AI can predict whether adult patients with brain cancer will survive more than eight months after receiving radiotherapy treatment, new research from King’s College London (KCL) has found.
The use of the AI to successfully predict patient outcomes would enable clinicians to be better informed for planning the next stage of treatment and refer patients to potentially life-saving treatment quicker.
This is the first use of AI to predict short-term and long-term survivors within eight-months of receiving radiotherapy.
Dr Thomas Booth is Reader in Neuroimaging at KCL and a Neurology Consultant at King’s College Hospital NHS Foundation Trust.
He said: “This study was motivated by a clinically-attuned and critical research question regarding aggressive brain tumours, and delivered by leveraging cutting edge artificial intelligence.
“Whilst less common than other cancers, the devastation is disproportionate with a two-year survival rate of 18 per cent.”
The paper published recently in Neuro-Oncology shows how KCL researchers created a deep learning model to allow them to more reliably and accurately predict outcomes for patients with adult primary brain cancer.
Glioblastoma is a difficult to treat cancer, with just one in four patients surviving more than one year after diagnosis.
The researchers applied deep learning to predict whether glioblastoma patients would survive the eight months after receiving radiotherapy.
Eight months is typically the time it takes to complete a typical course of routine chemotherapy that usually follows radiotherapy.
Currently, patients are regularly and routinely scanned to see if the treatment is working.
However, this means that some patients have ineffective chemotherapy which wouldn’t save their life and suffer through harmful side effects.
Instead, by giving an instantaneous and accurate prediction from one routine MRI scan, the AI enables doctors to identify patients who would not benefit from chemotherapy to try a different treatment or start an experimental treatment in a clinical trial.
Alysha Chelliah is a PhD researcher from KCL.
The researcher said: “The AI model showed improved performances when first trained to detect abnormalities on 10,000s of brain MRIs.
“This approach is intended to improve the ability to identify patients who require early second-line treatment or clinical trial enrolment, compared to those showing initial treatment response.”
Dr Booth said: “Instead of trying to grapple with interpreting each and every non-specific follow-up brain scan, we simply looked at one routine scan after radiotherapy and gave an accurate prediction using artificial intelligence to answer a simple question: which patients will not survive the next 8 months?
“The AI was able to give us an immediate and accurate prediction which means clinicians can empower patients to make choices about their treatment.
“We would be delighted if the cancer research community now uses our artificial intelligence tool to see improved outcomes for patients who won’t benefit from the usual course of chemotherapy.”
Commenting on how the work of Dr Booth and his team at KCL supported people-first brain tumour research as advocated for by the charity brainstrust, Dr Helen Bulbeck, Director of Services and Policy at brainstrust, said:
“This is exciting and fundamental research for people living with a glioblastoma, for two reasons.
“At its simplest level it demonstrates how AI can be used for patient benefit.
“More importantly however, it empowers patients and their caregivers to make choices about the clinical pathway and gives control back at a time when so much control has been lost.
“Patients will be able to make informed decisions about treatment choices and will be able to plan how they want to spend the time they have left so that they can live their best possible day, every day.”
Dr Michele Afif is CEO at The Brain Tumour Charity.
She added: “The use of AI to evaluate and predict response to radiotherapy at a much earlier point in a patient’s treatment for glioblastoma is a hugely important step in tackling this notoriously difficult to treat disease.
“At The Brain Tumour Charity, we welcome this important advance which could lead to more informed discussions at an early enough point in a patient’s treatment to consider meaningful alternatives, such as clinical trials.
“We look forward to seeing how this exciting research progresses as it is validated for wider use as a tool to improve care for those diagnosed with a brain tumour.”
