Since October 2017, The Aftershock has helped fund 3 high mortality rate cancer research projects.
While thyroid cancer is relatively rare, benign thyroid nodules are very common. Therefore, thyroid cancer research not only needs to focus on improving mortality for patients with aggressive disease, but researchers also need to develop systems to minimise over-treatment of the vast majority of patients with benign thyroid diseases or less aggressive cancer.
Precision medicine in thyroid cancer care is one of James’ key research themes. More specifically, a current research project aims to develop molecular markers that would improve the diagnosis of thyroid cancer on needle biopsy, thus allowing treating surgeons to determine the exact extent of surgery needed. James currently collaborates with other clinicians and researchers from institutions across Victoria to achieve this vision.
In early 2019, The Aftershock commenced support for Professor Meng Law, Head of Clinical Imaging, and his team to research into how to use AI to predict the appearance and growth of brain tumours on MRI.
This research aims to determine imaging, genomic, other biomarkers in the early diagnosis of neurogenerative diseases, apply artificial intelligence for diagnoses and test new therapeutic agents in clinical trials. The research centre on pre-clinical and translational clinical imaging in neurological disease but also some non-neurological diseases. Meng and his team utilise state of the art and ultra-high field MRI, PET, CT, magnetic particle imaging, photon microscopy approaches towards imaging pathology. They also house a data warehouse and repository for imaging, genomics, biomarker, pathology and other data to be used for machine learning, deep learning, artificial intelligence applications in diagnostics and therapeutics. They also perform pre-clinical and clinical trials on novel therapeutics in neurodegenerative diseases and non-neurological diseases.
The research so generously supported by The Aftershock’s donors will look at improving the diagnosis and management of brain tumours through the use of novel artificial intelligence, to visualise the future growth patterns of brain tumours and their response to treatment on MRI. This research is crucial in the fight against cancer. Predicting growth and response to treatment is difficult, and due to the availability of significantly improved computing power, the sheer amount of data that can be processed and analysed by AI is growing exponentially, and allows AI to learn from researchers’ and clinicians’ accumulated prior experience. This pioneering approach can then be applied to other cancers.
Oesophageal cancer is a relatively rare but lethal disease. Around 1,500 Australians will be diagnosed with oesophageal cancer in 2021, with only 50% expected to live more than 12 months. This is largely because diagnosis is usually made when the disease has spread too far throughout the body to contain with either surgery, radiotherapy or chemotherapy.
For those patients who are diagnosed whilst the disease is confined to the area of the oesophagus itself, the combination of chemotherapy, radiotherapy and surgery has led to improved long-term survival. Unfortunately, whilst we have improved survival from oesophageal cancer for those who are able to have curative treatment, quality of life never returns to normal. Patients suffer ongoing swallowing difficulties, nausea, lethargy, severe food intolerance, malnutrition and lethargy. These problems are associated with psychological distress, anxiety and depression.
These problems with the function of the gut after oesophagectomy reflect the complexity of the surgery that is required to cure oesophageal cancer. Oesophagectomy involves removing a large segment of the oesophagus (gullet or swallowing tube) and then recreating a tube from either stomach or large bowel that connects the stomach to the remaining oesophagus, allowing the patient to swallow. Whilst there have been major advances in chemotherapy and radiotherapy, key aspects of our surgical techniques have evolved little over the past 70 years.
In this study our researchers will utilise a new technique of dynamic magnetic resonance imaging (MRI) in concert with high resolution nuclear scintigraphy to help them understand two important questions that we hope will allow us to modify our surgical technique so that we not only cure patients, but give them the quality of life they deserve.
Firstly, they will evaluate how contraction and emptying of the reconstructed oesophagus evolves and changes over time. This will be done by performing analysis at different time points following oesophageal reconstruction. Historically few patients lived beyond 5 years after the diagnosis of oesophageal cancer, and therefore, this question has never been looked at in detail before. Given the majority of our patients who have an oesophagectomy now reach this important milestone, this is critically needed information.
Secondly, the team will compare how the reconstructed oesophagus functions and empties in patients who have achieved a good long term functional outcome from their gut compared to those with a poor outcome. They will seek to identify what are the key elements to gain an optimal outcome, as well as avoid a poor outcome.
By understanding how the reconstructed oesophagus changes over time, as well as the anatomical and physiological differences in patients that have a good quality of life and a poorer quality of life we have the opportunity to change the design of these procedures. These data will also enable us to design objective tests that can be used to better assess patients who are suffering after oesophagectomy and help us identify better treatments focused on improving their quality of life.