人工智能在肝癌精准诊疗中的研究进展

Research progress of artificial intelligence in precision diagnosis and treatment of liver cancer

摘要:

随着人工智能（AI）技术，尤其是深度学习的快速发展，AI在肝癌的诊疗中扮演着越来越重要的角色。AI技术在提高肝癌诊断准确性、减轻医生工作负担以及提供个性化治疗方案方面展现出巨大潜力。在肝癌影像诊断方面，AI技术已经被广泛应用于超声、CT和MRI等影像学数据，能够自动识别和分割肝脏病变，区分良性和恶性病变，其诊断准确率在某些情况下可达到甚至超过专业放射科医师的水平。在病理学诊断中，AI技术通过分析数字病理切片，辅助病理学家进行鉴别诊断和分类，提高诊断的效率和准确性。在治疗决策辅助方面，AI技术通过分析病人的临床、影像学和病理学数据，能预测术后复发风险和对特定治疗的治疗效果，以及识别生物标志物，为精准治疗提供新视角，辅助临床医生制定个性化治疗方案。随着多模态AI模型的发展，结合影像、病理和临床数据的分析，能够更全面地理解肝癌的生物学行为，为病人提供更精准的诊断和治疗。尽管AI在肝癌诊疗中显示出巨大潜力，但仍面临数据标准化、安全性、隐私保护等挑战，AI模型在临床实践中的转化需要进一步验证和改进。预计随着技术进步和数据积累，AI将在未来为肝癌病人提供更精准、个性化的医疗服务。本文将重点概述AI在肝癌诊疗中的重要研究进展，并简要讨论其局限性及未来发展方向。

Abstract:

With the rapid development of artificial intelligence (AI) technology, especially deep learning, AI is playing an increasingly important role in the diagnosis and treatment of liver cancer. AI has shown great potential in improving diagnostic accuracy, reducing the workload of physicians, and providing personalized treatment plans. In imaging diagnosis of liver cancer, AI technology has been widely applied to ultrasound, CT, and MRI data, enabling automatic recognition and segmentation of liver lesions and differentiation between benign and malignant lesions. In some cases, its diagnostic accuracy can match or even surpass that of professional radiologists. In pathological diagnosis, AI assists pathologists in differential diagnosis and classification by analyzing whole slide image, improving diagnostic efficiency and accuracy. For treatment decision support, AI analyzes clinical, imaging, and pathological data to predict postoperative recurrence risk, evaluate the effectiveness of specific treatments, and identify biomarkers, providing new perspectives for precision medicine and assisting clinicians in designing personalized treatment plans. With the advancement of multimodal AI models that integrate imaging, pathology, and clinical data, it is possible to achieve a more comprehensive understanding of the biological behavior of liver cancer, thereby offering more precise diagnoses and treatments for patients. Despite its immense potential, AI in liver cancer diagnosis and treatment faces challenges such as data standardization, security, and privacy protection. The clinical translation of AI models requires further validation and refinement. With technological advancements and data accumulation, AI is expected to provide more precise and personalized medical services for liver cancer patients in the future. This article focuses on summarizing significant research advances in AI for liver cancer diagnosis and treatment, and briefly discusses its limitations and future directions.