Lin Cheng1, Matthew D. Blackledge1, David J. Collins1, Nina Tunariu1,2, Neil P. Jerome1, Matthew R. Orton1, Veronica A. Morgan3, Martion O. Leach1, and Dow-Mu Koh1,2
1Division of Radiotherapy and Imaging, Cancer Research UK Cancer Imaging Centre, Institute of Cancer Research, London, United Kingdom, 2Radiology, Royal Marsden Hospital, London, United Kingdom, 3Clinical MRI Unit, Royal Marsden Hospital, London, United Kingdom
Disease
heterogeneity in patients with malignant pleural mesothelioma (MPM) makes it
challenging to characterise solid disease and assess response following
treatment. Computed
Diffusion-Weighted MRI (cDWI) provides improved contrast between disease and
background tissues, and facilitates total disease segmentation. A
mixture modelling of ADC and R2 with semi-automatic segmentation
on the cDWI is proposed to assess disease heterogeneity in MPM, with demonstration
of its utility on a paired pre/post-treatment dataset. The mixture
modelling methodology successfully characterised disease heterogeneity for two
MPM patients, and can provide additional quantitative functional disease
response characterisation compared with using only a single parameter.
