the accuracy of dMRI detection for cardiac fiber orientations due tothe limit of the spatial resolution. For solving this problem, two local cardiac fiberstructure models are firstly constructed, the corresponding diffusion weighted and tensor images with different spatial resolutions are then simulated using aMonte-Carlo method, the main cause for diffusion anisotropy is finally given byanalyzing the influence of cardiac fiber structural and physical characteristics on thediffusion anisotropy. Meanwhile, the dMRI detection accuracy at different scales isanalyzed.The second part addresses the problem of analyzing the relationship betweendMRI measures and the microstructures of the cardiac fiber. The3D cardiac fiberstructure model of an entire heart is firstly constructed using the high-resolutionpolarized light imaging data, and then the corresponding diffusion weighted andtensor images properties at multi-scales are described through the simulation, finally,by controlling the cardiac fiber modeling parameters, the influence of the cardiacmyocyte structure variation on the diffusion image properties is investigated, andthe results show that the proposed dMRI simulator can provide an auxiliary meanfor exploring the relationship between dMRI properties and cardiac fibermicrostructures, and also for cardiac disease analysis and diagnosis.The third part deals with the issue of optimizing the dMRI scanning parametersfor cardiac fibers. To realize the optimization, a novel improved dMRI signalanalysis and simulation method is proposed, which takes into account the weightsall the gradients used in the imaging sequence on the diffusion of water moleculesfor simulating the process of dMRI more realistically. By investigating the influenceof each parameter on the diffusion image properties, the optimization principle ofsuch parameter is finally given.The last part puts the emphasis on the modeling of dynamic cardiac fiberstructures and the simulation of the corresponding diffusion images. It also analyzesthe variation of the diffusion image properties of cardiac fibers with the heartmotion. This work provides a basis for the in vivo myocardial fiber image analysis.更多还原