Predicting outcomes in nonalcoholic steatohepatitis with advanced fibrosis

肝功能失代偿(显性腹水、脑病和静脉曲张出血)和死亡率 随着肝硬变的发展，非酒精性脂肪性肝炎(NASH)呈指数增加。预防 因此，这种与肝脏相关的临床事件(LACE)是治疗学的一个主要目标。这需要身份证明 对那些处于危险中的人进行治疗，并针对他们进行有效的治疗。目前识别这一群体的方法 包括使用纤维化标记物，如FIB4，肝脏硬度测量(LSM)，评估肝脏 静脉压力梯度和/或静脉曲张(内窥镜)和传统的肝功能测量。这些是 不幸的是，受限于某些模型的中等精度，大多数数据集具有追溯性、单中心的性质 发布并缺乏关于这些参数随时间变化对动态的影响的信息 风险概况的变化。本方案的创新之处在于系统、肝脏 血流灌注和功能，以及门脉高压相关参数，以整体模拟蕾丝和门脉高压的风险 生成对更改敏感的概率分数。我们将特别关注基于MRI的测量方法 全身性代谢功能障碍(代谢表型)，加多西汀摄取和清除(综合测量 肝血流灌注和清除功能)和脾硬度测量(SSM)作为门静脉的替代指标 高血压。我们进一步提出了新的假设，即包括这些指标的整体模型 捕捉肝脏失代偿事件的多因素来源优于用于 NASH所致代偿性肝硬变患者发生花边概率的常规做法。这个 假说将在由NASH引起的代偿性肝硬变的纵向队列研究中得到验证。具体的 对代谢表型的测量将包括内脏脂肪组织体积、无脂肪肌肉体积、肌肉 脂肪渗入。Gadoxetate的摄取和清除将在10分钟的检查中进行测量。SSM探测器是 最近获得批准，并将部署在瞬时弹性成像的旗舰仪器Fibroscan630上。 Metabo表型鉴定需要根据常规的临床成像序列实施成像方案， 在常规使用加多西汀的情况下，添加不到10分钟的扫描时间的标准临床扫描仪 用于肝脏成像。次级目标1将单独和结合对基线参数进行建模，以确定结果风险 在1-2年内。次级目标2将评估测试措施的值随时间的动态变化，并与 他们对结果风险的变化做出了反应。将采用回归和机器学习的方法来 生成结果的概率分数。将执行敏感度分析以测试 模特们。需要的患者群体和所有的方法/专业知识都是可用的。这样做的理由是 建议是，它将提供一种方法来识别那些患有纳什肝硬化症的人，这种方法可以 结合到临床护理中。这将通过改善个别患者的护理和药物产生强烈的积极影响 通过确定将从治疗中受益最大的人群来开发和优化护理提供。

Hepatic decompensation (overt ascites, encephalopathy and variceal hemorrhage) and mortality in patients with nonalcoholic steatohepatitis (NASH) increases exponentially with the development of cirrhosis. Prevention of such liver-associated clinical events (LACE) is therefore a major goal of therapeutics. This requires identification of those at risk and targeting them with effective therapeutics. Current approaches to identify this population include the use of fibrosis markers such as FIB4, liver-stiffness measurement (LSM), assessment of hepatic venous pressure gradient and/or varices (endoscopy) and traditional measures of liver function. These are unfortunately limited by modest accuracy of some models, retrospective, single center nature of most data-sets published and lack of information on the impact of changes in these parameters over time with respect to dynamic changes in risk profile. This proposal innovates by novel application and integration of systemic, hepatic perfusion and function, and portal hypertension related parameters to holistically model the risk of LACE and generate a probability score that is sensitive to change. We will specifically focus on MRI-based measures of systemic metabolic dysfunction (metabo-phenotype), gadoxetate uptake and clearance (integrated measure of hepatic perfusion and clearance function) and spleen stiffness measurement (SSM) as a surrogate for portal hypertension. We further propose the novel hypothesis that holistic models including these measures and capturing the multi-factorial origin of hepatic decompensation events are superior to conventional tools used in routine practice to define the probability of LACE in patients with compensated cirrhosis due to NASH. The hypothesis will be tested in a longitudinal cohort study of compensated cirrhosis due to NASH. The specific measures of the metabo-phenotype will include visceral adipose tissue volume, fat-free muscle volume, muscle fat infiltration. Gadoxetate uptake and clearance will be measured in a 10-minute exam. The SSM probe was recently approved and will be deployed on Fibroscan 630 the flagship instrument for transient elastography. Metabo-phenotyping requires implementing an imaging protocol, based on a routine clinical imaging sequence, onto standard clinical scanners which adds less than 10 minutes of scan-time while gadoxetate is routinely used for liver-imaging. Sub-aim 1 will model baseline parameters, alone and in combination, to define outcome risk within 1-2 years. Sub-aim 2 will evaluate dynamic changes in values of the test measures over time and relate them to changes in the risk of outcomes. Both regression and machine learned approaches will be taken to generate probability scores of the outcomes. Sensitivity analyses will be performed to test the robustness of the models. The patient populations needed and all of the methods/expertise are available. The rationale of this proposal is that it will provide a method for risk-identification in those with NASH-cirrhosis which can be incorporated in to clinical care. This will have a strong positive impact by improving individual patient care, drug development and optimizing care delivery by identifying the population that will benefit most from therapeutics.