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PEARL – Making radiotherapy more effective whilst reducing long-term side effects

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Location

Velindre Cancer Centre

Type of research

Better Treatments

Type of cancer

Head and neck

Oropharyngeal cancer is a type of head & neck cancer that affects the soft palate, tonsils and base of the tongue. It is increasingly common, particularly in young people, with rates doubling in the last 15 years. This cancer is often caused by HPV (human papillomavirus) and these cases the patients have a good prognosis, with many of them likely to be cured. 

Sadly, following the standard treatment with radiotherapy many patients suffer with debilitating side effects, which can be permanent. These can include difficulty in swallowing (or even the need to use feeding tubes), loss of taste and numbness in the mouth. These side effects are caused by the radiation damaging healthy tissues around the tumour during radiotherapy.


PEARL is a Cancer Research Wales funded clinical trial investigating the use of PET-CT scans to improve radiotherapy planning and reduce side effects for oropharyngeal cancer patients. PET-CT (Positron Emission Tomography-Computerised Tomography) scans combine two different types of scanning to allow more accurate imaging of tumours. Typically, oropharyngeal cancer patients have a PET-CT scan after their diagnosis, so that clinicians can plan their radiotherapy treatment. 

In the PEARL trial, Professor Evans’ team are conducting a second PET-CT scan halfway through the radiotherapy treatment course. The new scan allows the radiotherapy plan to be updated, accounting for the shrinkage of the tumour - this helps to ensure that healthy tissues near to the tumour are spared as much as possible. 

The aim of the trial is to assess whether this approach is feasible and whether side effects are reduced thanks to the more accurate targeting of the remaining tumour after the initial treatment.

There are also several sub-studies that will make use of the data acquired from the PEARL trial. The first of these will assess the use of a machine learning algorithm to distinguish tumour and healthy tissue on PET-CT scans. The second will investigate the use of radiomics – this involves computer analysis of PET-CT scans to detect differences that may predict how well patients respond to treatment.

Team involved

Professor Mererid Evans

Velindre Cancer Centre