The field of medical imaging has experienced significant growth in the last 20 years, with the democratization of multiparametric MRI in both preclinical and clinical settings. These technological developments in acquisition have been accompanied by the development of new analysis methods allowing for the extraction of quantitative information from these images. Notably, radiomics and deep learning approaches have been developed. Ultimately, many studies have shown correlations between certain metrics and a diagnosis or a pathological evolution. These metrics are commonly referred to as imaging biomarkers.

This presentation will present the work carried out by our team at the Grenoble Institute of Neurosciences, on the development and the validation of new imaging biomarkers applied to glioblastomas in various preclinical and clinical studies. Our research topics focus on the development of new MRI acquisition methods and on the development of analysis methods dedicated to medical imaging based on machine and deep learning. This presentation will focus on glioblastomas, but we will see that these methods can be applied to other imaging modalities and other brain pathologies.

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