Exclusive: Tool predicts how likely tumours are to grow back in cancer patients after they have undergone treatment
An MRI scanner in an NHS mobile truck. While treatment advances in recent years have boosted survival chances, there remains a risk that cancer might come back.An MRI scanner in an NHS mobile truck. While treatment advances in recent years have boosted survival chances, there remains a risk that cancer might come back.
“This is an important step forward in being able to use AI to understand which patients are at highest risk of cancer recurrence, and to detect this relapse sooner so that re-treatment can be more effective,” said Dr Richard Lee, a consultant physician in respiratory medicine and early diagnosis at the Royal Marsden NHS Foundation Trust.
In the retrospective study, doctors, scientists and researchers developed a machine learning model to determine whether it could accurately identify non-small cell lung cancer patients at risk of recurrence following radiotherapy. Machine learning is a form of AI that enables software to automatically predict outcomes.
These included the patient’s age, gender, BMI, smoking status, the intensity of radiotherapy, and their tumour’s characteristics. Researchers then used the AI model to categorise patients into low and high risk of recurrence, how long a period they might experience before a recurrence, and overall survival two years post treatment.
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