Quantitative neuroimaging with handcrafted and deep radiomics in neurological diseases

Mrs Elizaveta Lavrova will publicly defend her thesis entitled "Quantitative neuroimaging with handcrafted and deep radiomics in neurological diseases".

Summary

Neurological diseases are a major cause of disability and death globally, and there is a pressing need for reliable imaging biomarkers to aid in disease detection and monitoring. While radiomics has shown promising results in oncology, its application in neurology remains relatively unexplored. Therefore, this work aims to investigate the feasibility and challenges of implementing radiomics in the neurological context, addressing various limitations and proposing potential solutions. The thesis begins with a demonstration of the predictive power of radiomics in neuro-oncology. The research then delves into radiomics in non-oncological neurology, providing an overview of the pipeline steps, potential clinical applications, and existing challenges. To explore the predictive power of radiomics in non-oncological tasks, a radiomics approach was implemented to distinguish between multiple sclerosis patients and normal controls. To overcome the data harmonization challenge, in this work quantitative mapping of the brain was suggested. Another crucial challenge in radiomics is robust and fast data labelling, particularly segmentation. A deep learning method was proposed to perform automated carotid artery segmentation in stroke at-risk patients, surpassing current state-of-the-art approaches. In addition to addressing specific challenges, the thesis also proposes a community-driven open-source toolbox for radiomics, aimed at enhancing pipeline standardization and transparency. This thesis demonstrates its potential to enhance neurological disease diagnosis and monitoring. By addressing the challenges identified in this thesis and fostering collaboration within the research community, radiomics can advance toward clinical implementation, revolutionizing precision medicine in neurology.

Practical information

Defence will take place on May 31st at 10:00, to all at the Executive Board building of the University of Maastricht or via  https://youtube.com/@UMphddefense