Literature DB >> 22257792

Radiomics: extracting more information from medical images using advanced feature analysis.

Philippe Lambin1, Emmanuel Rios-Velazquez, Ralph Leijenaar, Sara Carvalho, Ruud G P M van Stiphout, Patrick Granton, Catharina M L Zegers, Robert Gillies, Ronald Boellard, André Dekker, Hugo J W L Aerts.   

Abstract

Solid cancers are spatially and temporally heterogeneous. This limits the use of invasive biopsy based molecular assays but gives huge potential for medical imaging, which has the ability to capture intra-tumoural heterogeneity in a non-invasive way. During the past decades, medical imaging innovations with new hardware, new imaging agents and standardised protocols, allows the field to move towards quantitative imaging. Therefore, also the development of automated and reproducible analysis methodologies to extract more information from image-based features is a requirement. Radiomics--the high-throughput extraction of large amounts of image features from radiographic images--addresses this problem and is one of the approaches that hold great promises but need further validation in multi-centric settings and in the laboratory. Copyright Â
© 2011 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 22257792      PMCID: PMC4533986          DOI: 10.1016/j.ejca.2011.11.036

Source DB:  PubMed          Journal:  Eur J Cancer        ISSN: 0959-8049            Impact factor:   9.162


  21 in total

1.  The patterns and dynamics of genomic instability in metastatic pancreatic cancer.

Authors:  Peter J Campbell; Shinichi Yachida; Laura J Mudie; Philip J Stephens; Erin D Pleasance; Lucy A Stebbings; Laura A Morsberger; Calli Latimer; Stuart McLaren; Meng-Lay Lin; David J McBride; Ignacio Varela; Serena A Nik-Zainal; Catherine Leroy; Mingming Jia; Andrew Menzies; Adam P Butler; Jon W Teague; Constance A Griffin; John Burton; Harold Swerdlow; Michael A Quail; Michael R Stratton; Christine Iacobuzio-Donahue; P Andrew Futreal
Journal:  Nature       Date:  2010-10-28       Impact factor: 49.962

2.  Development and validation of a prognostic model using blood biomarker information for prediction of survival of non-small-cell lung cancer patients treated with combined chemotherapy and radiation or radiotherapy alone (NCT00181519, NCT00573040, and NCT00572325).

Authors:  Cary Dehing-Oberije; Hugo Aerts; Shipeng Yu; Dirk De Ruysscher; Paul Menheere; Mika Hilvo; Hiska van der Weide; Bharat Rao; Philippe Lambin
Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-10-01       Impact factor: 7.038

3.  Intratumor heterogeneity characterized by textural features on baseline 18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer.

Authors:  Florent Tixier; Catherine Cheze Le Rest; Mathieu Hatt; Nidal Albarghach; Olivier Pradier; Jean-Philippe Metges; Laurent Corcos; Dimitris Visvikis
Journal:  J Nucl Med       Date:  2011-02-14       Impact factor: 10.057

4.  Evaluation of computer-aided diagnosis on a large clinical full-field digital mammographic dataset.

Authors:  Hui Li; Maryellen L Giger; Yading Yuan; Weijie Chen; Karla Horsch; Li Lan; Andrew R Jamieson; Charlene A Sennett; Sanaz A Jansen
Journal:  Acad Radiol       Date:  2008-11       Impact factor: 3.173

5.  Disparity between in vivo EGFR expression and 89Zr-labeled cetuximab uptake assessed with PET.

Authors:  Hugo J W L Aerts; Ludwig Dubois; Lars Perk; Peter Vermaelen; Guus A M S van Dongen; Bradly G Wouters; Philippe Lambin
Journal:  J Nucl Med       Date:  2008-12-17       Impact factor: 10.057

6.  Magnetic resonance image-guided proteomics of human glioblastoma multiforme.

Authors:  Susan K Hobbs; Gongyi Shi; Ron Homer; Griff Harsh; Scott W Atlas; Mark D Bednarski
Journal:  J Magn Reson Imaging       Date:  2003-11       Impact factor: 4.813

7.  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

8.  The maximum uptake of (18)F-deoxyglucose on positron emission tomography scan correlates with survival, hypoxia inducible factor-1alpha and GLUT-1 in non-small cell lung cancer.

Authors:  Angela van Baardwijk; Christophe Dooms; Robert Jan van Suylen; Erik Verbeken; Monique Hochstenbag; Cary Dehing-Oberije; Dennis Rupa; Silvia Pastorekova; Sigrid Stroobants; Ulrich Buell; Philippe Lambin; Johan Vansteenkiste; Dirk De Ruysscher
Journal:  Eur J Cancer       Date:  2007-05-23       Impact factor: 9.162

9.  Radiogenomic analysis to identify imaging phenotypes associated with drug response gene expression programs in hepatocellular carcinoma.

Authors:  Michael D Kuo; Jeremy Gollub; Claude B Sirlin; Clara Ooi; Xin Chen
Journal:  J Vasc Interv Radiol       Date:  2007-07       Impact factor: 3.464

Review 10.  Imaging tumor vascular heterogeneity and angiogenesis using dynamic contrast-enhanced magnetic resonance imaging.

Authors:  Alan Jackson; James P B O'Connor; Geoff J M Parker; Gordon C Jayson
Journal:  Clin Cancer Res       Date:  2007-06-15       Impact factor: 12.531

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  1242 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

Review 2.  Radiomics in precision medicine for lung cancer.

Authors:  Julie Constanzo; Lise Wei; Huan-Hsin Tseng; Issam El Naqa
Journal:  Transl Lung Cancer Res       Date:  2017-12

Review 3.  Imaging of Solid Renal Masses.

Authors:  Fernando U Kay; Ivan Pedrosa
Journal:  Urol Clin North Am       Date:  2018-06-15       Impact factor: 2.241

Review 4.  An Update on the Approach to the Imaging of Brain Tumors.

Authors:  Katherine M Mullen; Raymond Y Huang
Journal:  Curr Neurol Neurosci Rep       Date:  2017-07       Impact factor: 5.081

5.  High quality machine-robust image features: identification in nonsmall cell lung cancer computed tomography images.

Authors:  Luke A Hunter; Shane Krafft; Francesco Stingo; Haesun Choi; Mary K Martel; Stephen F Kry; Laurence E Court
Journal:  Med Phys       Date:  2013-12       Impact factor: 4.071

Review 6.  Anatomic, functional and molecular imaging in lung cancer precision radiation therapy: treatment response assessment and radiation therapy personalization.

Authors:  Michael MacManus; Sarah Everitt; Tanja Schimek-Jasch; X Allen Li; Ursula Nestle; Feng-Ming Spring Kong
Journal:  Transl Lung Cancer Res       Date:  2017-12

7.  Machine learning to improve breast cancer diagnosis by multimodal ultrasound.

Authors:  Laith R Sultan; Susan M Schultz; Theodore W Cary; Chandra M Sehgal
Journal:  IEEE Int Ultrason Symp       Date:  2018-12-20

Review 8.  Review of quantitative multiscale imaging of breast cancer.

Authors:  Michael A Pinkert; Lonie R Salkowski; Patricia J Keely; Timothy J Hall; Walter F Block; Kevin W Eliceiri
Journal:  J Med Imaging (Bellingham)       Date:  2018-01-22

9.  Hybrid models for lung nodule malignancy prediction utilizing convolutional neural network ensembles and clinical data.

Authors:  Rahul Paul; Matthew B Schabath; Robert Gillies; Lawrence O Hall; Dmitry B Goldgof
Journal:  J Med Imaging (Bellingham)       Date:  2020-04-06

10.  Exploring Variability in CT Characterization of Tumors: A Preliminary Phantom Study.

Authors:  Binsheng Zhao; Yongqiang Tan; Wei Yann Tsai; Lawrence H Schwartz; Lin Lu
Journal:  Transl Oncol       Date:  2014-02-01       Impact factor: 4.243

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