Early Detection of Hepatocellular Carcinoma

在美国，肝细胞癌是癌症相关死亡中增长最快的原因。 为了解决这一问题的严重性，至关重要的是要识别出那些肝癌和 制定有效的早期诊断监测策略。肝硬变是肝细胞癌的主要危险因素。双人- 年度超声和α-胎儿蛋白仍然是最常用的监测手段 尽管灵敏度和特异度很低，但仍可诊断为肝硬变。我们的目标是确定一种基于血液的风险模型 肝硬变患者的分层，以及基于血液和肝脏的综合成像模型 优化高危患者的肝细胞癌早期检测。在第一次赠款期间，我们开发了一个多中心 对比剂MRI监测下的肝硬变患者的前瞻性队列。这样的队列提供了一个独特的 严格研究患者临床材料上的血液生物标志物和影像特征的机会 在监测环境中被归类为患有早期疾病。配对血液的纵向采集 这些患者的样本和核磁共振成像在评估早期血液标志物和 在观察病变以获得肝细胞癌诊断的过程中，影像特征变为阳性。 到目前为止，已经登记了912名肝硬变患者，并对2590份血液样本和核磁共振成像进行了配对 收好了。在随访期间，63例患者发展为肝细胞癌，212例患者有可检出的病变(S)。同时， 我们已经在血浆和外体、蛋白质和代谢物中确定了肝细胞癌风险的预测和早期 侦测。我们还开发了基于定量成像和人工智能(AI)的方法来分析 肝癌患者的影像扫描。我们演示了体素增强模式是如何 标测(EPM)可以提高CT扫描的对比度噪声比。我们将这一发现扩展到核磁共振成像中 肝细胞癌患者，包括我们预期队列中的患者。EPM信号与PRE的差异 诊断磁共振成像到诊断磁共振成像可能会改善早期发现和病变特征。我们基于人工智能的 工具通过提供高通量工具来处理数以千计的磁共振成像来补充EPM算法 从我们的患者队列中以高效和准确的方式进行治疗。在这一竞争更新中，我们将延长 并进一步评估这些新的血液和肝脏MRI标记物的性能。我们会 确定纵向变化并评估其检测临床前疾病的能力。我们将确定 最能预测肝癌发展的标记物小组，因此在风险评估中可能有用处 肝细胞癌的早期发现。这一建议在一项研究中实现了两个主要目标：一)早期发现和二) 当生物标志物变为阳性时，肿瘤的特征。影响是多方面的：使患者免于 不必要的成像测试；识别高危患者并触发执行MRI进行监视的决定 代替超声波；在早期阶段发现病变，以便进行根治治疗。加在一起，这些临床 应用将显著降低肝细胞癌监测的成本并提高肝细胞癌患者的存活率。

Hepatocellular carcinoma (HCC) is the fastest growing cause of cancer-related death in the United States. To address the magnitude of this problem, it is critically important to identify those at high risk for HCC and institute effective surveillance strategies for early diagnosis. Liver cirrhosis is the main risk factor for HCC. Bi- annual ultrasound and α-fetoprotein remains the surveillance modality most frequently used in patients with cirrhosis, despite very low sensitivity and specificity. Our goals are to identify a blood-based model for risk stratification in patients with cirrhosis, as well as an integrated blood-based and liver imaging model to optimize early HCC detection in high-risk patients. During the first grant period, we developed a multi-center prospective cohort of patients with cirrhosis under contrast MRI surveillance. Such cohort provides a unique opportunity to study blood biomarkers and imaging features on clinical material from patients rigorously classified as having a very early disease in a surveillance setting. Longitudinal collection of paired blood samples and MRIs from these patients is particularly valuable in assessing how early blood markers and imaging features become positive during the period when lesions are observed to obtain a diagnosis of HCC. To date, 912 cirrhotic patients have been enrolled and 2590 paired blood samples and MRIs have been collected. During follow-up, 63 patients developed HCC and 212 patients had detectable lesion(s). In parallel, we have identified in plasma and exosomes, proteins and metabolites for HCC risk prediction and early detection. We also developed quantitative imaging and artificial intelligence (AI)-based methods to analyze imaging scans of patients with liver cancers. We demonstrated how voxel-wise enhancement pattern mapping (EPM) can improve the contrast-to-noise ratio in CT scans. We extended this finding to MRIs for patients with HCC, including patients in our prospective cohort. Differences in EPM signals from pre- diagnostic MRIs to diagnostic MRIs may improve early detection and lesion characterization. Our AI-based tools complement the EPM algorithm by providing high-throughput tools to process the thousands of MRIs from our patient cohort in an efficient and accurate manner. In this competing renewal, we will extend the existing cohort and further evaluate the performance of these novel blood and liver MRI markers. We will determine longitudinal changes and evaluate their capacity to detect preclinical disease. We will identify the panel of markers that best predict HCC development and that could therefore have utility in risk assessment and early detection of HCC. This proposal achieves in one study two major goals: i) early detection and ii) characterization of tumors when biomarker becomes positive. The impact is multiple: spare patients from unnecessary imaging tests; identify high-risk patients and trigger the decision to perform MRI for surveillance instead of ultrasound; detect lesions at an early stage allowing for curative treatment. Together, these clinical applications would significantly reduce the cost of HCC surveillance and improve survival of HCC patients.