May 21, 2024

Zenith Tranquil

Information treatments and health conditions

AI utilised to help prevent lung cancer patients getting heart disease

3 min read

The world’s first study to prevent around 1,000 people a year from developing heart disease caused by lung cancer radiotherapy has started on the NHS.

Specialist cancer treatment centre, the Christie Foundation Trust in Manchester, is trialling a way to spare the top of the heart during radiotherapy by using artificial intelligence (AI) to precisely and quickly map out which area to target.

Radiotherapy is a common treatment for lung cancer and one of the most effective available, but while it can kill tumours, it can also cause life-threatening damage to other organs.

Currently around 15 per cent of people who survive lung cancer go on to develop heart disease.

The doctors behind the study hope it will “pave the way for a new standard of care for lung cancer patients”.

The high energy X-rays are delivered externally by a machine almost daily and for several weeks at a time, and can cause severe side effects.

Experts have linked radiation of the chest to an increased risk of heart disease and death for a number of years.

Researchers are now determined to ensure that patients aren’t cured of lung cancer at the cost of other organs.

Lung cancer is the deadliest cancer in the UK, with 35,000 people dying and 48,000 people diagnosed each year.

Develop a cardiac disease

15 per cent of survivors go on to develop a cardiac disease caused by the radiotherapy, which is likely to be fatal.

Only around 10,000 of 24,000 patients receiving radiotherapy will be cured of lung cancer – but of those that survive, 1,500 could be at risk of heart conditions.

The NHS study will look at 2,000 patients over four years using an “opt out” approach so that patients are automatically enrolled.

Known as RAPID-RT, the study has been seven years in the making and will use AI to map out the tumour in the lung and limit the damage to other organs including the heart.

Traditionally doctors have had to draw a line around healthy organs on scans manually ahead of radiotherapy to protect healthy tissue surrounding the cancer from being exposed to radiation. This can take between 20 minutes and three hours for each patient.

The use of AI will significantly speed up this process, allowing more patients to be treated.

All lung cancer patients where radiotherapy is appropriate will be eligible to take part, as long as the cancer hasn’t spread to other parts of the body.

It is expected around 50 people per month will be involved.

The research is being funded by a £2.3 million grant from the National Institute for Health and Care Research.

‘Reduce the serious side effects’

Corinne Faivre-Finn, a professor of thoracic radiation oncology at the University of Manchester, said: “We need to reduce the serious side effects of treatment for cancer survivors.

“The real-world data from this large number of patients allows us to learn very quickly, be more agile in altering the dose, and improve results far faster than we would be able to do with a traditional trial design.”

She said the study could “pave the way for a new standard of care for lung cancer patients” and that using AI was “vital” to speed up the processes involved.

Alan Featherstone, 71, a great-grandfather from Wigan, is set to be one of the first to take part after being diagnosed with lung cancer in March.

After being diagnosed with a tumour in each lung, and having chemotherapy, he has just started a six-week course of radiotherapy.

He said: “I believe if you’re offered the chance to be on a trial you take it. It’s not about me. Without research we wouldn’t have the advances in cancer care.”

Betty Mullen, 70, also from Wigan, was diagnosed with stage three lung cancer three months ago. She opted to take part in the study after speaking to doctors.

“It was important to treat the cancer as soon as possible, so we felt radiotherapy was a better option than surgery,” she said. “You just have to crack on with it don’t you?”

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