Literature DB >> 28423406

The Rise of Radiomics and Implications for Oncologic Management.

Vivek Verma1, Charles B Simone2, Sunil Krishnan3, Steven H Lin3, Jinzhong Yang3, Stephen M Hahn3.   

Abstract

Clinical medicine, particularly oncology, is progressing toward personalized care. Whereas the terms genomics, proteomics, transcriptomics, and metabolomics have dominated personalized medicine for the past couple decades, the concept of radiomics was first described in 2012. This nascent concept has major implications for personalized cancer care and involves extracting hundreds of standardized and quantifiable imaging characteristics from diagnostic computed tomography/magnetic resonance imaging images. The central hypothesis of radiomics is that these libraries of quantitative individual voxel-based variables are more sensitively associated with various clinical endpoints compared with the more qualitative radiologic, histopathologic, and clinical data more commonly utilized today. Because radiomics offers immense potential but has not reached a mainstream oncologic audience, the authors discuss herein the role of radiomics in cancer care in the future.
© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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Year:  2017        PMID: 28423406     DOI: 10.1093/jnci/djx055

Source DB:  PubMed          Journal:  J Natl Cancer Inst        ISSN: 0027-8874            Impact factor:   13.506


  44 in total

1.  Prognostic value of computed tomography radiomics features in patients with gastric cancer following curative resection.

Authors:  Wuchao Li; Liwen Zhang; Chong Tian; Hui Song; Mengjie Fang; Chaoen Hu; Yali Zang; Ying Cao; Shiyuan Dai; Fang Wang; Di Dong; Rongpin Wang; Jie Tian
Journal:  Eur Radiol       Date:  2018-12-05       Impact factor: 5.315

2.  Metabolomics technology and bioinformatics for precision medicine.

Authors:  Rajeev K Azad; Vladimir Shulaev
Journal:  Brief Bioinform       Date:  2019-11-27       Impact factor: 11.622

3.  Radiomics in peritumoral non-enhancing regions: fractional anisotropy and cerebral blood volume improve prediction of local progression and overall survival in patients with glioblastoma.

Authors:  Jung Youn Kim; Min Jae Yoon; Ji Eun Park; Eun Jung Choi; Jongho Lee; Ho Sung Kim
Journal:  Neuroradiology       Date:  2019-07-09       Impact factor: 2.804

4.  MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma.

Authors:  Lina Zhao; Jie Gong; Yibin Xi; Man Xu; Chen Li; Xiaowei Kang; Yutian Yin; Wei Qin; Hong Yin; Mei Shi
Journal:  Eur Radiol       Date:  2019-08-01       Impact factor: 5.315

5.  Radiomics nomogram for predicting the malignant potential of gastrointestinal stromal tumours preoperatively.

Authors:  Tao Chen; Zhenyuan Ning; Lili Xu; Xingyu Feng; Shuai Han; Holger R Roth; Wei Xiong; Xixi Zhao; Yanfeng Hu; Hao Liu; Jiang Yu; Yu Zhang; Yong Li; Yikai Xu; Kensaku Mori; Guoxin Li
Journal:  Eur Radiol       Date:  2018-08-16       Impact factor: 5.315

6.  Multiparametric MRI-based radiomics analysis for prediction of breast cancers insensitive to neoadjuvant chemotherapy.

Authors:  Qianqian Xiong; Xuezhi Zhou; Zhenyu Liu; Chuqian Lei; Ciqiu Yang; Mei Yang; Liulu Zhang; Teng Zhu; Xiaosheng Zhuang; Changhong Liang; Zaiyi Liu; Jie Tian; Kun Wang
Journal:  Clin Transl Oncol       Date:  2019-04-11       Impact factor: 3.405

7.  The predictive value of CT-based radiomics in differentiating indolent from invasive lung adenocarcinoma in patients with pulmonary nodules.

Authors:  Yunlang She; Lei Zhang; Huiyuan Zhu; Chenyang Dai; Dong Xie; Huikang Xie; Wei Zhang; Lilan Zhao; Liling Zou; Ke Fei; Xiwen Sun; Chang Chen
Journal:  Eur Radiol       Date:  2018-06-04       Impact factor: 5.315

8.  Imaging phenotype using radiomics to predict dry pleural dissemination in non-small cell lung cancer.

Authors:  Minglei Yang; Yijiu Ren; Yunlang She; Dong Xie; Xiwen Sun; Jingyun Shi; Guofang Zhao; Chang Chen
Journal:  Ann Transl Med       Date:  2019-06

9.  Preoperative Prediction of Pathologic Response to Neoadjuvant Chemoradiotherapy in Patients With Esophageal Cancer Using 18F-FDG PET/CT and DW-MRI: A Prospective Multicenter Study.

Authors:  Alicia S Borggreve; Lucas Goense; Peter S N van Rossum; Sophie E Heethuis; Richard van Hillegersberg; Jan J W Lagendijk; Marnix G E H Lam; Astrid L H M W van Lier; Stella Mook; Jelle P Ruurda; Marco van Vulpen; Francine E M Voncken; Berthe M P Aleman; Annemarieke Bartels-Rutten; Jingfei Ma; Penny Fang; Benjamin C Musall; Steven H Lin; Gert J Meijer
Journal:  Int J Radiat Oncol Biol Phys       Date:  2020-01-25       Impact factor: 7.038

10.  Quantitative assessment of acquisition imaging parameters on MRI radiomics features: a prospective anthropomorphic phantom study using a 3D-T2W-TSE sequence for MR-guided-radiotherapy.

Authors:  Jing Yuan; Cindy Xue; Gladys Lo; Oi Lei Wong; Yihang Zhou; Siu Ki Yu; Kin Yin Cheung
Journal:  Quant Imaging Med Surg       Date:  2021-05
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