A Systems Approach to Modelling Tumour and Tissue Response in Radiotherapy for Head-and-Neck Cancer
type: CreativeWork
description: The heterogeneity of patient responses to radiotherapy poses significant challenges in head-and-neck cancer (HNC), with outcomes ranging from severe toxicities to loco-regional recurrence (LRR). Multi-modal biomarker data—encompassing genetic, dosimetric, and imaging domains—offers an opportunity to address this variability by leveraging all routinely collected radiotherapy data to guide personalised treatment. However, building comprehensive computational frameworks from these diverse data sources is complicated by ethical considerations, data heterogeneity, and reproducibility challenges. To address these issues, this thesis adopts a systems approach to understanding radiotherapy response, focusing on biomarker discovery at the patient, treatment, and tumour levels. This research employed a multi-faceted approach, beginning with the ethical evaluation of computational frameworks for multi-modal prediction of radiotherapy response. Key Data Hazards, such as interpretability and linkage of sensitive datasets, were identified alongside proposed strategies to mitigate these risks in current and future research. Patient-level analyses implemented genome-wide association studies (GWAS) to explore genetic contributors to radiotherapy toxicities. Common genetic variants associated with acute xerostomia and late dysphagia were identified, providing insights into the genetic basis of treatment response; however, larger national and international cohorts are needed to validate these findings. At the treatment level, a novel spatial mapping methodology classified patterns of loco-regional recurrence relative to planned dose distributions. The results revealed that most HNC recurrences occurred in high-dose regions, suggesting radioresistance and the potential need for targeted therapies. This methodology proved both reproducible and generalisable, with successful application to both HNC and breast cancer datasets. Tumour-level analyses applied a radiomic pipeline to clinical …
abstract: The heterogeneity of patient responses to radiotherapy poses significant challenges in head-and-neck cancer (HNC), with outcomes ranging from severe toxicities to loco-regional recurrence (LRR). Multi-modal biomarker data—encompassing genetic, dosimetric, and imaging domains—offers an opportunity to address this variability by leveraging all routinely collected radiotherapy data to guide personalised treatment. However, building comprehensive computational frameworks from these diverse data sources is complicated by ethical considerations, data heterogeneity, and reproducibility challenges. To address these issues, this thesis adopts a systems approach to understanding radiotherapy response, focusing on biomarker discovery at the patient, treatment, and tumour levels. This research employed a multi-faceted approach, beginning with the ethical evaluation of computational frameworks for multi-modal prediction of radiotherapy response. Key Data Hazards, such as interpretability and linkage of sensitive datasets, were identified alongside proposed strategies to mitigate these risks in current and future research. Patient-level analyses implemented genome-wide association studies (GWAS) to explore genetic contributors to radiotherapy toxicities. Common genetic variants associated with acute xerostomia and late dysphagia were identified, providing insights into the genetic basis of treatment response; however, larger national and international cohorts are needed to validate these findings. At the treatment level, a novel spatial mapping methodology classified patterns of loco-regional recurrence relative to planned dose distributions. The results revealed that most HNC recurrences occurred in high-dose regions, suggesting radioresistance and the potential need for targeted therapies. This methodology proved both reproducible and generalisable, with successful application to both HNC and breast cancer datasets. Tumour-level analyses applied a radiomic pipeline to clinical …
author: Welsh, Ceilidh
language: eng
keywords: oncology, head-and-neck cancer, radiotherapy, local recurrence, tissue toxicity
license: https://www.repository.cam.ac.uk/bitstreams/cc23fa5c-017e-4f79-b736-274225baceb1/download
license: http://purl.org/NET/rdflicense/allrightsreserved
date published: 2025-01-31
date modified: 2026-07-22T22:24:04Z
provider: Cambridge University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cambridge

PropertyValue
property ID: DOI
value: 10.17863/CAM.121839