Literature DB >> 29175982

Responsible Radiomics Research for Faster Clinical Translation.

Martin Vallières1, Alex Zwanenburg2,3, Bodgan Badic1, Catherine Cheze Le Rest1, Dimitris Visvikis1, Mathieu Hatt4.   

Abstract

Mesh：

Year:  2017        PMID： 29175982      PMCID： PMC5807530          DOI： 10.2967/jnumed.117.200501

Source DB:  PubMed          Journal:  J Nucl Med        ISSN： 0161-5505            Impact factor:   10.057


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  21 in total

1.  Effects of MRI acquisition parameter variations and protocol heterogeneity on the results of texture analysis and pattern discrimination: an application-oriented study.

Authors:  Marius E Mayerhoefer; Pavol Szomolanyi; Daniel Jirak; Andrzej Materka; Siegfried Trattnig
Journal:  Med Phys       Date:  2009-04       Impact factor: 4.071

Review 2.  Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM.

Authors:  Maryellen L Giger; Heang-Ping Chan; John Boone
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

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

Review 4.  Radiomics: extracting more information from medical images using advanced feature analysis.

Authors:  Philippe Lambin; 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
Journal:  Eur J Cancer       Date:  2012-01-16       Impact factor: 9.162

5.  Predicting the Future - Big Data, Machine Learning, and Clinical Medicine.

Authors:  Ziad Obermeyer; Ezekiel J Emanuel
Journal:  N Engl J Med       Date:  2016-09-29       Impact factor: 91.245

Review 6.  Applications and limitations of radiomics.

Authors:  Stephen S F Yip; Hugo J W L Aerts
Journal:  Phys Med Biol       Date:  2016-06-08       Impact factor: 3.609

Review 7.  PET Radiomics in NSCLC: state of the art and a proposal for harmonization of methodology.

Authors:  M Sollini; L Cozzi; L Antunovic; A Chiti; M Kirienko
Journal:  Sci Rep       Date:  2017-03-23       Impact factor: 4.379

8.  The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis.

Authors:  Ralph T H Leijenaar; Georgi Nalbantov; Sara Carvalho; Wouter J C van Elmpt; Esther G C Troost; Ronald Boellaard; Hugo J W L Aerts; Robert J Gillies; Philippe Lambin
Journal:  Sci Rep       Date:  2015-08-05       Impact factor: 4.379

9.  The FAIR Guiding Principles for scientific data management and stewardship.

Authors:  Mark D Wilkinson; Michel Dumontier; I Jsbrand Jan Aalbersberg; Gabrielle Appleton; Myles Axton; Arie Baak; Niklas Blomberg; Jan-Willem Boiten; Luiz Bonino da Silva Santos; Philip E Bourne; Jildau Bouwman; Anthony J Brookes; Tim Clark; Mercè Crosas; Ingrid Dillo; Olivier Dumon; Scott Edmunds; Chris T Evelo; Richard Finkers; Alejandra Gonzalez-Beltran; Alasdair J G Gray; Paul Groth; Carole Goble; Jeffrey S Grethe; Jaap Heringa; Peter A C 't Hoen; Rob Hooft; Tobias Kuhn; Ruben Kok; Joost Kok; Scott J Lusher; Maryann E Martone; Albert Mons; Abel L Packer; Bengt Persson; Philippe Rocca-Serra; Marco Roos; Rene van Schaik; Susanna-Assunta Sansone; Erik Schultes; Thierry Sengstag; Ted Slater; George Strawn; Morris A Swertz; Mark Thompson; Johan van der Lei; Erik van Mulligen; Jan Velterop; Andra Waagmeester; Peter Wittenburg; Katherine Wolstencroft; Jun Zhao; Barend Mons
Journal:  Sci Data       Date:  2016-03-15       Impact factor: 6.444

10.  Radiomics: Images Are More than Pictures, They Are Data.

Authors:  Robert J Gillies; Paul E Kinahan; Hedvig Hricak
Journal:  Radiology       Date:  2015-11-18       Impact factor: 11.105
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  65 in total

1.  Tumor Subregion Evolution-Based Imaging Features to Assess Early Response and Predict Prognosis in Oropharyngeal Cancer.

Authors:  Jia Wu; Michael F Gensheimer; Nasha Zhang; Meiying Guo; Rachel Liang; Carrie Zhang; Nancy Fischbein; Erqi L Pollom; Beth Beadle; Quynh-Thu Le; Ruijiang Li
Journal:  J Nucl Med       Date:  2019-08-16       Impact factor: 10.057

2.  External validation of a combined PET and MRI radiomics model for prediction of recurrence in cervical cancer patients treated with chemoradiotherapy.

Authors:  François Lucia; Dimitris Visvikis; Martin Vallières; Marie-Charlotte Desseroit; Omar Miranda; Philippe Robin; Pietro Andrea Bonaffini; Joanne Alfieri; Ingrid Masson; Augustin Mervoyer; Caroline Reinhold; Olivier Pradier; Mathieu Hatt; Ulrike Schick
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-12-07       Impact factor: 9.236

3.  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

4.  Radiomics in nuclear medicine: robustness, reproducibility, standardization, and how to avoid data analysis traps and replication crisis.

Authors:  Alex Zwanenburg
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-06-25       Impact factor: 9.236

5.  Integrating Tumor and Nodal Imaging Characteristics at Baseline and Mid-Treatment Computed Tomography Scans to Predict Distant Metastasis in Oropharyngeal Cancer Treated With Concurrent Chemoradiotherapy.

Authors:  Jia Wu; Micheal F Gensheimer; Nasha Zhang; Fei Han; Rachel Liang; Yushen Qian; Carrie Zhang; Nancy Fischbein; Erqi L Pollom; Beth Beadle; Quynh-Thu Le; Ruijiang Li
Journal:  Int J Radiat Oncol Biol Phys       Date:  2019-03-30       Impact factor: 7.038

6.  Prediction of KRAS, NRAS and BRAF status in colorectal cancer patients with liver metastasis using a deep artificial neural network based on radiomics and semantic features.

Authors:  Ruichuan Shi; Weixing Chen; Bowen Yang; Jinglei Qu; Yu Cheng; Zhitu Zhu; Yu Gao; Qian Wang; Yunpeng Liu; Zhi Li; Xiujuan Qu
Journal:  Am J Cancer Res       Date:  2020-12-01       Impact factor: 6.166

7.  The Evolving Status of Radiomics.

Authors:  Philip O Alderson; Ronald M Summers
Journal:  J Natl Cancer Inst       Date:  2020-09-01       Impact factor: 13.506

8.  Unsupervised machine learning of radiomic features for predicting treatment response and overall survival of early stage non-small cell lung cancer patients treated with stereotactic body radiation therapy.

Authors:  Hongming Li; Maya Galperin-Aizenberg; Daniel Pryma; Charles B Simone; Yong Fan
Journal:  Radiother Oncol       Date:  2018-07-04       Impact factor: 6.280

9.  Endometrial Carcinoma: Texture Analysis of Apparent Diffusion Coefficient Maps and Its Correlation with Histopathologic Findings and Prognosis.

Authors:  Ichiro Yamada; Naoyuki Miyasaka; Daisuke Kobayashi; Kimio Wakana; Noriko Oshima; Akira Wakabayashi; Junichiro Sakamoto; Yukihisa Saida; Ukihide Tateishi; Yoshinobu Eishi
Journal:  Radiol Imaging Cancer       Date:  2019-11-29

10.  Texture Analysis of Apparent Diffusion Coefficient Maps in Cervical Carcinoma: Correlation with Histopathologic Findings and Prognosis.

Authors:  Ichiro Yamada; Noriko Oshima; Naoyuki Miyasaka; Kimio Wakana; Akira Wakabayashi; Junichiro Sakamoto; Yukihisa Saida; Ukihide Tateishi; Daisuke Kobayashi
Journal:  Radiol Imaging Cancer       Date:  2020-05-22
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