Lu Cheng, Shiradkar Rakesh, Liu Zaiyi
Biomedical Engineering Department, Case Western Reserve University, Cleveland 44106, OH, USA.
Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou 510080, China.
Chin J Cancer Res. 2021 Oct 31;33(5):563-573. doi: 10.21147/j.issn.1000-9604.2021.05.03.
In the last decade, the focus of computational pathology research community has shifted from replicating the pathological examination for diagnosis done by pathologists to unlocking and discovering "sub-visual" prognostic image cues from the histopathological image. While we are getting more knowledge and experience in digital pathology, the emerging goal is to integrate other-omics or modalities that will contribute for building a better prognostic assay. In this paper, we provide a brief review of representative works that focus on integrating pathomics with radiomics and genomics for cancer prognosis. It includes: correlation of pathomics and genomics; fusion of pathomics and genomics; fusion of pathomics and radiomics. We also present challenges, potential opportunities, and avenues for future work.
在过去十年中,计算病理学研究领域的重点已从复制病理学家进行诊断的病理检查,转向从组织病理学图像中解锁和发现“亚视觉”预后图像线索。虽然我们在数字病理学方面获得了更多知识和经验,但新出现的目标是整合其他组学或模态,以有助于构建更好的预后分析方法。在本文中,我们简要回顾了一些代表性研究,这些研究专注于将病理组学与放射组学和基因组学整合用于癌症预后评估。内容包括:病理组学与基因组学的相关性;病理组学与基因组学的融合;病理组学与放射组学的融合。我们还提出了面临的挑战、潜在机遇以及未来工作的方向。