Detection, risk stratification and therapy monitoring of hepatocellular carcinoma – a deep learning approach based on iodine maps derived from dual energy computed tomography

原发性肝癌是全球第六种最常见的癌症类型，也是导致癌症死亡的第四大原因，而肝细胞癌是其最常见的形式。对于基于动态对比增强计算机断层扫描(CT)或磁共振成像的肝细胞癌的诊断，有明确的诊断标准(LI-RADS)，其中包括基于肿瘤血流灌注的诊断标准。与常规CT相比，双能CT碘图可以更准确地确定这些血流模式，因为它们允许对含碘造影剂进行精确的定量。先前的研究表明，这些碘图可以用来提高对肝癌的诊断，特别是在诊断具有挑战性的病例中(例如，非常小的肝癌病变)。此外，还表明它们有助于局部肿瘤治疗(如微波消融术、射频消融术、经动脉化疗栓塞术)患者的疗效评估。另一方面，先进的机器学习方法在放射学的几乎每一个领域都越来越重要。其中一种方法，即所谓的深度学习，已经被证明对肝癌的成像也是有益的。在这个项目中，由几种不同的双能CT扫描仪获得的定量碘地图将被转移到深度学习模型中，以评估这两种新兴技术的结合在接受局部区域肿瘤治疗的患者中是否有助于肝癌的检测和鉴别及其风险分层和治疗监测。

Primary liver cancer is the sixth most common cancer type worldwide and the fourth major cause of cancer deaths, while hepatocellular carcinoma (HCC) represents its most common form. For diagnosis of HCC based on dynamic, contrast-enhanced computed tomography (CT) or magnetic resonance imaging, there are defined diagnostic criteria (LI-RADS) which, inter alia, are based on tumor perfusion. These perfusion patterns can be determined more accurately in dual-energy CT-derived iodine maps as compared to conventional CT as they allow for precise quantification of iodinated contrast media. Previous studies have shown that these iodine maps can be used to improve diagnosis of HCC, particularly in diagnostically challenging cases (e.g. very small HCC lesions). Moreover, it was shown that they can be beneficial for the response assessment of patients who underwent locoregional tumor therapy (e.g. microwave ablation, radiofrequency ablation, transarterial chemoembolization). On the other hand, advanced machine learning methods continuously gain importance in almost every field of radiology. One of these methods, the so-called deep learning, has been shown to be beneficial for imaging of HCC as well. In this project, quantitative iodine maps derived by several different dual-energy CT scanners will be transferred to deep learning models to assess whether the combination of these two emerging technologies is beneficial in terms of detection and differentiation of HCC and its risk stratification and therapy monitoring in patients who underwent locoregional tumor therapy.