A histopathology-based artificial intelligence system assisting the screening of genetic alteration in intrahepatic cholangiocarcinoma.

IF 6.4 1区 医学 Q1 ONCOLOGY
Han Xiao, Jianping Wang, Zongpeng Weng, Xiaoxuan Lin, Man Shu, Jingxian Shen, Peng Sun, Muyan Cai, Xiao Xiang, Bin Li, Lihong Wei, Yiyu Shi, Jiaming Lai, Ming Kuang, Jingping Yun, Shuling Chen, Sui Peng
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引用次数: 0

Abstract

Background: Targeted therapy for intrahepatic cholangiocarcinoma (ICC) shows superior survival outcomes but patients with certain targetable alterations are no more than 20%. Genetic alteration screening for all ICC patients is of high cost and not routinely performed. This study intends to develop a histopathology-based artificial intelligence (AI)-assisted system for predicting genetic alteration of ICC.

Methods: We constructed a Genetic Alteration Prediction (GAP) system based on multi-instance learning and self-supervised learning to predict genetic alterations using whole-slide images (WSIs) of H&E-stained slides. A total of 2069 WSIs from 232 ICC patients underwent surgery of the FAH-SYSU dataset were used for model construction and adjustment by five-fold cross-validation. Another 150 patients from three medical centres were used as independent external validations. We also compared the cost-effectiveness of GAP-assisted precise treatment and all-sequencing strategy to non-sequencing strategy.

Results: The GAP was able to predict actionable genetic alterations of ICC, including FGFR2 and IDH. The area under the receiver operating characteristic curves (AUC) for FGFR2 and IDH were 0.754 and 0.713 in the internal dataset, and 0.724 and 0.656 in the external dataset, respectively. Furthermore, compared to giving chemotherapy without sequencing for every patient, GAP-assisted precise treatment could increase 1 progression-free quality-adjusted life month with a cost of $13871.72, the co-responding figure for all-sequencing strategy is $44538.93. Decision curve analysis showed that AI-assisted strategy provides better clinical benefits.

Conclusions: We constructed an AI-assisted genetic alteration screening system which is predictable to ICC actionable targets and has potential to assist precise targeted treatment of advanced ICC.

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来源期刊
British Journal of Cancer
British Journal of Cancer 医学-肿瘤学
CiteScore
15.10
自引率
1.10%
发文量
383
审稿时长
6 months
期刊介绍: The British Journal of Cancer is one of the most-cited general cancer journals, publishing significant advances in translational and clinical cancer research.It also publishes high-quality reviews and thought-provoking comment on all aspects of cancer prevention,diagnosis and treatment.
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