May 2021: Study to investigate how AI could aid early detection of pancreatic cancer

The study team (led by Edge Hill University) has been awarded a £100,000 start-up grant from Cancer Research UK, Pancreatic Cancer UK and the Engineering and Physical Sciences Research Council (EPSRC), part of UK Research and Innovation (UKRI). 

By using data from patients who have been diagnosed with the disease, researchers will use AI to identify potential biomarkers and risk groups who are more likely to develop pancreatic cancer in the future.

According to Cancer Research UK, there are around 10,300 new pancreatic cancer cases in the UK every year, with around eight in 10 cases being diagnosed at a late stage in England and Scotland.

Senior Imaging Scientist, Dr Balaji Ganeshan and his team at University College London will be working to develop a method to extract features (omics) from routinely acquired radiology scans (e.g.CT and MRI scans).

Dr Balaji said: "Radiology scans contain 'textures' which are imperceptible to the naked eye of a radiologist but reflect heterogeneity (complexity) within the tissue/cancer, which is a key feature of malignancy. This kind of information is otherwise obtained from invasive, complicated and expensive procedures such as biopsy and genetic analysis."

"Inclusion of these key biologically intuitive and objective metrics, will provide important signatures potentially identifying individuals at higher risk for pancreatic cancer. This will make the final AI computer architecture (algorithm/model) that much more clinically relevant, robust and intuitive unravelling the 'black-box' (unknown) approach of traditional AI algorithms, which face criticism within the clinical and scientific communities, thereby creating barriers to the adoption of AI in routine clinical practice."

Dr Ardhendu Behera (Reader in Computer Vision & AI at Edge Hill University), said: “Pancreatic cancer progresses very rapidly and because no method of early detection has been discovered, it is one of the most dangerous types of cancer. Symptoms are usually very vague and do not appear until the cancer is in its later stages, at which point it is sadly too late to treat effectively in most cases.

“This is a data-driven approach that aims to find out whether it is possible to use AI to signal that there are links between risk groups and those who have already been diagnosed. Using routinely collected data such as CT/MRI, health conditions, pathology, and blood tests, the AI can identify the possible predictors of pancreatic cancer and will screen out people at high-risk. The potential of AI is incredible, and in this instance could help to save and extend the lives of patients.”

March 2021: INM x HeartFlow FFR.

The institute is responsible for the provision of cardiac CT angiography scanning for University Colllege London Hospitals NHS Trust and has recently implemented a brand new collaboration with HeartFlow allowing for brand new quantitative information to be drawn from the scans undertaken.

HeartFlow’s non-invasive personalized cardiac test provides unprecedented visualization of each patient’s coronary arteries, enabling physicians to create more effective treatment plans for their patients.

The collaboration was a great success for the department with Irfan Kayani and John Hoath working together with Sandra John-Childs, Vishal Prithipail, Oswald Charakupa and Emma Tran at HeartFlow.