Back to Search Start Over

NAVIGATOR: an Italian regional imaging biobank to promote precision medicine for oncologic patients

Authors :
Rita Borgheresi
Andrea Barucci
Sara Colantonio
Gayane Aghakhanyan
Massimiliano Assante
Elena Bertelli
Emanuele Carlini
Roberto Carpi
Claudia Caudai
Diletta Cavallero
Dania Cioni
Roberto Cirillo
Valentina Colcelli
Andrea Dell’Amico
Domnico Di Gangi
Paola Anna Erba
Lorenzo Faggioni
Zeno Falaschi
Michela Gabelloni
Rosa Gini
Lucio Lelii
Pietro Liò
Antonio Lorito
Silvia Lucarini
Paolo Manghi
Francesco Mangiacrapa
Chiara Marzi
Maria Antonietta Mazzei
Laura Mercatelli
Antonella Mirabile
Francesco Mungai
Vittorio Miele
Maristella Olmastroni
Pasquale Pagano
Fabiola Paiar
Giancarlo Panichi
Maria Antonietta Pascali
Filippo Pasquinelli
Jorge Eduardo Shortrede
Lorenzo Tumminello
Luca Volterrani
Emanuele Neri
on behalf of the NAVIGATOR Consortium Group
Source :
European Radiology Experimental, Vol 6, Iss 1, Pp 1-13 (2022)
Publication Year :
2022
Publisher :
SpringerOpen, 2022.

Abstract

Abstract NAVIGATOR is an Italian regional project boosting precision medicine in oncology with the aim of making it more predictive, preventive, and personalised by advancing translational research based on quantitative imaging and integrative omics analyses. The project’s goal is to develop an open imaging biobank for the collection and preservation of a large amount of standardised imaging multimodal datasets, including computed tomography, magnetic resonance imaging, and positron emission tomography data, together with the corresponding patient-related and omics-related relevant information extracted from regional healthcare services using an adapted privacy-preserving model. The project is based on an open-source imaging biobank and an open-science oriented virtual research environment (VRE). Available integrative omics and multi-imaging data of three use cases (prostate cancer, rectal cancer, and gastric cancer) will be collected. All data confined in NAVIGATOR (i.e., standard and novel imaging biomarkers, non-imaging data, health agency data) will be used to create a digital patient model, to support the reliable prediction of the disease phenotype and risk stratification. The VRE that relies on a well-established infrastructure, called D4Science.org, will further provide a multiset infrastructure for processing the integrative omics data, extracting specific radiomic signatures, and for identification and testing of novel imaging biomarkers through big data analytics and artificial intelligence.

Details

Language :
English
ISSN :
25099280
Volume :
6
Issue :
1
Database :
Directory of Open Access Journals
Journal :
European Radiology Experimental
Publication Type :
Academic Journal
Accession number :
edsdoj.0bbb138068fa4165aef249eb563ca969
Document Type :
article
Full Text :
https://doi.org/10.1186/s41747-022-00306-9