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肺癌放射基因组学:影像学在肺癌患者个体化管理中的价值不断提升。

Lung Cancer Radiogenomics: The Increasing Value of Imaging in Personalized Management of Lung Cancer Patients.

机构信息

Department of Diagnostic Radiology, University of Hong Kong, Hong Kong.

Department of Computer and Electrical Engineering, National Chiao Tung University, HsinChu, Taiwan.

出版信息

J Thorac Imaging. 2018 Jan;33(1):17-25. doi: 10.1097/RTI.0000000000000312.

DOI:10.1097/RTI.0000000000000312
PMID:29252899
Abstract

Radiogenomics provide a large-scale data analytical framework that aims to understand the broad multiscale relationships between the complex information encoded in medical images (including computational, quantitative, and semantic image features) and their underlying clinical, therapeutic, and biological associations. As such it is a powerful and increasingly important tool for both clinicians and researchers involved in the imaging, evaluation, understanding, and management of lung cancers. Herein we provide an overview of the growing field of lung cancer radiogenomics and its applications.

摘要

放射组学提供了一个大规模数据分析框架,旨在理解医学图像中编码的复杂信息(包括计算、定量和语义图像特征)与其潜在的临床、治疗和生物学关联之间的广泛多尺度关系。因此,它是涉及肺癌成像、评估、理解和管理的临床医生和研究人员的强大且日益重要的工具。本文提供了肺癌放射组学及其应用的概述。

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Lung Cancer Radiogenomics: The Increasing Value of Imaging in Personalized Management of Lung Cancer Patients.肺癌放射基因组学:影像学在肺癌患者个体化管理中的价值不断提升。
J Thorac Imaging. 2018 Jan;33(1):17-25. doi: 10.1097/RTI.0000000000000312.
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[The application and progress of radiogenomics in lung cancer].[放射基因组学在肺癌中的应用与进展]
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Radiogenomics in personalized management of lung cancer patients: Where are we?放射组学在肺癌患者个体化管理中的应用:我们在哪里?
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Precision Medicine and Radiogenomics in Breast Cancer: New Approaches toward Diagnosis and Treatment.精准医学与乳腺癌放射组学:诊断与治疗的新方法。
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Radiomics and radiogenomics for precision radiotherapy.用于精确放疗的放射组学和放射基因组学。
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Radiogenomics: bridging imaging and genomics.放射组学:连接影像学与基因组学
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Radiomics and radiogenomics in lung cancer: A review for the clinician.肺癌的影像组学和放射组学:临床医生的综述。
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引用本文的文献

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Machine Learning and Deep Neural Networks in Thoracic and Cardiovascular Imaging.机器学习和深度学习在胸心血管成像中的应用。
J Thorac Imaging. 2019 May;34(3):192-201. doi: 10.1097/RTI.0000000000000385.
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Radiogenomics as association between non-invasive imaging features and molecular genomics of lung cancer.放射基因组学作为肺癌非侵入性影像特征与分子基因组学之间的关联。
Ann Transl Med. 2018 Dec;6(23):447. doi: 10.21037/atm.2018.11.17.