Primary Liver Cancer CECT Imaging Dataset
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Primary liver cancer is a significant global health issue, characterized by high incidence and mortality rates worldwide. Accurate diagnosis and classification of subtypes are essential for selecting appropriate treatment options and enhancing patient outcomes. Contrast-enhanced computed tomography (CECT) has proven highly sensitive and specific in diagnosing liver cancer. Currently, publicly available datasets of liver cancer CECT scans are limited and often do not comprehensively cover liver cancer subtypes or include complete phasing of CT scans. We hypothesize that utilizing full-phase 3D CECT images, including the Plain, Arterial, Venous, and Delayed phases, can improve the diagnostic classification performance for liver cancer. To test this hypothesis, we have collected a large dataset from a single medical institution that includes 275 cases of liver cancer, featuring Hepatocellular Carcinoma (HCC), Intrahepatic Cholangiocarcinoma (ICC), and Combined Hepatocellular-Cholangiocarcinoma (cHCC-CCA), as well as CECT images from 83 non-liver cancer subjects. For each patient, we annotated the liver and lesion regions. This dataset, rich in liver cancer types and complete in CT phasing, facilitates the development and validation of diagnostic classification models and lesion segmentation models tailored to liver cancer CT imaging.
原发性肝癌是重大全球健康问题，具有全球高发病率与高死亡率的特征。精准诊断与亚型分类对于选择适宜治疗方案、改善患者预后至关重要。对比增强计算机断层扫描（Contrast-enhanced computed tomography, CECT）在肝癌诊断中已被证实具有较高的灵敏度与特异性。当前，公开可用的肝癌CECT扫描数据集数量有限，且往往未能全面覆盖肝癌亚型，亦未包含完整的CT扫描时相。我们提出假设：利用包含平扫期、动脉期、静脉期及延迟期的全时相三维CECT图像，可提升肝癌的诊断分类性能。为验证该假设，我们从单一医疗机构收集了大型数据集，包含275例肝癌病例，涵盖肝细胞癌（Hepatocellular Carcinoma, HCC）、肝内胆管癌（Intrahepatic Cholangiocarcinoma, ICC）及混合型肝细胞癌-胆管癌（Combined Hepatocellular-Cholangiocarcinoma, cHCC-CCA），同时纳入83例非肝癌受试者的CECT图像。我们为每位患者标注了肝脏及病灶区域。本数据集肝癌类型丰富、CT时相完整，可为针对肝癌CT成像的诊断分类模型与病灶分割模型的开发与验证提供有力支撑。
