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Title: Modelling secondary cancer risk from photon and proton therapy in medulloblastoma
Author: Madkhali, Abdossalam Mohammed A.
ISNI:       0000 0004 7652 6527
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2018
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More than half of cancer patients receive radiotherapy for radical or palliative purposes. Increasing survival rates in cancer patients makes it important to study long-term side effects, especially secondary cancers. Medulloblastoma (MB), a posterior fossa tumour, predominantly a childhood disease, is an example of a clinical scenario where proton therapy could have significant advantages. It is therefore used as an exemplar in this thesis to investigate the relationship between malignant induction probability (MIP) and secondary cancer risk in 3D conformal photon therapy (3DCRT) and actively scanned proton therapy by using MATLAB-based code, models, relevant parameters and input values from voxel-by-voxel dose maps. In this thesis, work started by modelling MIP for different treatment plans to assess the relative MIP values. MIP for different modalities was investigated whilst explicitly incorporating the uncertainty in the model parameters in the modelling process. Results showed that proton therapy is less likely to induce malignancy when compared to 3DCRT (p-value < 0.05). To be able to compare our results with published absolute secondary cancer risk estimates and across patients, model parameters were calibrated and benchmarked, and absolute risk values were calculated. This thesis also addresses, in part, some of the other uncertainties that affect secondary cancer modelling. The effect of spatial dose averaging on predicting MIP was studied by modelling risk using mean, and voxel-by-voxel dose. The effect of changes in radiobiological effectiveness (RBE) on modelling MIP was also studied. This work showed that independent of the model chosen, and independent of the uncertainty in parameters, proton therapy is less likely to induce malignancy and cause secondary cancer than 3DCRT in patients with medulloblastoma. It was also shown that models used could be benchmarked and calibrated against published models, enabling the calculation of clinically realistic absolute secondary cancer risk estimates. The use of mean dose was shown to introduce a systematic error in regions of high dose inhomogeneity in comparison to the voxel-by-voxel method, making use of the high resolution voxel-by-voxel MIP calculation a necessary step in decreasing uncertainty in modelling outcomes. The work also demonstrated that using an RBE of 1.1 could lead to errors in the range of 5%, leading to potentially higher NTCP or lower local control, which is in agreement with what published literature suggests.
Supervisor: Partridge, Mike ; Timlin, Claire ; Vallis, Katherine ; Hill, Mark ; Van Den Heuvel, Frank Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Oncology ; Radiobiology ; Modelling