Immunotherapy and targeted therapy for cholangiocarcinoma: Artificial intelligence research in imaging

免疫疗法 医学 恶性肿瘤 靶向治疗 肿瘤微环境 癌症 内科学
作者
Jiong Liu,Jian Shu
出处
期刊:Critical Reviews in Oncology Hematology [Elsevier]
卷期号:194: 104235-104235 被引量:3
标识
DOI:10.1016/j.critrevonc.2023.104235
摘要

Cholangiocarcinoma (CCA) is a highly aggressive hepatobiliary malignancy, second only to hepatocellular carcinoma in prevalence. Despite surgical treatment being the recommended method to achieve a cure, it is not viable for patients with advanced CCA. Gene sequencing and artificial intelligence (AI) have recently opened up new possibilities in CCA diagnosis, treatment, and prognosis assessment. Basic research has furthered our understanding of the tumor-immunity microenvironment and revealed targeted molecular mechanisms, resulting in immunotherapy and targeted therapy being increasingly employed in the clinic. Yet, the application of these remedies in CCA is a challenging endeavor due to the varying pathological mechanisms of different CCA types and the lack of expressed immune proteins and molecular targets in some patients. AI in medical imaging has emerged as a powerful tool in this situation, as machine learning and deep learning are able to extract intricate data from CCA lesion images while assisting clinical decision making, and ultimately improving patient prognosis. This review summarized and discussed the current immunotherapy and targeted therapy related to CCA, and the research progress of AI in this field.
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