This technique is currently being used in Renal Cancer.
In this project we investigate the ability of radiomics of standard of care imaging in RCC to support clinical decision making. Radiomics models may help address clinical questions which are difficult to assess with subjective image interpretation. Questions, which are of particular interest to our group, are the imaging-based prediction of tumour subtype, aggressiveness and early response to therapy.
Imaging plays an important role in oncological treatment response assessment for many cancer types. With the availability of an increasing number of targeted and non-targeted anti-cancer drugs for renal cancer, the rapid detection of treatment response and relapse become of increasing clinical relevance. In collaboration with colleagues from the departments of urology and oncology, we investigate how multiparametric MRI can be utilised for treatment stratification in current and future clinical trials.
The radiomics of computed tomography and magnetic resonance imaging in renal cell carcinoma study gives a deeper dive into this research;
Ursprung, S. et al, European Radiology, 2020
Summary: Radiomics algorithms show promise for answering clinical questions where subjective interpretation is challenging or not established. However, the generalizability of findings to prospective cohorts needs to be demonstrated in future trials for progression towards clinical translation. Improved sharing of methods including code and images could facilitate independent validation of radiomics signatures.
The Mark Foundation Institute for Integrated Cancer Medicine (MFICM) at the University of Cambridge aims to revolutionise cancer care by affecting patients along their treatment pathway.