摘要
恶性肿瘤是严重威胁人类健康的重大疾病,精准诊断和疗效评估是提高临床治疗效果、降低肿瘤相关死亡率的关键。随着人工智能在医学图像领域的深入发展,影像组学与病理组学应运而生并在肿瘤诊治过程中显示出巨大的潜力,但也分别显示出其缺乏生物学验证以及缺乏肿瘤宏观属性的局限性。将两者跨模态跨尺度结合,彼此取长补短很有必要。本文对影像组学和病理组学工作流程及两者联合在肿瘤方面的应用进展、局限性及未来展望进行综述。
Cancers are significant diseases that seriously threaten human health.Accurate diagnosis and efficacy assessment are the keys to improving clinical treatment and reducing cancer-related mortality.With the further development of artificial intelligence in medical imaging,radiomics and pathomics have emerged and shown great potential in diagnosing and treating cancers.However,at the same time,radiomics and pathomics have also shown their limitations of lacking biological validation and macroscopic properties of cancers,respectively.Combining them across modalities and scales is necessary to complement each other's strengths.This paper reviewed the progress,limitations,and future perspectives of radiomics and pathomics workflows and their combined application in cancers.
作者
曹颖
王晓霞
张久权
CAO Ying;WANG Xiaoxia;ZHANG Jiuquan(School of Medicine,Chongqing University,Chongqing 400030,China;Department of Radiology,Chongqing University Cancer Hospital,Chongqing 400030,China)
出处
《中国医学影像学杂志》
CSCD
北大核心
2024年第5期524-528,共5页
Chinese Journal of Medical Imaging
基金
重庆市自然科学基金(cstc2021jcyj-msxmX0387)
重庆市卫生健康委员会医学科研项目(2022WSJK027)
中华国际医学交流基金会SKY影像科研基金项目(Z-2014-07-2101)。
关键词
肿瘤
人工智能
影像组学
病理组学
综述
Neoplasms
Artificial intelligence
Radiomics
Pathomics
Review
