在食道癌症个性化新辅助免疫化学疗法的多模式协同模型
Zihan Zhao1, Dexia Chen2, Xiaolong Wei3
1Department of Pathology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
Cell reports. Medicine
|December 9, 2025
概括
一个新的AI工具,eSPARK,使用常规临床数据预测食道癌症中新辅助免疫化学疗法的反应. 这种方法增强了个性化治疗决策,并确定了改善结果的关键生物标志物.
科学领域:
- 在瘤学瘤学.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 新辅助免疫化学疗法 (nICT) 改善了局部晚期食道癌 (EC) 的结果.
- 预测患者对nICT的反应仍然是一个重大的临床挑战.
- 准确的反应预测对于优化EC治疗策略至关重要.
研究的目的:
- 开发和验证eSPARK,一种多式人工智能框架,用于预测EC中对nICT的病理完整反应 (pCR).
- 整合常规可用的临床数据,包括CT成像和病理学,以提高预测准确度.
- 确定与EC患者的nICT反应相关的潜在生物标志物.
主要方法:
- 使用多式数据 (CT成像,病理幻灯片) 来开发eSPARK,来自三个地区的344名EC患者.
- 将细胞学语义信息纳入AI模型.
- 在多中心数据集中验证了模型的概括性和预测性能.
- 使用多尺度可解释性模块来识别生物标志物.
主要成果:
- 与单一模式模型相比,eSPARK表现出优越的概括性和强大的预测准确性.
- 该框架在独立的多中心数据集中实现了强的性能.
- 确定了与nICT反应相关的生物标志物,包括中性粒细胞与淋巴细胞比率 (NLR).
结论:
- 在本地先进的EC中,eSPARK提供了一个强大的工具,用于个性化治疗决策.
- 通过人工智能进行多学科数据集成可以推进精确瘤学.
- 该框架对改善欧盟的nICT治疗策略有重大影响.
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