Advanced Assessment of Hepatic Inflammation and Fibrosis with MR Elastography

描述（由申请人提供）：机械性能是监测和表征细胞和组织的各种病理生理条件的有前景的替代品。例如，我们率先开发了肝脏MR弹性成像（MRE），这是一种用于测量肝脏硬度的非侵入性成像技术，已开始广泛用于临床评估肝纤维化，作为活检的替代方法。尽管取得了这一进展，但仍需要进一步开发肝脏MRE，以便其具有跟踪疾病进展和对治疗的反应所需的精确度。肝脏的几种内在病理状况（例如，炎症）损害了肝硬度表征的阳性预测值 肝纤维化这些因素导致相似的刚度增加量，但有不同的病理生理学起源，并对应于不同的结构变化。因此，该提案的主要目标是开发先进的肝脏MRE技术，包括多孔粘弹性（PVE）力学模型，能够区分炎症和纤维化，同时考虑肝组织中脂肪变性的影响。我们的基本假设是，肝组织可以合理地使用两相PVE理论，包括一个固有的各向同性的不可压缩的粘弹性固体基质相和不可压缩的饱和流体相。假设是基于这样的PVE模型的时间谐波肝脏MRE数据的分析将使得能够将脂肪变性和纤维变性相关的固体基质机械响应与炎症相关的孔隙流体行为的机械响应分离。在目标1中，我们将实施PVE分析方法，以确定PVE参数并评估体模研究中模型的关键假设。在目标2中，我们将使用急性肝脏炎症小鼠模型来评估PVE模型区分和量化炎症程度的潜力，通过测试无创计算的PVE孔隙压力是否与有创测量的间质液压力（IFP）显著相关，表明它可以用作组织学证实的炎症程度的替代品。在目标3中，我们将进一步评估PVE肝脏MRE区分和量化慢性肝病小鼠模型（NAFLD/NASH小鼠模型）中共存炎症和纤维化的潜力。我们假设MRE评估的PVE参数（弹性、粘度和孔隙压）与肝组织学（纤维化、脂肪变性和炎症）之间存在显著相关性。 在目标4中，我们将使用现有患者数据进行转化人体研究，以确定是否存在至少一种PVE参数或几种PVE参数的组合，可以区分和量化肝脏中的进行性脂肪变性、早发性和持续性炎症以及随后发生的肝纤维化。这项拟议研究的成功将最大限度地提高肝脏MRE提供的临床相关信息，从而大大提高我们在慢性肝病广泛的病理生理谱中诊断疾病进展的理解和能力。

DESCRIPTION (provided by applicant): Mechanical properties are promising surrogates for monitoring and characterizing various pathophysiologic conditions of cells and tissues. For example, we have pioneered the development of liver MR elastography (MRE), a noninvasive imaging technology for measuring liver stiffness, which is beginning to see widespread clinical use for assessing hepatic fibrosis as an alternative to biopsy. Despite this progress, there is a need to further develop hepatic MRE so that it can have the precision necessary to track disease progression and response to therapy. Several intrinsic pathologic conditions of the liver (e.g., inflammation) compromise the positive predictive value of liver stiffness for characterizing hepatic fibrosis alone. These factors cause similar amounts of stiffness augmentation but have different pathophysiological origins and correspond to different architectural changes. Therefore, the major goal of this proposal is to develop advanced hepatic MRE techniques, including poroviscoelastic (PVE) mechanical models, capable of differentiating inflammation and fibrosis while considering the effects of steatosis in the liver tissue. Our basic assumption is that liver tissue can reasonably be modeled using biphasic PVE theory consisting of an intrinsically isotropic incompressible viscoelastic solid matrix phase and an incompressible saturated fluid phase. The hypothesis is that analysis of time-harmonic hepatic MRE data based on such a PVE model will enable the separation of the steatosis- and fibrosis-related solid matrix mechanical responses from that of the inflammation-related pore fluid behavior. In Aim 1, we will implement a PVE analysis method to determine PVE parameters and evaluate the key assumptions of the model in phantom studies. In Aim 2, we will use an acute hepatic inflammation mouse model to evaluate the potential for a PVE model to differentiate and quantify inflammation extent by testing whether noninvasively calculated PVE pore pressure significantly correlates with invasively measured interstitial fluid pressure (IFP), indicating tha it could be used as a surrogate for histology-proven inflammation extent. In Aim 3, we will further evaluate the potential for PVE hepatic MRE to differentiate and quantify coexisting inflammation and fibrosis in mouse models with chronic liver disease (NAFLD/NASH mouse model). We hypothesize that significant correlations can be found among MRE-assessed PVE parameters (elasticity, viscosity & pore pressure) and hepatic histology (fibrosis, steatosis & inflammation). In Aim 4, we will perform a translational human study using existing patient data to determine if there is at least one or a combination of several PVE parameters that can distinguish and quantify progressive steatosis, early onset and ongoing inflammation and subsequently developed hepatic fibrosis in the liver. The success of this proposed study will maximize the clinically relevant information provided by hepatic MRE to substantially advance our understanding and ability to diagnose disease progress in the broad pathophysiologic spectrum of chronic liver diseases.