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Title: Prognostic radiological variables derived from oesophageal cancer staging investigations
Author: Foley, Kieran
ISNI:       0000 0004 6496 4810
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2017
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Accurate radiological staging is vital in oesophageal cancer (OC). Radiological staging largely informs risk-stratification, treatment decisions and planning. However, the prognosis of OC remains poor, suggesting that radiological staging must improve. Therefore, the additional value of novel prognostic variables compared to current staging methods was assessed in a large cohort of OC patients managed by a regional upper gastrointestinal cancer network. Radiological-pathological correlation of resected lymph nodes assessed the accuracy of CT, EUS and PET/CT N-stage. The added value of PET-defined variables to predict circumferential resection margin (CRM) involvement was investigated. With EUS use declining, differences in PET and EUS measurements were assessed to understand potential implications for treatment planning should staging PET/CT be performed alone. Validation of two prognostic models; one in patients staged N0 on PET/CT and one incorporating novel PET features, was performed. The accuracy of CT, EUS and PET/CT N-stage was poor (54.5%, 55.4% and 57.1%, respectively) which greatly impacts on patient selection and treatment decisions. EUS continues to play an important role in OC staging, being significantly and independently associated with overall survival (OS;p=0.012) and CRM involvement (p=0.022). PET-defined variables had no additional value for predicting CRM status. The difference between PET and EUS length of disease was statistically significant (p < 0.001), increasing the risk of geographical miss (38.1%) had PET/CT been used alone. Three novel PET image features (log (TLG), log(Histogram Energy) and Histogram Kurtosis) were independently associated with OS in the prognostic model. There was a significant OS difference between patient quartiles (p < 0.001) in the development and validation cohorts. Incorporation of these image features added prognostic value and improved model performance compared to current staging methods. These significant data demonstrate radiological prognostic variables that add value in OC management and highlight the importance of improved radiological staging.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available