Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.793517
Title: A tumour database with prediction tools for side effects and modelling of hadron therapy
Author: Kanellopoulos, Vassiliki S. E.
Awarding Body: University of Surrey
Current Institution: University of Surrey
Date of Award: 2019
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Abstract:
About 50% of all cancer patients receive radiotherapy in the course of their disease. Hadron therapy uses protons or ions and shows a more advantageous depth-dose characteristic compared to photons. The superior dose distribution of particles enables to deliver a high dose to the tumour whilst sparing normal tissue. Although hadron therapy is believed to be superior to advanced photon therapies for certain types of cancers it has yet not been possible to draw definite conclusions from current clinical studies. To support the necessary extensive documentation of tumour, treatment and side effects data a database model for hadron therapy was established. It was implemented in a prototype hadron therapy information sharing platform. The assessment of a new treatment modality is based on the evaluation of treatment outcome and treatment related side effects. For this a generic Markov model for the evaluation of side effects was developed. Data from the database can automatically be used to refine the model and convert it into a tumour or treatment specific prediction model. Treatment models are a very powerful tool to investigate therapy options within silico clinical trials. A novel analytical model is introduced which describes the response of solid tumours to radiation therapy in a simple yet effective way. The introduction of proliferating and quiescent tumour cells enables to simulate important characteristics of tumour behaviour like sigmoid growth, cell quiescence, cell death and response to radiation therapy with different beam qualities. Main basic principles of fractionation like repair, redistribution, repopulation, reoxygenation and radiosensitivity are naturally contained within the model. The model involves the patient, tumour growth and fractionated radiotherapy to predict tumour recurrence. It is successfully applied to clinical data of patients treated with photons, protons and carbon ions for skull base chordoma and investigated for indications for hadron therapy.
Supervisor: Webb, Roger Sponsor: Marie Curie Initial Training Fellowship of the European Community
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.793517  DOI:
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