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[肿瘤精准医学中的医学成像:机遇与挑战]

[Medical imaging in tumor precision medicine: opportunities and challenges].

作者信息

Xu Jingjing, Tan Yanbin, Zhang Minming

机构信息

Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China.

出版信息

Zhejiang Da Xue Xue Bao Yi Xue Ban. 2017 May 25;46(5):455-461. doi: 10.3785/j.issn.1008-9292.2017.10.01.

DOI:10.3785/j.issn.1008-9292.2017.10.01
PMID:29488709
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10396976/
Abstract

Tumor precision medicine is an emerging approach for tumor diagnosis, treatment and prevention, which takes account of individual variability of environment, lifestyle and genetic information. Tumor precision medicine is built up on the medical imaging innovations developed during the past decades, including the new hardware, new imaging agents, standardized protocols, image analysis and multimodal imaging fusion technology. Also the development of automated and reproducible analysis algorithm has extracted large amount of information from image-based features. With the continuous development and mining of tumor clinical and imaging databases, the radiogenomics, radiomics and artificial intelligence have been flourishing. Therefore, these new technological advances bring new opportunities and challenges to the application of imaging in tumor precision medicine.

摘要

肿瘤精准医学是一种用于肿瘤诊断、治疗和预防的新兴方法,它考虑了环境、生活方式和基因信息的个体差异。肿瘤精准医学建立在过去几十年发展起来的医学成像创新基础之上,包括新硬件、新型成像剂、标准化方案、图像分析和多模态成像融合技术。此外,自动化且可重复的分析算法的发展从基于图像的特征中提取了大量信息。随着肿瘤临床和成像数据库的不断发展与挖掘,放射基因组学、放射组学和人工智能蓬勃发展。因此,这些新的技术进步给成像技术在肿瘤精准医学中的应用带来了新的机遇和挑战。

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1
[Medical imaging in tumor precision medicine: opportunities and challenges].[肿瘤精准医学中的医学成像:机遇与挑战]
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Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches.脑肿瘤的放射组学:图像评估、定量特征描述符和机器学习方法。
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