Capturing Tumor Heterogeneity in Hepatocellular Carcinoma- A Radiomics Approach Systematically Tested in Transgenic Mice

放射组学似乎为医学中许多尚未解决的任务提供了很好的解决方案。将遗传和分子分析的多模态数据与高端诊断成像方法相结合，将在很大程度上彻底改变疾病诊断。因此，放射组学可以通过将肿瘤异质性与结果预测联系起来，为精准医学进入临床常规打开大门，这是个体化治疗的先决条件。然而，由于这种方法处于临床评价的初期，有各种影响因素，其中一些尚未得到很好的理解，因此需要标准化测试来评估其潜力并发现任何目前未知的局限性。此外，与我们今天的临床工作流程相比，放射组学将需要高度跨学科的团队，重点关注数学和信息学。在这个研究计划中，我们提出了一个高度多学科的方法来实施放射组学来研究肝细胞癌。由于HCC的基本诊断和治疗反应评估的标准诊断程序的局限性，本提案的目的是开发一种放射组学方法，用于HCC的高级分子诊断，以捕获（内部）肿瘤异质性的复杂性和由已建立的多激酶抑制剂诱导的治疗反应模式。最终目标是通过系统的放射组学分析来识别基于成像和非成像的生物标志物，从而识别和预测治疗反应。我们假设放射组学可以为以下两方面提供一个有希望的方法：(i)基于涉及分子和遗传相关的创新成像的原发性肝细胞癌的高级表征；（ii）描述受MKI治疗影响的细胞/分子过程。在已建立的动物模型的标准化条件下系统地测试放射组学将控制整个系统的实验方差，其程度在人类中是不可能的。为了解决这个复杂的问题，工作方案将由一个高度跨学科的研究小组执行，该小组由来自放射学、生物化学、医学物理学、仪器生物分析和应用计算机科学的五名主要研究人员组成。

Radiomics seem to offer great solutions for many as of yet unsolved tasks in medicine. Integrating multimodality data from genetic and molecular analyses with high-end diagnostic imaging methods will revolutionize disease diagnosis to a great extent. Thus, Radiomics could open the door for entry of precision medicine into clinical routine by linking tumor heterogeneity with outcome prediction, a prerequisite for individualized treatment. However, since this methodology is at the very beginning of clinical evaluation with various influencing factors, some of which are not yet well-understood, standardized testing is required to evaluate its potential and to uncover any currently unknown limitations. Moreover, in contrast to our today`s clinical workflow Radiomics will require highly transdisciplinary teams with a strong focus on mathematics and informatics.With this research proposal we submit a highly multidisciplinary approach for the implementation of Radiomics to study hepatocellular cancer. Due to the limitations of standard diagnostic procedures in both primary diagnosis of HCC as well as treatment response assessment, the purpose of this proposal is to develop a radiomics approach for advanced molecular diagnosis of HCC that captures the complexity of (intra-)tumoral heterogeneity and treatment response patterns induced by an established Multi Kinase Inhibitor. The ultimate goal is to identify imaging and non-imaging based biomarkers by a systematic radiomics analysis that can identify and predict treatment response. We hypothesize that radiomics could offer a promising approach for both, (i) an advanced characterization of primary hepatocellular carcinoma based on innovative imaging that involves molecular as well as genetic correlates and (ii) the delineation of cellular/molecular processes affected by MKI treatment. Testing radiomics systematically under the standardized conditions of established animal models will control experimental variance of the entire system to an extent that is not possible in humans.To adress this complex topic the work programme will be performed by a highly transdisciplinary research team, consisting of five principal investigators from radiology, biochemistry, medical physics, instrumental bioanalytics and applied computer science.