肝细胞癌是最常见的原发性恶性肝肿瘤,最常见于慢性肝病。肝移植是一种治愈性治疗选择,是一种理想的解决方案,因为它解决了慢性潜在的肝脏疾病,同时消除了恶性病变。然而,由于器官短缺,根据临床指南,这种治疗方法只能应用于精心选择的患者。人工智能是一种新兴技术,在医学中具有多种应用,对与医学成像一起工作的领域具有优势,比如放射学.在这些技术的帮助下,费力的任务可以自动化,并且可以基于像素级分析开发新的病变成像标准。我们的目标是审查可以实施的AI应用程序,以更好地对肝移植候选人进行分层。论文分析了应用AI进行肝脏分割,脂肪变性的评估,肌肉减少症评估,病变检测,分割,和表征。肝移植是慢性肝病背景下肝细胞癌患者的最佳治疗方法。此外,AI可以为改善肝移植候选人的管理提供解决方案,以提高生存率。
Hepatocellular carcinoma is the most common primary malignant hepatic tumor and occurs most often in the setting of chronic liver disease. Liver transplantation is a curative treatment option and is an ideal solution because it solves the chronic underlying liver disorder while removing the malignant lesion. However, due to organ shortages, this treatment can only be applied to carefully selected patients according to clinical
guidelines. Artificial intelligence is an emerging technology with multiple applications in medicine with a predilection for domains that work with medical imaging, like radiology. With the help of these technologies, laborious tasks can be automated, and new lesion imaging criteria can be developed based on pixel-level analysis. Our objectives are to review the developing AI applications that could be implemented to better stratify liver transplant candidates. The papers analysed applied AI for liver segmentation, evaluation of steatosis, sarcopenia assessment, lesion detection, segmentation, and characterization. A liver transplant is an optimal treatment for patients with hepatocellular carcinoma in the setting of chronic liver disease. Furthermore, AI could provide solutions for improving the management of liver transplant candidates to improve survival.