Literature DB >> 33882246

Radiomics in radiation oncology for gynecological malignancies: a review of literature.

Morgan Michalet1,2, David Azria1,2, Marion Tardieu2, Hichem Tibermacine2, Stéphanie Nougaret2.   

Abstract

Radiomics is the extraction of a significant number of quantitative imaging features with the aim of detecting information in correlation with useful clinical outcomes. Features are extracted, after delineation of an area of interest, from a single or a combined set of imaging modalities (including X-ray, US, CT, PET/CT and MRI). Given the high dimensionality, the analytical process requires the use of artificial intelligence algorithms. Firstly developed for diagnostic performance in radiology, it has now been translated to radiation oncology mainly to predict tumor response and patient outcome but other applications have been developed such as dose painting, prediction of side-effects, and quality assurance. In gynecological cancers, most studies have focused on outcomes of cervical cancers after chemoradiation. This review highlights the role of this new tool for the radiation oncologists with particular focus on female GU oncology.

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Year:  2021        PMID: 33882246      PMCID: PMC9327766          DOI: 10.1259/bjr.20210032

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.629


  76 in total

1.  18F-FDG PET image biomarkers improve prediction of late radiation-induced xerostomia.

Authors:  Lisanne V van Dijk; Walter Noordzij; Charlotte L Brouwer; Ronald Boellaard; Johannes G M Burgerhof; Johannes A Langendijk; Nanna M Sijtsema; Roel J H M Steenbakkers
Journal:  Radiother Oncol       Date:  2017-09-23       Impact factor: 6.280

Review 2.  Role of Imaging in the Era of Precision Medicine.

Authors:  Angela Giardino; Supriya Gupta; Emmi Olson; Karla Sepulveda; Leon Lenchik; Jana Ivanidze; Rebecca Rakow-Penner; Midhir J Patel; Rathan M Subramaniam; Dhakshinamoorthy Ganeshan
Journal:  Acad Radiol       Date:  2017-01-25       Impact factor: 3.173

3.  Assessing the performance of prediction models: a framework for traditional and novel measures.

Authors:  Ewout W Steyerberg; Andrew J Vickers; Nancy R Cook; Thomas Gerds; Mithat Gonen; Nancy Obuchowski; Michael J Pencina; Michael W Kattan
Journal:  Epidemiology       Date:  2010-01       Impact factor: 4.822

4.  Carbon ion radiotherapy decreases the impact of tumor heterogeneity on radiation response in experimental prostate tumors.

Authors:  Christin Glowa; Christian P Karger; Stephan Brons; Dawen Zhao; Ralph P Mason; Peter E Huber; Jürgen Debus; Peter Peschke
Journal:  Cancer Lett       Date:  2016-05-17       Impact factor: 8.679

5.  Feasibility of an ADC-based radiomics model for predicting pelvic lymph node metastases in patients with stage IB-IIA cervical squamous cell carcinoma.

Authors:  Yan Yan Yu; Rui Zhang; Rui Tong Dong; Qi Yun Hu; Tao Yu; Fan Liu; Ya Hong Luo; Yue Dong
Journal:  Br J Radiol       Date:  2019-04-01       Impact factor: 3.039

6.  Machine Learning methods for Quantitative Radiomic Biomarkers.

Authors:  Chintan Parmar; Patrick Grossmann; Johan Bussink; Philippe Lambin; Hugo J W L Aerts
Journal:  Sci Rep       Date:  2015-08-17       Impact factor: 4.379

7.  Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI.

Authors:  Rakesh Shiradkar; Tarun K Podder; Ahmad Algohary; Satish Viswanath; Rodney J Ellis; Anant Madabhushi
Journal:  Radiat Oncol       Date:  2016-11-10       Impact factor: 3.481

8.  Radiomics-based Prognosis Analysis for Non-Small Cell Lung Cancer.

Authors:  Yucheng Zhang; Anastasia Oikonomou; Alexander Wong; Masoom A Haider; Farzad Khalvati
Journal:  Sci Rep       Date:  2017-04-18       Impact factor: 4.379

9.  Predicting acute radiation induced xerostomia in head and neck Cancer using MR and CT Radiomics of parotid and submandibular glands.

Authors:  Khadija Sheikh; Sang Ho Lee; Zhi Cheng; Pranav Lakshminarayanan; Luke Peng; Peijin Han; Todd R McNutt; Harry Quon; Junghoon Lee
Journal:  Radiat Oncol       Date:  2019-07-29       Impact factor: 3.481

10.  The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping.

Authors:  Alex Zwanenburg; Martin Vallières; Mahmoud A Abdalah; Hugo J W L Aerts; Vincent Andrearczyk; Aditya Apte; Saeed Ashrafinia; Spyridon Bakas; Roelof J Beukinga; Ronald Boellaard; Marta Bogowicz; Luca Boldrini; Irène Buvat; Gary J R Cook; Christos Davatzikos; Adrien Depeursinge; Marie-Charlotte Desseroit; Nicola Dinapoli; Cuong Viet Dinh; Sebastian Echegaray; Issam El Naqa; Andriy Y Fedorov; Roberto Gatta; Robert J Gillies; Vicky Goh; Michael Götz; Matthias Guckenberger; Sung Min Ha; Mathieu Hatt; Fabian Isensee; Philippe Lambin; Stefan Leger; Ralph T H Leijenaar; Jacopo Lenkowicz; Fiona Lippert; Are Losnegård; Klaus H Maier-Hein; Olivier Morin; Henning Müller; Sandy Napel; Christophe Nioche; Fanny Orlhac; Sarthak Pati; Elisabeth A G Pfaehler; Arman Rahmim; Arvind U K Rao; Jonas Scherer; Muhammad Musib Siddique; Nanna M Sijtsema; Jairo Socarras Fernandez; Emiliano Spezi; Roel J H M Steenbakkers; Stephanie Tanadini-Lang; Daniela Thorwarth; Esther G C Troost; Taman Upadhaya; Vincenzo Valentini; Lisanne V van Dijk; Joost van Griethuysen; Floris H P van Velden; Philip Whybra; Christian Richter; Steffen Löck
Journal:  Radiology       Date:  2020-03-10       Impact factor: 29.146

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  1 in total

1.  BJR female genitourinary oncology special feature: introductory editorial.

Authors:  Stephanie Nougaret; Hebert Alberto Vargas; Evis Sala
Journal:  Br J Radiol       Date:  2021-09-01       Impact factor: 3.629

  1 in total

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