Radiogenomics Map: A Novel Approach for Noninvasive Identification of Molecular Properties?

医学 放射基因组学 梅德林 医学物理学 核医学 病理 肿瘤科 内科学 放射科 无线电技术 政治学 法学
作者
Sizhe Chen,Zhenyuan Ning,Xiaoshun He,Xiaolong Qi
出处
期刊:Radiology [Radiological Society of North America]
卷期号:285 (3): 1060-1061 被引量:2
标识
DOI:10.1148/radiol.2017171819
摘要

HomeRadiologyVol. 285, No. 3 PreviousNext CommunicationsLetters to the EditorRadiogenomics Map: A Novel Approach for Noninvasive Identification of Molecular Properties?Sizhe Chen*, Zhenyuan Ning*, Xiaoshun He†, Xiaolong Qi* Sizhe Chen*, Zhenyuan Ning*, Xiaoshun He†, Xiaolong Qi* Author AffiliationsDepartment of General Surgery, Nanfang Hospital, Southern Medical University, Guangdong Provincial Engineering Technology Research Center of Minimally Invasive Surgery, 1838 N Guanzhou Ave, Guangzhou 510515, China*Organ Transplant Center, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China†e-mail: [email protected]Sizhe Chen*Zhenyuan Ning*Xiaoshun He†Xiaolong Qi* Published Online:Nov 20 2017https://doi.org/10.1148/radiol.2017171819MoreSectionsFull textPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In References1. Zhou M, Leung A, Echegaray S, et al. Non–small cell lung cancer radiogenomics map identifies relationships between molecular and imaging phenotypes with prognostic implications. Radiology doi: 10.1148/radiol.2017161845. Published online July 20, 2017. Google Scholar2. Gillies RJ, Kinahan PE, Hricak H. Radiomics: images are more than pictures, they are data. Radiology 2016;278(2):563–577. Link, Google Scholar3. Aerts HJ, Velazquez ER, Leijenaar RT, et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun 2014;5:4006. Crossref, Medline, Google Scholar4. Banerjee S, Wang DS, Kim HJ, et al. A computed tomography radiogenomic biomarker predicts microvascular invasion and clinical outcomes in hepatocellular carcinoma. Hepatology 2015;62(3):792–800. Crossref, Medline, Google Scholar5. Kuo MD, Jamshidi N. Behind the numbers: decoding molecular phenotypes with radiogenomics—guiding principles and technical considerations. Radiology 2014;270(2):320–325. Link, Google Scholar6. Baker M. Statisticians issue warning over misuse of P values. Nature 2016;531(7593):151. Crossref, Medline, Google Scholar7. Segal E, Sirlin CB, Ooi C, et al. Decoding global gene expression programs in liver cancer by noninvasive imaging. Nat Biotechnol 2007;25(6):675–680. Crossref, Medline, Google Scholar8. Huang YQ, Liang CH, He L, et al. Development and validation of a radiomics nomogram for preoperative prediction of lymph node metastasis in colorectal cancer. J Clin Oncol 2016;34(18):2157–2164. Crossref, Medline, Google ScholarArticle HistoryPublished online: Nov 20 2017Published in print: Dec 2017 FiguresReferencesRelatedDetailsCited ByThe Era of Radiogenomics in Precision Medicine: An Emerging Approach to Support Diagnosis, Treatment Decisions, and Prognostication in OncologyLinShui, HaoyuRen, XiYang, JianLi, ZiweiChen, ChengYi, HongZhu, PixianShui2021 | Frontiers in Oncology, Vol. 10Prostate Cancer Radiogenomics—From Imaging to Molecular CharacterizationMatteoFerro, Ottaviode Cobelli, Mihai DorinVartolomei, GiuseppeLucarelli, FeliceCrocetto, BiagioBarone, AlessandroSciarra, FrancescoDel Giudice, MatteoMuto, MartinaMaggi, GiuseppeCarrieri, Gian MariaBusetto, UgoFalagario, DanielaTerracciano, LuigiCormio, GennaroMusi, Octavian SabinTataru2021 | International Journal of Molecular Sciences, Vol. 22, No. 18Recommended Articles Radiomics for Survival Risk Stratification of Clinical and Pathologic Stage IA Pure-Solid Non–Small Cell Lung CancerRadiology2021Volume: 302Issue: 2pp. 425-434Early-Stage Non–Small Cell Lung Cancer: Quantitative Imaging Characteristics of 18F Fluorodeoxyglucose PET/CT Allow Prediction of Distant MetastasisRadiology2016Volume: 281Issue: 1pp. 270-278Biliary Tract Cancer at CT: A Radiomics-based Model to Predict Lymph Node Metastasis and Survival OutcomesRadiology2018Volume: 290Issue: 1pp. 90-98Intratumoral Metabolic Heterogeneity and Other Quantitative 18F-FDG PET/CT Parameters for Prognosis Prediction in Esophageal CancerRadiology: Imaging Cancer2020Volume: 3Issue: 1Liquid Biopsy for Cancer: Review and Implications for the RadiologistRadiology2019Volume: 294Issue: 1pp. 5-17See More RSNA Education Exhibits Multifocal Lung Adenocarcinomas: Comprehensive Review and the Current Management StrategyDigital Posters2019Breast Cancer Metastasis or Not: That is the QuestionDigital Posters2019Role Of Radiology In Addressing The Challenge Of Lung Cancer After Lung Transplantation.Digital Posters2021 RSNA Case Collection Small cell lung carcinomaRSNA Case Collection2020LI-RADS 5RSNA Case Collection2022LI-RADS 5RSNA Case Collection2021 Vol. 285, No. 3 Metrics Altmetric Score PDF download
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