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Published in: Pediatric Radiology 4/2024

25-09-2023 | Neuroblastoma | ESPR Belgrade 2023 - Postgraduate Course and Taskforce Lectures

Imaging biomarkers and radiomics in pediatric oncology: a view from the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project

Authors: Diana Veiga-Canuto, Leonor Cerdá Alberich, Matías Fernández-Patón, Ana Jiménez Pastor, Jose Lozano-Montoya, Ana Miguel Blanco, Blanca Martínez de las Heras, Cinta Sangüesa Nebot, Luis Martí-Bonmatí, PRIMAGE Project consortium

Published in: Pediatric Radiology | Issue 4/2024

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Abstract

This review paper presents the practical development of imaging biomarkers in the scope of the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project, as a noninvasive and reliable way to improve the diagnosis and prognosis in pediatric oncology. The PRIMAGE project is a European multi-center research initiative that focuses on developing medical imaging-derived artificial intelligence (AI) solutions designed to enhance overall management and decision-making for two types of pediatric cancer: neuroblastoma and diffuse intrinsic pontine glioma. To allow this, the PRIMAGE project has created an open-cloud platform that combines imaging, clinical, and molecular data together with AI models developed from this data, creating a comprehensive decision support environment for clinicians managing patients with these two cancers. In order to achieve this, a standardized data processing and analysis workflow was implemented to generate robust and reliable predictions for different clinical endpoints. Magnetic resonance (MR) image harmonization and registration was performed as part of the workflow. Subsequently, an automated tool for the detection and segmentation of tumors was trained and internally validated. The Dice similarity coefficient obtained for the independent validation dataset was 0.997, indicating compatibility with the manual segmentation variability. Following this, radiomics and deep features were extracted and correlated with clinical endpoints. Finally, reproducible and relevant imaging quantitative features were integrated with clinical and molecular data to enrich both the predictive models and a set of visual analytics tools, making the PRIMAGE platform a complete clinical decision aid system. In order to ensure the advancement of research in this field and to foster engagement with the wider research community, the PRIMAGE data repository and platform are currently being integrated into the European Federation for Cancer Images (EUCAIM), which is the largest European cancer imaging research infrastructure created to date.

Graphical abstract

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Metadata
Title
Imaging biomarkers and radiomics in pediatric oncology: a view from the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project
Authors
Diana Veiga-Canuto
Leonor Cerdá Alberich
Matías Fernández-Patón
Ana Jiménez Pastor
Jose Lozano-Montoya
Ana Miguel Blanco
Blanca Martínez de las Heras
Cinta Sangüesa Nebot
Luis Martí-Bonmatí
PRIMAGE Project consortium
Publication date
25-09-2023
Publisher
Springer Berlin Heidelberg
Published in
Pediatric Radiology / Issue 4/2024
Print ISSN: 0301-0449
Electronic ISSN: 1432-1998
DOI
https://doi.org/10.1007/s00247-023-05770-y

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