Authors: | Nougaret, S.; Tardieu, M.; Vargas, H. A.; Reinhold, C.; Vande Perre, S.; Bonanno, N.; Sala, E.; Thomassin-Naggara, I. |
Review Title: | Ovarian cancer: An update on imaging in the era of radiomics |
Abstract: | Tumor heterogeneity in ovarian cancer has been reported at the histological and genetic levels and is associated with adverse clinical outcomes. Tumor evaluation using standard computed tomography or magnetic resonance imaging techniques does not account for the intra- or inter-tumoral heterogeneity in advanced ovarian cancer with peritoneal carcinomatosis. As such, computational approaches in assessing tumor heterogeneity have been proposed using radiomics and radiogenomics in order to analyze the whole tumor heterogeneity as opposed to single biopsy sampling. As part of radiomics, texture analysis, which includes the extraction of multiple data from images has been proposed recently to evaluate advanced ovarian tumor heterogeneity. In this short review, we explain the basics of radiomics, how to perform texture analysis, and its applications to ovarian cancer imaging. © 2018 Société française de radiologie |
Keywords: | nuclear magnetic resonance imaging; cancer diagnosis; analysis; ovarian cancer; computer assisted tomography; ovary cancer; image analysis; diagnostic imaging; quantitative analysis; genomics; short survey; epidemiology; qualitative analysis; image segmentation; texture analysis; feature extraction; human; radiogenomics; radiomics; omics; advanced imaging |
Journal Title: | Diagnostic and Interventional Imaging |
Volume: | 100 |
Issue: | 10 |
ISSN: | 2211-5684 |
Publisher: | Elsevier Masson |
Date Published: | 2019-10-01 |
Start Page: | 647 |
End Page: | 655 |
Language: | English |
DOI: | 10.1016/j.diii.2018.11.007 |
PROVIDER: | scopus |
PUBMED: | 30555018 |
DOI/URL: | |
Notes: | Short Survey -- Export Date: 1 October 2019 -- Source: Scopus |