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Journal of Zhejiang University SCIENCE B 2018 Vol.19 No.1 P.6-24

http://doi.org/10.1631/jzus.B1700260


Towards precision medicine: from quantitative imaging to radiomics


Author(s):  U. Rajendra Acharya, Yuki Hagiwara, Vidya K. Sudarshan, Wai Yee Chan, Kwan Hoong Ng

Affiliation(s):  Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore 599489, Singapore; more

Corresponding email(s):   ngkh@ummc.edu.my

Key Words:  Radiological imaging, Personalised medicine, Precision medicine, Quantitative imaging, Radiogenomics, Radiomics


U. Rajendra Acharya, Yuki Hagiwara, Vidya K. Sudarshan, Wai Yee Chan, Kwan Hoong Ng. Towards precision medicine: from quantitative imaging to radiomics[J]. Journal of Zhejiang University Science B, 2018, 19(1): 6-24.

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Abstract: 
Radiology (imaging) and imaging-guided interventions, which provide multi-parametric morphologic and functional information, are playing an increasingly significant role in precision medicine. Radiologists are trained to understand the imaging phenotypes, transcribe those observations (phenotypes) to correlate with underlying diseases and to characterize the images. However, in order to understand and characterize the molecular phenotype (to obtain genomic information) of solid heterogeneous tumours, the advanced sequencing of those tissues using biopsy is required. Thus, radiologists image the tissues from various views and angles in order to have the complete image phenotypes, thereby acquiring a huge amount of data. Deriving meaningful details from all these radiological data becomes challenging and raises the big data issues. Therefore, interest in the application of radiomics has been growing in recent years as it has the potential to provide significant interpretive and predictive information for decision support. radiomics is a combination of conventional computer-aided diagnosis, deep learning methods, and human skills, and thus can be used for quantitative characterization of tumour phenotypes. This paper discusses the overview of radiomics workflow, the results of various radiomics-based studies conducted using various radiological images such as computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET), the challenges we are facing, and the potential contribution of radiomics towards precision medicine.

精准医学发展趋势:从定量成像到放射组学

概要:放射学(影像学)及影像引导的介入手段能提供多参数的形态学及功能信息,在精准医学中扮演着越来越重要的角色.因此,放射科医生需要理解影像表型,并将这些表型与潜在的疾病相关联,进而描述图像特征.但是为了能理解并描述异质性实体肿瘤的分子表型(基因组学信息),就需要通过活检取得这些组织更进一步的序列信息.因此,放射科医生为了能获得详尽的影像表型,需要从不同视图和角度采集图像,而这就产生了大量的数据.从所有这些影像数据中提取有意义的细节非常具有挑战性,并衍生出了大数据这个命题.因为影像组学有对诊断支持提供有意义的诠释性和预测性信息的潜力,所以近年来对于影像组学的关注越来越多.影像组学是传统的计算机辅助诊断、深度学习和人类技能的结合,因此它能被用来定量描述肿瘤表型.本文对影像组学流程的概览、基于不同手段(如计算机断层扫描(CT)、磁共振成像(MRI)和正电子发射计算机断层扫描(PET))的影像组学研究结果、面临的挑战和影像组学对于精准医学潜在的贡献等方面进行了讨论.
(感谢浙江大学医学院附属第二医院核医学科陈琳提供中文概要)

关键词:放射影像学;个体化医学;精准医学;定量成像;放射基因组学;放射组学

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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