AI – Oncology’s new secret weapon

The lack of an effective early diagnosis tool and the challenge of staging (i.e. measuring the size) of Malignant Pleural Mesothelioma (MPM) prompted a proposal from Canon Medical Research Europe and the Glasgow Pleural Disease Unit to the Scottish Cancer Innovation Challenge in mid-2018.

Using phase one funding, the study team tested the feasibility of a method to automatically identify MPM tumours and their boundaries on CT images (a process known as ‘image segmentation’). Subsequent phase two funding has allowed development of a prototype algorithm that uses a trained Artificial Intelligence (AI) system to achieve this. This development paves the way for an AI system that could greatly improve the efficiency of clinical trials and the accuracy and reliability of measurements of response to treatments in the clinic.

Dr Kevin Blyth, Honorary Clinical Associate Professor at the University of Glasgow and Chief Investigator of the study, said:
“We are collaborating with Canon Medical Research Europe, who have considerable expertise in use of AI for medical imaging via the Cancer Innovation Challenge. This fantastic initiative facilitates closer integration between industry partners and clinical researchers.

“Automatic RECIST (Response Evaluation Criteria in Solid Tumours) reporting is a scoring system applied to CT scans to describe a patient’s response to cancer treatment but is difficult to use in mesothelioma, because of the complex shape of mesothelioma tumours. A carefully trained, and properly optimised AI algorithm could theoretically locate a mesothelioma on a CT scan and measure its volume, allowing comparison with previous measurements and making clinical trials less expensive. Development of this system involves a training process in which a human must ‘draw around’ all areas of mesothelioma on each CT scan to show the AI what this looks like. In phase one we learnt this process (known as ‘ground truth generation’) needed to be done by an expert mesothelioma clinician, with experience of mesothelioma images and the anatomy of the chest, since it proved very difficult for an imaging technician.

“This training and AI development process is going well, and we hope to be able to announce our results in the autumn of this year. If we are successful at this stage, we will be ready to test our trained AI algorithm in larger numbers of CT scans, bring us closer to deployment of AI RECIST in future trials and clinical practice.”

For more information on the Cancer Innovation Challenge visit

Introducing the new Health Companion portal

Working in collaboration with DaSH-Global, a pharmaceutical manufacturing company, we have developed a new digital patient portal known as the ‘Health Companion’. The new system will allow patients to submit data regarding their quality of life and experiences in the...

Join our Asbestos Commercial Club

If you are a business involved in the management of asbestos or the diseases it causes, why not join our Asbestos Commercial Club (MUKACC) to support the vital work that we do? Joining MUKACC can be a great morale booster for your staff, encouraging them to get...

CEO Liz Darlison to speak at the European Asbestos Conference

Mesothelioma UK’s CEO, Liz Darlison, has been confirmed as a speaker at the European Asbestos Forum Conference (EAF). The event will take place from 10-11 November in Amsterdam, in the Netherlands, where she will deliver a talk entitled, Establishing a National...

Mesothelioma National Statistics

The Health and Safety Executive has been publishing statistics on annual mesothelioma deaths in Great Britain on a consistent basis for 50 years. Detailed statistical tables and commentary are available as part of HSE’s National Statistics web pages here. The data...