An AI model spotted pancreatic cancer abnormalities on CT scans up to three years before diagnosis and is now being tested in a clinical trial.
The scientists behind the model trained it by feeding it CT scans from patients who had been screened for other medical conditions and were later diagnosed with pancreatic cancer.
The team then had radiologists review the scans and compared their ability to find early signs of cancer with that of the AI model. The model was found to be three times better at identifying the early signs.
Dr Ajit Goenka is a radiologist at the Mayo Clinic and an author of the study.
The researcher said: “We knew, based on the biology of the disease, that this is not something which is coming all of a sudden in three months.
“We knew that the signal was there. We just needed to find a way to be able to detect it.”
With a five-year survival rate of 13 per cent, pancreatic cancer is on track to become the second leading cause of cancer deaths by 2030.
Around 80 per cent of patients are diagnosed after the disease has reached an advanced stage.
Unlike colon or breast cancer, there is no routine screening for pancreatic cancer in healthy people. Feeling for a lump is nearly impossible, since the pancreas is buried deep in the abdomen.
Typical symptoms such as stomach pain and sudden weight loss usually do not begin until the cancer has spread to other organs.
Early markers of the disease are often too subtle to be seen by the human eye on a scan. In many cases, patients’ scans appear normal as little as six months before they are diagnosed.
“I analyse these images every day,” said Dr Daniel Jeong, a diagnostic radiologist at Moffitt Cancer Center in Tampa, Florida, who was not involved in the Mayo Clinic research
. “We’re really looking for a measurable mass that could represent the cancer. So these tumours need to grow to a certain level to become visible.”
Goenka said one signature of early cancer that the AI model was able to detect is abnormal cells in the pancreas that shelter and protect cancer from the body’s immune defences.
Scientists have known such cells exist but have struggled to find them on scans.
Goenka said the model could someday be useful for people who already have risk factors for the disease, such as a family history or diabetes, but do not have any symptoms.
From there, doctors would likely recommend additional blood work and imaging.
“Unfortunately, if they have symptoms and if it’s truly pancreas cancer, you don’t need AI for that,” he said.
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