Literature DB >> 29366600

Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application-Part 1: From Methodology to Clinical Implementation.

Faiq Shaikh1, Benjamin Franc2, Erastus Allen3, Evis Sala4, Omer Awan5, Kenneth Hendrata6, Safwan Halabi7, Sohaib Mohiuddin8, Sana Malik9, Dexter Hadley10, Rasu Shrestha3.   

Abstract

Enterprise imaging has channeled various technological innovations to the field of clinical radiology, ranging from advanced imaging equipment and postacquisition iterative reconstruction tools to image analysis and computer-aided detection tools. More recently, the advancements in the field of quantitative image analysis coupled with machine learning-based data analytics, classification, and integration have ushered us into the era of radiomics, which has tremendous potential in clinical decision support as well as drug discovery. There are important issues to consider to incorporate radiomics as a clinically applicable system and a commercially viable solution. In this two-part series, we offer insights into the development of the translational pipeline for radiomics from methodology to clinical implementation (Part 1) and from that to enterprise development (Part 2).
Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Radiomics; enterprise; medicine; precision; radiology; translational

Mesh:

Year:  2018        PMID: 29366600      PMCID: PMC7440362          DOI: 10.1016/j.jacr.2017.12.008

Source DB:  PubMed          Journal:  J Am Coll Radiol        ISSN: 1546-1440            Impact factor:   5.532


  6 in total

1.  Utilization of dashboard technology in academic radiology departments: results of a national survey.

Authors:  Bahar Mansoori; Ronald D Novak; Carlos J Sivit; Pablo R Ros
Journal:  J Am Coll Radiol       Date:  2013-04       Impact factor: 5.532

2.  From Information Management to Information Visualization: Development of Radiology Dashboards.

Authors:  Mahtab Karami; Reza Safdari
Journal:  Appl Clin Inform       Date:  2016-05-11       Impact factor: 2.342

3.  A novel representation of inter-site tumour heterogeneity from pre-treatment computed tomography textures classifies ovarian cancers by clinical outcome.

Authors:  Hebert Alberto Vargas; Harini Veeraraghavan; Maura Micco; Stephanie Nougaret; Yulia Lakhman; Andreas A Meier; Ramon Sosa; Robert A Soslow; Douglas A Levine; Britta Weigelt; Carol Aghajanian; Hedvig Hricak; Joseph Deasy; Alexandra Snyder; Evis Sala
Journal:  Eur Radiol       Date:  2017-03-13       Impact factor: 5.315

4.  Biomedical imaging ontologies: A survey and proposal for future work.

Authors:  Barry Smith; Sivaram Arabandi; Mathias Brochhausen; Michael Calhoun; Paolo Ciccarese; Scott Doyle; Bernard Gibaud; Ilya Goldberg; Charles E Kahn; James Overton; John Tomaszewski; Metin Gurcan
Journal:  J Pathol Inform       Date:  2015-06-23

Review 5.  The causes and consequences of genetic heterogeneity in cancer evolution.

Authors:  Rebecca A Burrell; Nicholas McGranahan; Jiri Bartek; Charles Swanton
Journal:  Nature       Date:  2013-09-19       Impact factor: 49.962

Review 6.  Intra-tumor heterogeneity of cancer cells and its implications for cancer treatment.

Authors:  Xiao-xiao Sun; Qiang Yu
Journal:  Acta Pharmacol Sin       Date:  2015-09-21       Impact factor: 6.150

  6 in total
  2 in total

1.  Radiomics and Machine Learning Differentiate Soft-Tissue Lipoma and Liposarcoma Better than Musculoskeletal Radiologists.

Authors:  Ieva Malinauskaite; Jeremy Hofmeister; Simon Burgermeister; Angeliki Neroladaki; Marion Hamard; Xavier Montet; Sana Boudabbous
Journal:  Sarcoma       Date:  2020-01-07

2.  Incorporating radiomics into clinical trials: expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to biologically driven quantitative biomarkers.

Authors:  Laure Fournier; Lena Costaridou; Luc Bidaut; Nicolas Michoux; Frederic E Lecouvet; Lioe-Fee de Geus-Oei; Ronald Boellaard; Daniela E Oprea-Lager; Nancy A Obuchowski; Anna Caroli; Wolfgang G Kunz; Edwin H Oei; James P B O'Connor; Marius E Mayerhoefer; Manuela Franca; Angel Alberich-Bayarri; Christophe M Deroose; Christian Loewe; Rashindra Manniesing; Caroline Caramella; Egesta Lopci; Nathalie Lassau; Anders Persson; Rik Achten; Karen Rosendahl; Olivier Clement; Elmar Kotter; Xavier Golay; Marion Smits; Marc Dewey; Daniel C Sullivan; Aad van der Lugt; Nandita M deSouza
Journal:  Eur Radiol       Date:  2021-01-25       Impact factor: 5.315

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.