A groundbreaking new test that can detect the deadliest form of cancer years before diagnosis could save thousands of lives. Researchers at Minnesota's Mayo Clinic have developed an AI-assisted test to detect pancreatic cancer up to three years before a patient receives a diagnosis.
How REDMOD Works
The AI model, called REDMOD, picks up even the most subtle tissue changes of pancreatic ductal adenocarcinoma, the most common form of pancreatic cancer. Conventional imaging and the human eye often struggle to detect these subtle changes, which can go unnoticed.
Pancreatic cancer is notorious not only for its high mortality rate but also for how swiftly it advances before patients realize anything is wrong. In its early stages, symptoms are vague and easily dismissed: a dull back ache, intermittent indigestion, unexplained fatigue, or subtle yellowing of the eyes or skin that comes and goes.
Doctors often describe it as a cancer that 'whispers' rather than shouts – and by the time it makes itself heard, it is frequently a death sentence. Around 80 percent of cases are diagnosed only after the disease has spread beyond the pancreas, at which point surgery – the only potential cure – is no longer an option.
Survival Statistics
Overall, just 12 percent of patients survive for five years after diagnosis, and the majority do not live more than a year. Each year, pancreatic cancer is diagnosed in around 67,000 Americans and kills more than 52,000. Now, researchers believe the AI-assisted technology could detect the cancer at stage 0, making it more treatable and increasing chances of survival.
Study Findings
Dr. Ajit Goenka, the study's senior author and a Mayo Clinic radiologist and nuclear medicine specialist, said: 'The greatest barrier to saving lives from pancreatic cancer has been our inability to see the disease when it is still curable. This AI can now identify the signature of cancer from a normal-appearing pancreas, and it can do so reliably over time and across diverse clinical settings.'
In the study, published in the journal Gut, REDMOD was used on hundreds of CT scans from 219 patients' abdomens that were deemed by a radiologist to show no evidence of disease. However, the patients were later diagnosed with pancreatic cancer. REDMOD detected the 'invisible' signature of pre-clinical pancreatic cancer an average of 475 days before diagnosis.
Additionally, it performed better than radiologists and was twice as sensitive – meaning it had a superior ability to pick up true positive cancer results. It correctly detected cancer in 73 percent of cases, compared to 39 percent among radiologists. REDMOD was also nearly three times as accurate as radiologists when it came to detecting cases more than two years before diagnosis – accurate in 68 percent of cases compared to 23 percent.
Future Implications
The researchers acknowledged that their patient set was not diverse and would like to expand its test subjects. They still concluded: 'This study validates REDMOD as a fully automated AI framework capable of identifying the imaging signatures of stage 0 pancreatic ductal adenocarcinoma in normal pancreas, achieving this with substantial lead times and performance superior to expert radiologists. While prospective validation is paramount to confirm clinical utility, the REDMOD framework represents a significant advance towards shifting the paradigm for sporadic [pancreatic ductal adenocarcinoma] from a late-stage symptomatic diagnosis to proactive pre-clinical interception, offering tangible hope for improving outcomes in this challenging disease.'
