Unicancer 2020 award, 6th edition.
Aim of the project:
Our project is to develop an application that enables multicenter evaluation of radiomic and AI models proposed for managing patients with lung cancer. Multicenter validation of these models is essential before they can be considered for clinical use.
Target users:
Our project will serve both current and future LIFEx users. Ten Unicancer centers already use LIFEx, alongside approximately 10,000 users worldwide, and we add about 100 new users each month. The user base consists mainly of radiologists, nuclear medicine physicians, researchers, and engineers working in medical image analysis.
Methods:
This application will actually be a new module added to LIFEx, a software we are developing, to easily describe a radiomic model. As for any module of this application, the libraries used will guarantee that the application remains free and autonomous (i.e. without installation of third party software). Interfacing with the ConSoRe platform, which is a Unicancer's Big Data platform, will later make it possible to combine features extracted from medical images and text included in the medical reports.
Impact:
The main benefit will be to give medical teams a tool to evaluate radiomic and AI models on their own data, using models that have already been published or developed by colleagues. This large-scale, multicenter validation step provides information on the reliability and robustness of the models and is absolutely essential for clinical translation.
Problem to be solved:
If the field of radiomics and AI in radiology and nuclear medicine is growing exponentially, the current major bottleneck is the difficulty to validate the many published models in order to establish their performance and clinical added value. Our project will make this evaluation possible in an independent way, via a public software guaranteeing the transparency of the results.
The Best of the AACR journals,
The most-cited research articles:
