Professor Kevin Brindle joins Ellie Wolmark to discuss his life's work in imaging research as he reaches retirement. Kevin is particularly interested in metabolic imaging. His research group has developed novel magnetic resonance-based molecular imaging techniques to detect the early responses of tumours to therapy, with a view to translating these into clinical application. He talks about how he got into this topic in the first place, his amazing contributions to the field over the past four decades, and about how his techniques can be translated into the clinic to impact patient treatment.

Kevin is Emeritus Professor of Biomedical Magnetic Resonance in the Department of Biochemistry and a Senior Group Leader in the CRUK Cambridge Institute at the University of Cambridge, UK. He is also a Fellow of the Academy of Medical Sciences and of the Royal Society.

Integrated Cancer Medicine: Research in Focus

Kevin Brindle – Reflections on a lifetime in imaging research

How is artificial intelligence being used in cancer care, and what do patients think about it?

In this 'Ask Me Anything' episode, Ellie Wolmark, Programme Manager for Integrated Cancer Medicine (ICM) at the CRUK Cambridge Centre, speaks with patient representatives Lorraine, Frankie, and Ann from across our Patient and Public Involvement groups, alongside ICM researchers Professor James Brenton, Dr Ines Machado, and Dr Gabriel Funingana from the University of Cambridge.

Together, they explore how artificial intelligence (AI) is being applied in cancer research, how it could support personalised treatment, and what the future might hold. The patients share thoughtful questions and concerns about the role of AI in healthcare, while the researchers explain how it's currently being used and what challenges remain.

This lively and insightful discussion highlights just how valuable patient involvement is in shaping research that truly meets the needs of those it aims to help.

Ask me anything about cancer

Ask me anything about... the use of artificial intelligence in healthcare

Why does eating more not fix the severe weight loss seen in some cancer patients, and what can be done about it?

In this 'Ask Me Anything' episode, Dr Hui-Ling Ou, Programme Manager for the Pancreatic Cancer and Cancer Immunology Programmes at the CRUK Cambridge Centre, speaks with researchers from the Cancer Cachexia Action Network (CANCAN): Dr Claire Connell (University of Cambridge and Cambridge University Hospitals NHS Foundation Trust), Dr David Lewis (CRUK Scotland Institute), and Dr Tobias Janowitz (Cold Spring Harbor Laboratory).

Together, they unpack what cancer-associated cachexia is, why it's so devastating for patients, and how scientists are working to understand and reverse this syndrome. The guests share how their research, spanning metabolism, imaging, immunology, and clinical studies, is bringing fresh insights and hope to a problem that affects quality of life for so many.

This thought-provoking discussion shines a light on the collaborative efforts driving progress against one of cancer's most challenging complications.

Ask me anything about... the science of cancer-associated cachexia

What do you most want to know about pancreatic cancer and cancer-associated cachexia?

In this special episode, we bring you a recording of a live 'Ask Me Anything (AMA)' event hosted by the CRUK Cambridge Centre Pancreatic Cancer Programme for World Pancreatic Cancer Day 2024.

A multidisciplinary and international panel of experts, including clinicians, researchers, nurses, dietitians and physiotherapists, answer thoughtful questions from the public about pancreatic cancer, cachexia and the latest research and care approaches. Topics range from understanding the biology of these diseases to managing symptoms and improving quality of life.

The discussion sheds light on the progress being made and the ongoing challenges in improving outcomes for people affected by these conditions.

Ask me anything about... cachexia research and management

How can artificial intelligence (AI) support both cancer research and healthcare more generally? Anoushka Harit (University of Cambridge) and Dr Zhongtian Sun (University of Kent) join today's episode to discuss this topic.

Anoushka talks about her research in hereditary diffuse gastric cancer (HDGC) and the development of an AI system to enable early detection of signet ring cell carcinoma (SRCC) during endoscopy. This new AI system could help to treat SRCC better or to prevent or delay drastic life-changing treatment, preserving patients' quality of life.

Zhongtian shares insights on how AI can support health applications more generally and how he tries to make it as explainable as possible. He even talks about his wish to make the AI mimic as much as possible the way a human brain works!

Using AI to detect stomach cancer during endoscopy

Have you ever wondered how artificial intelligence (AI) is used in research in a healthcare setting? Rebecca Wray and Bill McGough, two PhD students at the University of Cambridge, both use AI in different ways in their research into the screening and treatment of kidney cancer.

Rebecca is an MRes PhD student investigating the response and resistance to therapy in patients with kidney cancer. She uses AI to find tumour features at multiple scales. For his PhD, Bill is developing AI models that will sift through the mounds of imaging data produced during the Yorkshire Kidney Screening Trial (funded by Yorkshire Cancer Research), flagging images that show masses in the kidneys.

This interesting conversation gives insight into how researchers are using patient data safely in order for AI models to integrate all the information about a patient to help review their treatment and personalise it. The discussion also highlights how using AI in the screening setting is speeding up processes to help save clinicians' time and allowing the potential earlier detection of kidney cancer in a cost-effective manner.

Using AI in the screening and treatment of kidney cancer

What if a time machine could be built, not from metal but from human tissue, to help us understand cancer and how it responds to treatment?

Dr Alecia-Jane Twigger, Dr Akanksha Anand, Dr Kui Hua, Dr Pedro Victori and Dr Jo Worley from the University of Cambridge have done just that. In this episode, they talk about their project funded by Wellcome LEAP under the Delta Tissue programme to build a 'tissue time machine'. By studying tumour samples from patients with triple negative breast cancer before and after treatment, they aim to build a model that can predict how patients would respond to therapy.

The conversation offers a fascinating look at how a truly multidisciplinary team, bringing together scientists from very different fields, can achieve something remarkable.

Building a tissue time machine

Could the environment around a cancer tumour hold the key to better treatments?

In this episode, PhD students Emily Lythgoe and Ellie Bunce from the University of Cambridge discuss their research into tumour microenvironments. They explain why studying these environments in ovarian cancer (in a clinical setting) and head and neck cancer (in a pre-clinical setting) is so important for predicting how tumours might respond to treatment. They also highlight the value of integrating multiple technologies to create a more complete picture of a patient and their disease.

This insightful conversation explores how their work helps to understand the building blocks of these cancers and why such complex research could be crucial for developing new ways to treat patients in the future.

Studying the tumour microenvironment

Can we use artificial intelligence (AI) to predict where a brain tumour might recur at the point of first diagnosis in order to pre-emptively treat it to stop recurrence?
 
Dr Francesca Cozzi (a PhD student at the University of Cambridge) and Dr Curtis Holliman (Associate Professor in the Mathematics Department at The Catholic University of America, USA) believe this will eventually be possible.
 
In this exciting conversation they talk about their collaboration to find a mechanism to mathematically model the progression of glioblastoma. They highlight why it is important to achieve this in an explainable way using AI, to keep the process of decision making transparent and interpretable to self-validate the models they develop.

Using AI to mathematically model the progression of glioblastoma

Is a tumour's ability to evolve and adapt over time linked to why it becomes resistant to radiotherapy? And if so, what can we do to overcome this radioresistance?

In this episode, Dr Christopher Jones and Dr Ashley Nicholls from CRUK RadNet Cambridge at the University of Cambridge explore these questions. They explain why some tumours are resistant to radiation and why some patients are more resistant to treatment than others. They also offer insights into why recurrence happens and how to identify it early in order to treat it more effectively with new technologies.

This includes designing new tools to make drug delivery more accurate and new genetic approaches to investigate specific ways to treat cancer in the context of radiation. Chris works predominantly in oesophageal cancer, while Ash studies lung cancer, but both strive to understand why relapse and radioresistance occur to then try to target these cancers with specific drugs or drug combinations to lessen toxicity and help personalise treatment.

The association between radioresistance and tumour evolution

The Cancer Research UK Cambridge Centre unites over 1,000 world-leading biologists, chemists, physicists, engineers, mathematicians, computer scientists, clinicians, nurses and allied healthcare professionals from across Cambridge, UK to tackle cancer from every angle.

Our mission is to end death and disease caused by cancer through research, treatment and education. We are detecting cancer at its earliest stage and are developing personalised treatments for every patient through facilitating new collaborations and driving the translation of new scientific discoveries into clinical applications to improve patient care. By working together across a range of different disciplines, our members are breaking down the barriers between the laboratory and the clinic, enabling patients to benefit from the latest innovations in cancer science.

New tracks tagged #Cancer Research UK