Integrating multi-source data to reveal potential biological basis for radiomics based prognostic stratification of colorectal cancer
直肠癌是全球发病率和死亡率较高的恶性肿瘤之一。医学影像在结直肠癌诊疗决策中至关重要。影像组学(Radiomics)作为一种从医学影像中提取高维量化特征并将其与临床结果相关联的方法,为推进肿瘤个体化诊疗提供了新的机遇。然而,缺乏预测机制与肿瘤潜在生物学基础之间的关联性证据,一定程度上限制了影像组学的临床应用。广东省人民医院刘再毅教授团队最近在Science Bulletin杂志发表的研究“Integrated analysis of radiomics, RNA, and clinicopathologic phenotype reveals biological basis of prognostic risk stratification in colorectal cancer”采用了创新的多模态数据整合分析方法,探索基于CT影像的影像组学模型在预测结直肠癌患者术后生存风险中的应用,并深入研究其潜在的生物学机制,为影像组学预测机制提供了新的方法学框架。
Authors
- Yu Fu (ORCID: https://orcid.org/0000-0003-1174-944X)
- Shengnan Mou
- Huimao Zhang
Publication Details
- Journal
- Chinese Science Bulletin (Chinese Version)
- Published
- 2025-04-03
- DOI
- https://doi.org/10.1360/tb-2025-0088
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00