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Lung cancer study aims to improve treatment efficiency through unique medical imaging framework

Torso image

Researchers are developing a unique medical image processing framework aimed at helping oncologists treat lung cancer tumours more effectively.

Lung cancer is the third most common cancer type in the UK, with around 130 new cases diagnosed daily.

In most cases, treatment decisions are made based on the patient’s clinical history and visual information from medical scans such as CT (Computed Tomography) and PET (Positron Emission Tomography).

Cancerous tissue

A CT scan gives information on tissue density, while a PET scan uses special radioactive tracers to help doctors identify areas of high metabolic activity in the body. These visual representations of the cancer only offer partial information about the disease, and the only way to confirm these findings for sure is by comparing the scans to the actual cancerous tissue.

 A four-year study carried out by researchers at the University of Strathclyde, in partnership with NHS Greater Glasgow and Clyde, has developed a medical image processing framework to match up these different sources of information for the clinicians.

Funded by the Engineering and Physical Sciences Research Council’s Centre for Doctoral Training in Applied Photonics and the Beatson West of Scotland Cancer Centre in partnership with the Beatson Cancer Charity, the retrospective study used resected tissue from nine lung cancer patients who had been treated using radical surgery.

Dr Gabriel Reines March, doctoral graduate from Strathclyde’s Centre for Signal and Image Processing, said: “In this project we’ve developed a robust framework for registering pre-operative scans from lung cancer patients with images of the actual cancer specimen.

By matching these sources of data, researchers can investigate which features in the scans relate to which specific traits of the tumour. A unique aspect of this study is that every step in the framework, from tissue dissection to validation of the results, has been developed by a multi-disciplinary team of engineers and clinicians.

"This synergy was facilitated by NHS Greater Glasgow and Clyde’s Medical Devices Unit, a specialist clinical engineering team responsible for medical device innovation projects across the health board.

“This has resulted in a translational project targeted at solving an unmet need within the NHS.”

Information match

The alignment allows clinicians to spatially match the information seen on the pre-operative PET/CT scans and the physical tumour, and gain better understanding of the disease from the various sources of data.

Tumours can often be surrounded by inflammation, which is not cancer, but will show a similar response to a cancerous region on a PET scan.

Man at computer

Dr Reines March added: “If an area of inflammation is treated as a tumour, it will be bombarded with high energy radiation, causing unnecessary damage to healthy tissue.”

The framework will shed light on how particular information on the scan is related to the pathology of the tumour and its surroundings, which could result in an improvement of treatment effectiveness in the future.

The doctoral researcher added: “Knowing about detailed tumour structure is very important for choosing the right type of treatment for each individual.”

The project results were reviewed by two independent clinicians. Initially, they were asked how they would have proceeded if they didn’t have the algorithms to refer to, with their manual alignments used as the baseline.

The second phase saw the same clinicians presented with four different anonymous results, including the study method, their own, a colleague’s, and a non-expert. In two out of three cases analysed, the clinicians blindly picked the algorithm as providing the best solution.

Dr Reines March, who has now taken up an engineering post with the University of Glasgow, added: “This means our method performed better than their own expert results, which is very encouraging.”

Precise information

Clinical trials are now set to follow, which will use another type of PET scan to give more precise information of the metabolic fingerprint of the tumour.

Professor Stephen Marshall, project supervisor from Strathclyde, who is also Deputy Director of the CDT, said: “This is an excellent example of collaborative research between the University and NHS Greater Glasgow and Clyde, which has the potential to lead to significant improvements in quality of life for lung cancer sufferers.”

Dr Stephen Harrow, Consultant Clinical Oncologist at Beatson West of Scotland Cancer Centre said: “Lung cancer is a devastating disease associated with poor survival. If we can better understand the diagnostic imaging and in particular the functional imaging, then we believe that this may open up avenues to adapt and individualise treatment strategies and ultimately improve patient outcomes.”

Martin Cawley, CEO of the Beatson Cancer Charity said: “We were delighted to collaborate in this exciting initiative.  Advancements in diagnosis of cancers will ultimately lead to better targeted and specific treatments.  The results from this innovative research will certainly contribute towards this goal and Beatson Cancer Charity are thrilled to play a role.” 

The charity has recently provided additional funding for the clinical trials.