Most patients with cancer undergo invasive procedures before precision treatment can be initiated. Virtual biopsy, i.e. providing tissue diagnosis through radiological imaging, holds the promise to reduce diagnostic invasiveness, while also providing fundamental insights into cancer biology in vivo beyond the current surgical biopsy reference standard. Although it is unrealistic at present to expect that non-invasive diagnosis will entirely replace tissue diagnosis in the near future, there is much to be gained – both clinically and scientifically – from changing our current paradigms and leveraging the information that can be obtained from non-invasive tumour imaging with novel imaging techniques and analysis methods.
This project centres around patients with brain cancer, in whom procedures to obtain tumour tissue are particularly impactful. With my research team, I willwork towards quantitative diagnostics from both radiological and histopathological imaging, by developing computational analysis methods to characterize the brain tumour with MRI (radiomics) and histopathology (pathomics) quantitatively. In parallel, I will use advanced MRI techniques to obtain in-depthcellular, metabolic and physiological information from the tumour in vivo. Combined, these provide information on tissue dynamics, spatial and longitudinal heterogeneity, which cannot be appreciated from ex vivo tissue diagnostics. Using this cross-modal radiomics-pathomics approach, I expect to improve tissue-based diagnosis, with direct impact on clinical management, and provide fundamental insights into the tumour micro-environment. These will be crucial steps towards my end-goal of virtual biopsy, which may eventually be used in selected patient populations to obviate surgery solely performed for tissue diagnosis.
To ease transition towards clinical practice, I will perform an in silico trial to determine the introduction of such non-invasive diagnostics into the clinical workflow.
This paves the way towards clinical acceptability of virtual biopsy and will eventually lead to better informed clinical decision making by healthcare professionals and patients.