Non-invasive MRI Biomarkers for Oncology

This project develops innovative Magnetic Resonance Imaging (MRI) methods to reveal new non-invasive markers of cancer pathology. In particular the research programme develops biophysical models of tumour tissue that support non-invasive estimates of key characteristics of tissue cellular architecture including those that currently guide diagnosis, grading, and treatment assignment through classical histology. These cellular characteristics include cell size, cell shape, cell density, similar features of subcellular structures, and potentially new features that histology cannot reveal such as cell membrane permeability and cell cytoplasm viscosity. In contrast to classical histology, such an approach avoids unnecessary interventions like biopsies. Moreover, the models combine with macroscopic imaging to provide maps of histological features over the whole organ, thus evading false-positives from poor biopsy targeting. In contrast to current imaging techniques, the new model-based imaging techniques provide much greater specificity associating contrast with particular tissue changes thus providing much better information on which to assign treatment. The ultimate goal is to enable non-invasive cancer detection, staging and grading entirely through harmless imaging.

The project will leverage the advances of a method I recently devised, called VERDICT, which uses diffusion MRI to provide an early demonstration of the power of such a model-based imaging technique in estimating cancer-tissue microstructure non-invasively. This project builds on these ideas to achieve the performance levels required to allow robust detection, grading and staging for establishing non-invasive imaging as the primary cancer diagnostic method. The project exploits advances in computational methods and in MRI technology to improve sensitivity and specificity dramatically. Specifically: 1) sophisticated optimisation techniques will enhance performance and practical utility of non-invasive model-based imaging; 2) advanced MRI sequences will allow access to new and important cancer microstructural features, such as the morphology of cell nuclei, and 3) alternative contrast methods will extend the methods to other MRI modalities beyond diffusion for complementary and additional cancer malignancy information. Although the project focuses on prostate cancer, it also aims to initiate follow-on projects to explore applications to other cancers such as brain, breast and bone metastasis.

This fellowship is a significant stepping-stone for my career in fighting cancer. My aspiration is for patients to have a quick, safe and comfortable clinical cancer examination with determinate diagnosis. Towards this vision the fellowship will allow me to capitalise on my recent progress on this idea, exploiting my current expertise in diffusion MRI, and its application in cancer. It provides me the opportunity to gain experience of leading my own multidisciplinary project and research team thus establishing myself in the UK and internationally as a leader on that topic. Moreover, the fellowship will allow me to broader my skills and collaborations to the wider medical imaging arena and variety of clinical applications in cancer. This underpins my development towards an international academic leader in the fields of computational imaging and cancer research and management.

In spite of significant advances in diagnosis and treatment, cancer remains a major killer. Diagnosis is often inaccurate and subsequent treatment ineffective for far too many patients. Specifically prostate cancer diagnosis still relies on traditional histology via biopsies. Each year in the UK 75000 men undergo this invasive procedure, which can have unpleasant side effects and poor sensitivity, as the biopsy may miss lesions. A recent study indicates that more than 50% of prostate biopsy analyses underestimate the severity of the disease. Simultaneously biopsy can also lead to "over-diagnosis" as it can detect small clinically insignificant lesions, by random chance, which are indolent and do not need treatment. This detection of indolent disease often leads to men undergoing unnecessary radical surgery or radiotherapy. Approximately 90% of prostate cancer patients undergo such interventions, which can cause side effects like incontinence, significantly impacting their quality of life. Additionally a negative biopsy result does not imply free of cancer and negative-biopsy patients are monitored in regular repeat exams. The on-going process increases risks of side effects and is expensive for the National Health Service. Similar statistics of risks and costs translate worldwide and are also associated with other common cancers such as breast, bowel and liver.

This project develops non-intrusive imaging methods to provide diagnostic information as powerful as current invasive techniques. Primarily this will ameliorate patient suffering from the examination and the side effects, while assisting better clinical detection, staging and diagnosis by earlier and enhanced knowledge of what is happening at the tissue level. In particular improved detection rates can reduce the number of biopsies and repeated biopsies. Fewer biopsies can also decrease the cost of treatments from avoiding side effects such as urinary retention and rectal bleeding. Avoidance of biopsies will also contribute to the sustainability of the healthcare system by drastically reducing the number of surgical procedures and histopathological evaluations. Earlier cancer diagnosis can lead to more effective and potentially less radical/harmful treatments.

The microstructure MRI methods will provide new insight into cancer biology concerning the mechanisms of tumour growth, interactions between cancer cells and healthy tissue, the role of inflammation and subtle or difficult to detect effects such as distinguishing between apoptosis and necrosis, encouraging exciting new research prospects. Further exploitation of such computational methods can lead to identification of subgroups of biological targets in the tumour that when correlated with tumour genetics could lead to the design of individualised therapies based on metabolic pathways, achieving patient stratification for precision medicine.

The development of new MRI techniques can impact the commercial and industrial sector, such as MRI manufacturers, offering opportunities that can drive future development of medical hardware; Philips Healthcare have expressed their strong support and interest in the project. Finally microstructure imaging can also inform drug development and trials, revealing the effects of treatment earlier, moving trials more quickly to the final stages and accelerating the availability of new promising cancer treatments to patients.