超越标准放射治疗:人工智能驱动的个性化放射治疗框架,在头部和部状细胞癌 (HNSCC) 患者中进行四步分类
Yongxin Guo1,2, Eric O Aboagye1, Dorothy M Gujral3
1Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, W12 0NN, United Kingdom.
Current oncology reports
|November 1, 2025
概括
人工智能 (AI) 模型在个性化头癌 (HNC) 放射治疗方面表现有前途. 放射学分析可以预测结果,并指导适应风险的治疗方法,改善患者护理.
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:
- 放射治疗 (RT) 是对头癌 (HNC) 的首要治疗方法.
- 个性化RT面临挑战,治疗阶段的结果各不相同.
研究的目的:
- 评估AI驱动模型在HNC个性化放射治疗策略中的潜力.
- 评估人工智能如何弥合个性化RT的现有差距.
主要方法:
- 审查放射学和人工智能驱动的成像分析方法.
- 对人工智能驱动的多模式和多时态成像模型的分析.
- 审查拟议的四步人工智能驱动的RT框架.
主要成果:
- 放射学为预测生存,治疗反应和毒性提供了定量特征.
- 放射学模型显示出高预测效率 (C指数/AUC>0.70).
- 人工智能模型可以对患者进行分层,并指导风险适应的放射治疗.
结论:
- 人工智能驱动的放射学在HNC中具有个性化放射治疗的巨大潜力.
- 人工智能模型可以增强治疗分层和风险适应.
- 一个标准化的AI框架可以促进未来的临床试验和证据生成.
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