Optimising Prostate Radiation Using Magnetic Resonance Imaging and Hypoxia Biomarkers

Despite radiotherapy (RT) being an effective treatment, prostate cancer recurrence is not uncommon, particularly in high-risk disease. A key biological process driving treatment failure is tumour hypoxia which is associated with radiotherapy resistance. Established methods of detecting hypoxia are invasive and not routinely undertaken. Predicting which patients will recur after RT and those more likely to suffer from RT-related side effects is also challenging. Quantitative analysis of routinely acquired prostate magnetic resonance imaging (MRI) data might help to address these existing dilemmas. The choice of the optimal treatment for recurrent prostate cancer remains uncertain and warrants further investigation. The aims of this PhD thesis were to investigate the role of quantitative MRI and hypoxia biomarkers in optimising prostate RT, predicting oncological outcomes and toxicity, and providing further evidence on the efficacy of prostate reirradiation.

The following five studies were undertaken during this PhD: A model to predict prostate tumour hypoxia using pre-treatment MRI-derived radiomics was developed and
compared to an established genomic hypoxic signature using a twin-centre retrospective cohort of patients with prostate cancer. The potential utility of an outcome prediction model integrating radiomic and hypoxia information with clinical data for predicting biochemical recurrence free survival (BCRFS) was explored. An exploratory study of bladder and rectum radiomic feature changes following external beam radiation therapy (EBRT) delivered on a magnetic resonance imaging linear accelerator (MRI-LINAC) was undertaken. A systematic review of the evidence for prostate reirradiation in locally recurrent cancer was undertaken. Finally, a prospective trial Reirradiation Options for Previously Irradiated Prostate cancer (RO-PIP) comparing different radiation treatments for recurrent prostate cancer was designed and set-up.

The key findings from this PhD included: Whole prostate MRI-radiomics has the potential to non-invasively predict tumour hypoxia prior to radiotherapy, which may be helpful for individualised treatment optimisation. The addition of pre-treatment MRI-derived radiomic features to clinical variables improved the accuracy of predicting BCRFS after prostate radiotherapy with or without the addition of hypoxia gene signature. A feasible methodology for collecting longitudinal radiomic changes from the bladder and rectum during MRI-LINAC radiotherapy treatments was designed and preliminary results show potential radiomic changes between the EBRT treatment time points. Published literature evaluating salvage reirradiation of radiorecurrent prostate cancer using stereotactic body radiotherapy (SBRT) or high-dose-rate brachytherapy (HDR-BT) reports similar biochemical control and acceptable late toxicity however data is mainly retrospective and of low quality and prospective randomised trials are needed. The RO-PIP study, a feasibility study investigating toxicity outcomes following reirradiation with SBRT versus HDR-BT is currently open to recruitment.

Pre-treatment MRI-derived radiomic analysis may help reveal underlying biological processes such as tumour hypoxia and in outcome prediction models. Longitudinal evaluation of radiomic feature changes using an MRI-LINAC potentially provides an innovative way of measuring tissue response during radiotherapy treatments. A feasibility study of reirradiation techniques should help inform the design of a future phase 3 trial, which could be driven by MRI biomarkers