NOVEL STRATEGIES TO IMPROVE LIVER CANCER SURVEILLANCE UPTAKE AND EARLY DETECTION

摘要 本提案是根据RFA-CA-17-025提交的。其中，肝细胞癌是最常见的 常见的原发性肝癌，是美国发病率上升的为数不多的癌症之一。 肝癌患者的存活率很低，因为大多数患者在接受治疗时都是在晚期确诊的。 选择是有限的。肝细胞癌监测可以及早发现癌症并提高存活率，但这并不一致 实施。并不是所有在监视成像上发现的肝脏结节都是恶性的，这些不确定 结节需要后续成像以确定是否为肝细胞癌。这项建议组建了一个专家团队。 在肝病、肝癌、放射学、工程学、统计学和信息学方面具有互补的专业知识 技术我们的目标是：(1)通过提高肝硬变患者对肝细胞癌的监测能力 电子医疗记录，提醒医疗保健提供者和患者何时应进行筛查测试； (2)利用解析形态组学和机器学习技术提高肝癌的早期诊断率； 以及(3)使用标记的肝细胞癌特异性多肽在早期阶段提高对肝细胞癌的可检测性。我们一直在努力 多年来密切合作，参与/领导了许多由NIH资助的临床研究网络。我们 有专业知识和经验进行拟议的研究，并将与其他中心在 肝脏中心网络，以验证我们开发的方法/模型。我们还将招收肝硬变患者。 并收集数据和样本，并提供对现有特征良好的数据和样本的访问 包括跨网络研究的流行的和偶发的肝细胞癌的资料库。我们有信心我们会的 能够以多种方式为这一肝癌网络和肝细胞癌的早期发现做出贡献。

ABSTRACT This proposal is submitted in response to RFA-CA-17-025. Hepatocellular carcinoma (HCC) is the most common primary liver cancer and one of the few cancers with increasing incidence in the United States. Survival of patients with HCC is poor because most patients are diagnosed at late stages when treatment options are limited. HCC surveillance can detect cancers early and improve survival but it is inconsistently implemented. Not all liver nodules detected on surveillance imaging are malignant, these indeterminate nodules require follow up imaging to determine if they are HCC. This proposal assembles a team of specialists with complementary expertise in liver diseases, liver cancer, radiology, engineering, statistics, and information technology. The goals are to: (1) Improve HCC surveillance uptake in patients with cirrhosis by leveraging electronic medical records to remind healthcare providers and patients when they are due for screening tests; (2) Leverage analytic morphomics and machine learning to increase the detectability of HCC at an early stage; and (3) Increase detectability of HCC at an early stage using tagged HCC-specific peptides. We have worked closely together for many years and have participated/led many NIH funded clinical research networks. We have expertise and experience to carry out the proposed studies and will collaborate with other centers in the Liver Center Network to validate the methods/models we develop. We will also enroll patients with cirrhosis and collect data and specimens and provide access to existing well characterized data and specimen repositories that include both prevalent and incident HCC for Trans-Network studies. We are confident we will be able to contribute to this Liver Cancer Network and to early detection of HCC in multiple ways.