Meeting Banner
Abstract #2432

Characterisation of disease heterogeneity in malignant pleural mesothelioma using mixture modelling of ADC and R2

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.

This abstract and the presentation materials are available to members only; a login is required.

Join Here