| Literature DB >> 28975929 |
Philippe Lambin1, Ralph T H Leijenaar1, Timo M Deist1, Jurgen Peerlings1,2, Evelyn E C de Jong1, Janita van Timmeren1, Sebastian Sanduleanu1, Ruben T H M Larue1, Aniek J G Even1, Arthur Jochems1, Yvonka van Wijk1, Henry Woodruff1, Johan van Soest3, Tim Lustberg3, Erik Roelofs1,3, Wouter van Elmpt3, Andre Dekker3, Felix M Mottaghy2,4, Joachim E Wildberger2, Sean Walsh1.
Abstract
Radiomics, the high-throughput mining of quantitative image features from standard-of-care medical imaging that enables data to be extracted and applied within clinical-decision support systems to improve diagnostic, prognostic, and predictive accuracy, is gaining importance in cancer research. Radiomic analysis exploits sophisticated image analysis tools and the rapid development and validation of medical imaging data that uses image-based signatures for precision diagnosis and treatment, providing a powerful tool in modern medicine. Herein, we describe the process of radiomics, its pitfalls, challenges, opportunities, and its capacity to improve clinical decision making, emphasizing the utility for patients with cancer. Currently, the field of radiomics lacks standardized evaluation of both the scientific integrity and the clinical relevance of the numerous published radiomics investigations resulting from the rapid growth of this area. Rigorous evaluation criteria and reporting guidelines need to be established in order for radiomics to mature as a discipline. Herein, we provide guidance for investigations to meet this urgent need in the field of radiomics.Entities:
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Year: 2017 PMID: 28975929 DOI: 10.1038/nrclinonc.2017.141
Source DB: PubMed Journal: Nat Rev Clin Oncol ISSN: 1759-4774 Impact factor: 66.675