QuantImage: an online tool for high-throughput 3D radiomics feature extraction in PET-CT

Dicente Cid, Yashin (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) ; University of Geneva, Switzerland) ; Castelli, Joël (Lausanne University hospital (CHUV), radiotherapy department, Switzerland ; INSERM, Rennes, France ; University of Rennes, France) ; Schaer, Roger (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Scher, Nathaniel (Lausanne University hospital (CHUV), radiotherapy department, Switzerland) ; Pomoni, Anastasia (Lausanne University hospital (CHUV), nuclear medicine and molecular imaging department, Switzerland) ; Prior, John O. (Lausanne University hospital (CHUV), nuclear medicine and molecular imaging department, Switzerland) ; Depeursinge, Adrien (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) ; Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland)

Theprocessesofradiomicsconsistofimage-basedpersonalizedtumorphenotypingforpre-cision medicine. They complement slow, costly and invasive molecular analysis of tumoral tissue. Whereastherelevanceofalargevarietyofquantitativeimagingbiomarkershasbeen demonstrated for various cancer types, most studies were based on 2D image analysis of relatively small patient cohorts. In this work, we propose an online tool for automatically ex-tracting 3D state-of-the-art quantitative imaging features from large batches of patients. The developed platform is called QuantImage and can be accessed from any web browser. Its use is straightforward and can be further parameterized for refined analyses. It relies on a robust 3D processing pipeline allowing normalization across patients and imaging protocols. Theusercansimplydrag-and-dropalargezipfilecontainingallimagedataforabatchofpa-tients and the platform returns a spreadsheet with the set of quantitative features extracted for each patient. It is expected to enable high-throughput reproducible research and the validation of radiomics imaging parameters to shape the future of non-invasive personalized medicine.


Mots-clés:
Faculté:
Economie et services
Ecole:
HEG VS HES-SO Valais-Wallis - Haute Ecole de Gestion & Tourisme
Institut:
Institut Informatique de gestion
Classification:
Economie/gestion
Adresse bibliogr.:
London, Academic Press
Date:
London
Academic Press
2017
Pagination:
pp. 365-394
Titre du document hôte:
Biomedical texture analysis : fundamentals, tools and challenges
ISBN:
9780128121337
Ressource(s) externe(s):
Le document apparaît dans:

Note: The status of this file is: restricted


 Notice créée le 2017-11-06, modifiée le 2017-11-10

Fichiers:
Télécharger le document
PDF

Évaluer ce document:

Rate this document:
1
2
3
 
(Pas encore évalué)