Radiomics : principles and radiotherapy applications

Gardin, Isabelle; Grégoire, Vincent; Gibon, David; Kirisli, Hortense; Pasquier, David; Thariat, Juliette; Vera, Pierre

Document type :

Compte-rendu et recension critique d'ouvrage

DOI :

10.1016/j.critrevonc.2019.03.015

Title :

Radiomics : principles and radiotherapy applications

Author(s) :

Gardin, Isabelle [Auteur]
Equipe Quantification en Imagerie Fonctionnelle [QuantIF-LITIS]
Grégoire, Vincent [Auteur]
Université Catholique de Louvain = Catholic University of Louvain [UCL]
Gibon, David [Auteur]
Centre Régional de Lutte contre le Cancer Oscar Lambret [Lille] [UNICANCER/Lille]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Kirisli, Hortense [Auteur]
Centre Régional de Lutte contre le Cancer Oscar Lambret [Lille] [UNICANCER/Lille]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Pasquier, David [Auteur]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Centre Régional de Lutte contre le Cancer Oscar Lambret [Lille] [UNICANCER/Lille]
Thariat, Juliette [Auteur]
Laboratoire de physique corpusculaire de Caen [LPCC]
Vera, Pierre [Auteur]
Equipe Quantification en Imagerie Fonctionnelle [QuantIF-LITIS]

Journal title :

Critical Reviews in Oncology/Hematology

Pages :

44-50

Publisher :

Elsevier

Publication date :

2019

ISSN :

1040-8428

English keyword(s) :

Radiomics
Radiotherapy
Chemoradiotherapy
Medical imaging

HAL domain(s) :

Sciences du Vivant [q-bio]

English abstract : [en]

Radiomics is defined as the extraction of a large quantity of quantitative image features. The different radiomic indexes that have been proposed in the literature are described as well as the various factors that have an ...
Show more >Radiomics is defined as the extraction of a large quantity of quantitative image features. The different radiomic indexes that have been proposed in the literature are described as well as the various factors that have an impact on the robustness of these indexes. We will see that several hundred quantitative features can be extracted per lesion and imaging modality. The ever-growing number of features studied raises the question of the statistical method of analysis used.This review addresses the research supporting the clinical use of radiomics in oncology in the staging of disease, discrimination between healthy and pathological tissues, the identification of genetic features, the prediction of patient survival, the response to treatment, the recurrence after radiotherapy and chemoradiotherapy and the side effects.Based on the existing literature, it remains difficult to identify features that should be used for current clinical practice.Show less >

Language :

Anglais

Popular science :

Non

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