论著摘要 |【综述】使用下一代成像技术揭示肿瘤异质性:影像组学,影像基因组学和肿瘤微环境(双语版)

2017-09-27 11:23:52 admin 0

Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging.发表日期: 2016.10.11   来源: Clinical Radiology,2017,72: 3-10.

作者

E.Salaa ,E.Memaa,b  ,Y.Himotoa  ,H.Veeraraghavanc ,J.D.Brentond  ,A.Snydere  ,B.Weigeltf,H.A.Vargasa.

作者介绍: ,

a. Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA

b. Department of Radiology, New York Presbyterian/Columbia University Medical Center, 622 W 168th St., New York, NY 10032, USA

c. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA

d. Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK

e. Department of Medicine, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA

f. Department of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA

 

摘要

肿瘤的异质性在癌症的组织水平和基因水平均有发现。据报道高水平的肿瘤内基因水平的异质性也与不良临床结果有关。本篇综述对影像组学,影像基因组学和肿瘤微环境进行了概述,同时评价了这个新的领域在肿瘤异质性的诊断中的作用与前景。本文阐述了影像组学和影像基因组学在辅助癌症诊断和癌症侵袭性方面潜在的价值。讨论了影像基因组学分析如何通过预测药物反应和潜在的治疗障碍来指导未来的癌症个性化诊断方案的制定,同时评价了他在影像组学中找到肿瘤诊断的标志物中的作用。最后,讨论了目前这一新的领域在发展过程中存在的障碍,包括重现性,验证需求,成像处理标准化,数据共享和向临床的转化。同时也给出了应对这些挑战的潜在解决方案,最终实现肿瘤疾病的进准医疗。

Abstract

Tumour heterogeneity in cancers has been observed at the histological and genetic levels, and increased levels of intra-tumour genetic heterogeneity have been reported to be associated with adverse clinical outcomes. This review provides an overview of radiomics, radiogenomics, and habitat imaging, and examines the use of these newly emergent fields in assessing tumour heterogeneity and its implications. It reviews the potential value of radiomics and radiogenomics in assisting in the diagnosis of cancer disease and determining cancer aggressiveness. This review discusses how radiogenomic analysis can be further used to guide treatment therapy for individual tumours by predicting drug response and potential therapy resistance and examines its role in developing radiomics as biomarkers of oncological outcomes. Lastly, it provides an overview of the obstacles in these emergent fields today including reproducibility, need for validation, imaging analysis standardisation, data sharing and clinical translatability and offers potential solutions to these challenges towards the realisation of precision oncology.

阅读原文:https://doi.org/10.1016/j.crad.2016.09.013

 


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