Literature DB >> 30555018

Ovarian cancer: An update on imaging in the era of radiomics.

S Nougaret1, M Tardieu2, H A Vargas3, C Reinhold4, S Vande Perre5, N Bonanno6, E Sala7, I Thomassin-Naggara5.   

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.
Copyright © 2018 Société française de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  Advanced imaging; Genomics; Ovarian cancer; Radiomics; Texture analysis

Mesh:

Year:  2018        PMID: 30555018     DOI: 10.1016/j.diii.2018.11.007

Source DB:  PubMed          Journal:  Diagn Interv Imaging        ISSN: 2211-5684            Impact factor:   4.026


  22 in total

1.  CT texture analysis in histological classification of epithelial ovarian carcinoma.

Authors:  He An; Yiang Wang; Esther M F Wong; Shanshan Lyu; Lujun Han; Jose A U Perucho; Peng Cao; Elaine Y P Lee
Journal:  Eur Radiol       Date:  2021-01-06       Impact factor: 5.315

Review 2.  CT and MRI of pancreatic tumors: an update in the era of radiomics.

Authors:  Marion Bartoli; Maxime Barat; Anthony Dohan; Sébastien Gaujoux; Romain Coriat; Christine Hoeffel; Christophe Cassinotto; Guillaume Chassagnon; Philippe Soyer
Journal:  Jpn J Radiol       Date:  2020-10-21       Impact factor: 2.374

Review 3.  Radiomics: from qualitative to quantitative imaging.

Authors:  William Rogers; Sithin Thulasi Seetha; Turkey A G Refaee; Relinde I Y Lieverse; Renée W Y Granzier; Abdalla Ibrahim; Simon A Keek; Sebastian Sanduleanu; Sergey P Primakov; Manon P L Beuque; Damiënne Marcus; Alexander M A van der Wiel; Fadila Zerka; Cary J G Oberije; Janita E van Timmeren; Henry C Woodruff; Philippe Lambin
Journal:  Br J Radiol       Date:  2020-02-26       Impact factor: 3.039

4.  Decoding incidental ovarian lesions: use of texture analysis and machine learning for characterization and detection of malignancy.

Authors:  Hyesun Park; Lei Qin; Pamela Guerra; Camden P Bay; Atul B Shinagare
Journal:  Abdom Radiol (NY)       Date:  2020-07-29

Review 5.  Radiomics: an Introductory Guide to What It May Foretell.

Authors:  Stephanie Nougaret; Hichem Tibermacine; Marion Tardieu; Evis Sala
Journal:  Curr Oncol Rep       Date:  2019-06-25       Impact factor: 5.075

Review 6.  Diagnostic performance of PET/CT and PET/MR in the management of ovarian carcinoma-a literature review.

Authors:  Mayur Virarkar; Dhakshinamoorthy Ganeshan; Anjalie Tara Gulati; Sarah Palmquist; Revathy Iyer; Priya Bhosale
Journal:  Abdom Radiol (NY)       Date:  2020-11-11

7.  Exploring MRI Characteristics of Brain Diffuse Midline Gliomas With the H3 K27M Mutation Using Radiomics.

Authors:  Qian Li; Fei Dong; Biao Jiang; Minming Zhang
Journal:  Front Oncol       Date:  2021-05-24       Impact factor: 6.244

8.  A radiomic nomogram based on arterial phase of CT for differential diagnosis of ovarian cancer.

Authors:  Yumin Hu; Qiaoyou Weng; Haihong Xia; Tao Chen; Chunli Kong; Weiyue Chen; Peipei Pang; Min Xu; Chenying Lu; Jiansong Ji
Journal:  Abdom Radiol (NY)       Date:  2021-06-04

Review 9.  Update on quantitative radiomics of pancreatic tumors.

Authors:  Mayur Virarkar; Vincenzo K Wong; Ajaykumar C Morani; Eric P Tamm; Priya Bhosale
Journal:  Abdom Radiol (NY)       Date:  2021-07-22

Review 10.  Implications of the new FIGO staging and the role of imaging in cervical cancer.

Authors:  Aki Kido; Yuji Nakamoto
Journal:  Br J Radiol       Date:  2021-05-14       Impact factor: 3.629

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