Advanced magnetic resonance imaging in lung mesothelioma
Thesis or Dissertation
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Malignant pleural mesothelioma (MPM) has a rind-like growth pattern and may have both solid disease and pleural fluid, so it is very challenging to accurately categorize change in tumour burden using size-based tumour response criteria, eg. modified Response Evaluation Criteria in Solid Tumours (RECIST). Diffusion Weighted Magnetic Resonance Imaging (DWI) provides functional information of tissue microstructure and is a promising technique to enable segmentation of tumours due to its excellent contrast between tumour and suppressed background. The aim of this thesis is to evaluate the changes in tumour volume and functions during treatment thus assess disease treatment response using DWI. A novel method, T2-adjusted computed diffusion weighted magnetic resonance imaging (T2-cDWI), is proposed to improve the image contrast between solid tumour and pleural effusion, and may eliminate T2 shine-through effect. In T2-cDWI, T2-weighted echo-planar images at multiple (>2) echo times were acquired in addition to the standard DWI acquisition protocol. To acquire the solid tumour volume, a workflow including image segmentation and classification has been investigated on DWI images and further applied in a clinical mesothelioma study for treatment response evaluation. DWI imaging protocols were developed to dovetail with a routine clinically chest scan for treatment evaluation. Using previously developed workflow, volumetric tumour burden and DWI parameter values are obtained and shown to be correlated with disease progression after treatment. These results clearly show the potential for the developed tools as a novel and quantifiable biomarker for assessing the volumetric response of MPm to therapy compared with the conventional modified RECIST. In summary, this thesis has investigated and provided a new volumetric response assessment strategy for MPM patients using DWI images.
Magnetic Resonance Imaging
Lung Cancer - Radiology
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Institute of Cancer Research (University Of London)