Tracking tumor biology with radiomics: A systematic review utilizing a radiomics quality score

Sebastian Sanduleanu*, Henry C. Woodruff, Evelyn E. C. de Jong, Janna E. van Timmeren, Arthur Jochems, Ludwig Dubois, Philippe Lambin

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

115 Citations (Web of Science)

Abstract

Introduction: In this review we describe recent developments in the field of radiomics along with current relevant literature linking it to tumor biology. We furthermore explore the methodologic quality of these studies with our in-house radiomics quality scoring (RQS) tool. Finally, we offer our vision on necessary future steps for the development of stable radiomic features and their links to tumor biology. Methods: Two authors (S.S. and H.W.) independently performed a thorough systematic literature search and outcome extraction to identify relevant studies published in MEDLINE/PubMed (National Center for Biotechnology Information, NCBI), EMBASE (Ovid) and Web of Science (WoS). Two authors (S.S, H.W) separately and two authors (J.v.T and E.d.J) concordantly scored the articles for their methodology and analyses according to the previously published radiomics quality score (RQS). Results: In summary, a total of 655 records were identified till 25-09-2017 based on the previously specified search terms, from which n = 236 in MEDLINE/PubMed, n = 215 in EMBASE and n = 204 from Web of Science. After determining full article availability and reading the available articles, a total of n = 41 studies were included in the systematic review. The RQS scoring resulted in some discrepancies between the reviewers, e.g. reviewer H.W scored 4 studies >= 50%, reviewer S.S scored 3 studies >= 50% while reviewers J.v.T and E.d.J scored 1 study >= 50%. Up to nine studies were given a quality score of 0%. The majority of studies were scored below 50%. Discussion: In this study, we performed a systematic literature search linking radiomics to tumor biology. All but two studies (n = 39) revealed that radiomic features derived from ultrasound, CT, PET and/or MR are significantly associated with one or several specific tumor biologic substrates, from somatic mutation status to tumor histopathologic grading and metabolism. Considerable inter-observer differences were found with regard to RQS scoring, while important questions were raised concerning the interpretability of the outcome of such scores. (C) 2018 The Author(s). Published by Elsevier B.V. Radiotherapy and Oncology 127 (2018) 349-360This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Original languageEnglish
Pages (from-to)349-360
Number of pages12
JournalRadiotherapy and Oncology
Volume127
Issue number3
DOIs
Publication statusPublished - 1 Jun 2018

Keywords

  • Radiomics
  • Neoplasms
  • Biology
  • CELL LUNG-CANCER
  • DECISION-SUPPORT-SYSTEMS
  • QUANTITATIVE IMAGE
  • SOMATIC MUTATIONS
  • PROSTATE-CANCER
  • CT IMAGES
  • FEATURES
  • HETEROGENEITY
  • MRI
  • ADENOCARCINOMA

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