With research presented in this PhD thesis I aimed to develop advanced MRI techniques to address unmet clinical needs in the management of early-stage (localised and locallyadvanced) renal cancer. Renal cancer is the deadliest urological malignancy with a widening gap between incidence and mortality, which highlights the need to review the current guidelines. In particular, early-stage renal cancer is to be looked into as it is usually discovered incidentally, yet current diagnostic pathway cannot accurately determine the nature of the mass. This has implications for management, causing treatment delays in case of malignancy, or overtreatment in of benign renal masses. Also, early-stage renal cancer has excellent survival, but this drops rapidly in later stages. In Chapter 1 I review the current clinical guidelines, identify the unmet needs, and propose how metabolic imaging techniques could be used to tackle these needs. This proposal was the core of my PhD research, of which results I present in Chapters 2-4, as described below. Chapter 2: here I investigated the potential of hyperpolarised [1-13C]pyruvate MRI (HP 13C-MRI) to probe metabolic intratumoral heterogeneity in renal cancer. I discovered that within a single tumour, regions of varying degrees of perfusion and Warburg effect are present, which differ in aggressiveness. Chapter 2 presents my findings in two clinical scenarios: in a fumarate hydratase-deficient (FHd) renal cell carcinoma (RCC) case, which is a rare but highly aggressive RCC subtype (Chapter 2.1); and in a cohort of patients with clear cell RCC (Chapter 2.2), which is the most common malignant histological subtype of kidney cancer. Both projects suggested higher aggressiveness in the intratumoural region exhibiting low perfusion and high Warburg effect, the socalled perfusion/metabolism mismatch. This could have ramifications for informing the interventional radiologist to target the biopsy to this specific region for higher specificity yield, or adapting the therapy based on the underlying biology of the most aggressive region (e.g. immune-checkpoint inhibition rather than anti-angiogenetic agent as I propose in the FHd-RCC report). Chapter 3: here I have addressed the unmet clinical need for more accurate renal tumour subtype differentiation. Building on previously reported findings on potential of HP 13C-MRI in aggressiveness stratification, I have expanded this research question to include another metabolic MRI technique, the deuterium metabolic imaging (DMI). We have previously applied the DMI in the brain, but it has thus far not been probed within abdominal area in a clinical setting. In collaboration with our team’s MRI physicists I successfully secured a fund towards acquiring the abdominal DMI coil, and in parallel, I have conceptualised, submitted and received ethics approval for my own research study, called IBM-Renal (Investigation of differential biology of Benign and Malignant renal masses using advanced MRI techniques) - protocol paper is to be found in Appendix A1. We also received Primer Award from CRUK to support funding of this research. The IBM-Renal study not only allowed us to investigate the potential of DMI in renal tumour subtypes differentiation (Chapter 3.1), but also to understand the role of other micro- and macrostructural processes in subtype characterisation. This included studying the sodium content using the 23Na-MRI (Chapter 3.2) and studying molecular motion affecting the T2 relaxation time, and thus performing T2 mapping (Chapter 3.3). Chapter 4: here I probed the potential of HP 13C-MRI to detect response to neoadjuvant treatment in ccRCC as part of the WIRE clinical trial (WIndow-ofopportunity clinical trial platform for evaluation of novel treatment strategies in REnal cell cancer). I found that in the four imaged cases, the 13C-pyruvate-to-lactate conversion was highly variable depending on the treatment agent and speculating about the differential treatment response. In conclusion, my research focuses on the development and application of metabolic MRI techniques to improve the diagnosis, characterization, and treatment monitoring of kidney cancer. By addressing the current limitations in clinical management, these techniques have the potential to significantly impact patient care and outcomes in kidney cancer, reducing mortality and improving overall quality of life.