Literature DB >> 26864054

Imaging genomics in cancer research: limitations and promises.

Harrison X Bai1, Ashley M Lee1, Li Yang2, Paul Zhang3, Christos Davatzikos1, John M Maris4,5,6, Sharon J Diskin4,5,6.   

Abstract

Recently, radiogenomics or imaging genomics has emerged as a novel high-throughput method of associating imaging features with genomic data. Radiogenomics has the potential to provide comprehensive intratumour, intertumour and peritumour information non-invasively. This review article summarizes the current state of radiogenomic research in tumour characterization, discusses some of its limitations and promises and projects its future directions. Semi-radiogenomic studies that relate specific gene expressions to imaging features will also be briefly reviewed.

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Year:  2016        PMID： 26864054      PMCID： PMC4985482          DOI： 10.1259/bjr.20151030

Source DB:  PubMed          Journal:  Br J Radiol        ISSN： 0007-1285            Impact factor:   3.039


  102 in total

Review 1.  Imaging genetics--days of future past.

Authors:  Kristin L Bigos; Daniel R Weinberger
Journal:  Neuroimage       Date:  2010-01-18       Impact factor: 6.556

2.  Interim positron emission tomography scan associated with international prognostic index and germinal center B cell-like signature as prognostic index in diffuse large B-cell lymphoma.

Authors:  Hélène Lanic; Sylvain Mareschal; Férial Mechken; Jean-Michel Picquenot; Marie Cornic; Catherine Maingonnat; Philippe Bertrand; Florian Clatot; Elodie Bohers; Aspasia Stamatoullas; Stéphane Leprêtre; Vinciane Rainville; Philippe Ruminy; Christian Bastard; Hervé Tilly; Stéphanie Becker; Pierre Vera; Fabrice Jardin
Journal:  Leuk Lymphoma       Date:  2011-08-01

3.  A generative approach for image-based modeling of tumor growth.

Authors:  Bjoern H Menze; Koen Van Leemput; Antti Honkela; Ender Konukoglu; Marc-André Weber; Nicholas Ayache; Polina Golland
Journal:  Inf Process Med Imaging       Date:  2011

4.  Hepatocellular carcinoma: signal intensity at gadoxetic acid-enhanced MR Imaging--correlation with molecular transporters and histopathologic features.

Authors:  Azusa Kitao; Yoh Zen; Osamu Matsui; Toshifumi Gabata; Satoshi Kobayashi; Wataru Koda; Kazuto Kozaka; Norihide Yoneda; Tatsuya Yamashita; Shuichi Kaneko; Yasuni Nakanuma
Journal:  Radiology       Date:  2010-07-27       Impact factor: 11.105

5.  Radiogenomics: what it is and why it is important.

Authors:  Maciej A Mazurowski
Journal:  J Am Coll Radiol       Date:  2015-08       Impact factor: 5.532

6.  Identification of noninvasive imaging surrogates for brain tumor gene-expression modules.

Authors:  Maximilian Diehn; Christine Nardini; David S Wang; Susan McGovern; Mahesh Jayaraman; Yu Liang; Kenneth Aldape; Soonmee Cha; Michael D Kuo
Journal:  Proc Natl Acad Sci U S A       Date:  2008-03-24       Impact factor: 11.205

7.  MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set.

Authors:  David A Gutman; Lee A D Cooper; Scott N Hwang; Chad A Holder; Jingjing Gao; Tarun D Aurora; William D Dunn; Lisa Scarpace; Tom Mikkelsen; Rajan Jain; Max Wintermark; Manal Jilwan; Prashant Raghavan; Erich Huang; Robert J Clifford; Pattanasak Mongkolwat; Vladimir Kleper; John Freymann; Justin Kirby; Pascal O Zinn; Carlos S Moreno; Carl Jaffe; Rivka Colen; Daniel L Rubin; Joel Saltz; Adam Flanders; Daniel J Brat
Journal:  Radiology       Date:  2013-02-07       Impact factor: 11.105

8.  Pretreatment Dynamic Susceptibility Contrast MRI Perfusion in Glioblastoma: Prediction of EGFR Gene Amplification.

Authors:  A Gupta; R J Young; A D Shah; A D Schweitzer; J J Graber; W Shi; Z Zhang; J Huse; A M P Omuro
Journal:  Clin Neuroradiol       Date:  2014-01-29       Impact factor: 3.649

9.  Prediction of methylguanine methyltransferase promoter methylation in glioblastoma using dynamic contrast-enhanced magnetic resonance and diffusion tensor imaging.

Authors:  Sung Soo Ahn; Na-Young Shin; Jong Hee Chang; Se Hoon Kim; Eui Hyun Kim; Dong Wook Kim; Seung-Koo Lee
Journal:  J Neurosurg       Date:  2014-06-20       Impact factor: 5.115

10.  Radiogenomic mapping of edema/cellular invasion MRI-phenotypes in glioblastoma multiforme.

Authors:  Pascal O Zinn; Bhanu Mahajan; Bhanu Majadan; Pratheesh Sathyan; Sanjay K Singh; Sadhan Majumder; Ferenc A Jolesz; Rivka R Colen
Journal:  PLoS One       Date:  2011-10-05       Impact factor: 3.240
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  37 in total

1.  Artificial intelligence, machine (deep) learning and radio(geno)mics: definitions and nuclear medicine imaging applications.

Authors:  Dimitris Visvikis; Catherine Cheze Le Rest; Vincent Jaouen; Mathieu Hatt
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-07-06       Impact factor: 9.236

Review 2.  Advanced MRI Techniques in the Monitoring of Treatment of Gliomas.

Authors:  Harpreet Hyare; Steffi Thust; Jeremy Rees
Journal:  Curr Treat Options Neurol       Date:  2017-03       Impact factor: 3.598

3.  MRI features can predict EGFR expression in lower grade gliomas: A voxel-based radiomic analysis.

Authors:  Yiming Li; Xing Liu; Kaibin Xu; Zenghui Qian; Kai Wang; Xing Fan; Shaowu Li; Yinyan Wang; Tao Jiang
Journal:  Eur Radiol       Date:  2017-07-28       Impact factor: 5.315

Review 4.  Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging.

Authors:  E Sala; E Mema; Y Himoto; H Veeraraghavan; J D Brenton; A Snyder; B Weigelt; H A Vargas
Journal:  Clin Radiol       Date:  2016-10-11       Impact factor: 2.350

Review 5.  The Continuing Evolution of Molecular Functional Imaging in Clinical Oncology: The Road to Precision Medicine and Radiogenomics (Part I).

Authors:  Tanvi Vaidya; Archi Agrawal; Shivani Mahajan; Meenakshi H Thakur; Abhishek Mahajan
Journal:  Mol Diagn Ther       Date:  2019-02       Impact factor: 4.074

6.  MRI features predict survival and molecular markers in diffuse lower-grade gliomas.

Authors:  Hao Zhou; Martin Vallières; Harrison X Bai; Chang Su; Haiyun Tang; Derek Oldridge; Zishu Zhang; Bo Xiao; Weihua Liao; Yongguang Tao; Jianhua Zhou; Paul Zhang; Li Yang
Journal:  Neuro Oncol       Date:  2017-06-01       Impact factor: 12.300

Review 7.  Background, current role, and potential applications of radiogenomics.

Authors:  Katja Pinker; Fuki Shitano; Evis Sala; Richard K Do; Robert J Young; Andreas G Wibmer; Hedvig Hricak; Elizabeth J Sutton; Elizabeth A Morris
Journal:  J Magn Reson Imaging       Date:  2017-11-02       Impact factor: 4.813

8.  Correlations between metabolic texture features, genetic heterogeneity, and mutation burden in patients with lung cancer.

Authors:  Seung Hwan Moon; Jinho Kim; Je-Gun Joung; Hongui Cha; Woong-Yang Park; Jin Seok Ahn; Myung-Ju Ahn; Keunchil Park; Joon Young Choi; Kyung-Han Lee; Byung-Tae Kim; Se-Hoon Lee
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-08-25       Impact factor: 9.236

9.  Radiomic features predict Ki-67 expression level and survival in lower grade gliomas.

Authors:  Yiming Li; Zenghui Qian; Kaibin Xu; Kai Wang; Xing Fan; Shaowu Li; Xing Liu; Yinyan Wang; Tao Jiang
Journal:  J Neurooncol       Date:  2017-09-12       Impact factor: 4.130

Review 10.  Background, applications and challenges of radiogenomics in genitourinary tumor.

Authors:  Longfei Liu; Xiaoping Yi; Can Lu; Yingxian Pang; Xiongbing Zu; Minfeng Chen; Xiao Guan
Journal:  Am J Cancer Res       Date:  2021-05-15       Impact factor: 6.166
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