Imaging biomarkers for oligometastatic colorectal cancer - Franklin, J (2018)
Oligometastatic colorectal cancer represents an intermediate disease state potentially treatable with curative intent. Novel treatment strategies are expanding the opportunity to offer local treatment for limited metastatic disease. It is therefore increasingly important to define patients likely to benefit from these targeted treatments. Diagnostic imaging is central to patient management, to establish the burden and distribution of metastatic disease. This thesis explores the potential value of novel imaging biomarkers in patients with colorectal liver metastases (CRLM). In a prospective study, perfusion CT (pCT) and dynamic contrast-enhanced MRI (DCE-MRI) were performed prior to resection, and a retrospective series of patients with resected CRLM was collated. Resected metastases were analysed for relevant morphological features and IHC expression. Novel and conventional imaging variables were derived based on CT, MRI, pCT, DCE-MRI and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG-PET), and their associations with histopathological features, immunohistochemical expression and patient outcomes analysed. A novel subregion analysis based on DCE-MRI data was developed to classify tumour subregions, using a histological reference standard. The results presented in this thesis confirm that the number and distribution of hepatic metastases are prognostic markers for patients with resected CRLM, and that higher SUVmean of liver metastases, and higher SUVmax of the background liver, are potential prognostic biomarkers. Histopathological assessment of resected CRLM highlighted that there is significant between and within patient variability of clinically relevant histopathological features and IHC expression, which would support the potential utility of imaging biomarkers to characterise multi- site disease. Analysis of functional imaging data demonstrated positive correlations between imaging variables and clinically relevant markers of tumour vascularity and metabolism, while subregion analysis of DCE-MRI data produced good spatial correlation with viable and non-viable tumour based on histopathology, with significant differences in derived phamacokinetic parameters between subregions.