Body composition changes visible on routine CT scans may help identify individuals at risk for pancreatic cancer, according to a new Mayo Clinic study. The research, published in Pancreatology, found that patients who later developed pancreatic ductal adenocarcinoma (PDAC) showed measurable declines in visceral and subcutaneous fat over three years before diagnosis, differing from similar individuals without cancer. This approach could expand early detection beyond current high-risk groups, addressing the challenge that most pancreatic cancers occur in people without genetic predisposition or family history.
Study Methodology and Key Findings
The study analyzed abdominal CT scans from 1,825 PDAC patients and 3,650 matched controls across Mayo Clinic sites in Arizona, Florida, and Minnesota. Researchers used an artificial intelligence-based tool to measure changes in skeletal muscle, subcutaneous fat, and visceral fat over time. Compared to controls, PDAC patients exhibited significantly steeper declines in both fat types during the three years preceding diagnosis, with muscle mass differences most pronounced in the final 12 months.
“Pancreatic cancer often develops silently, making early detection extremely challenging,” states Yan Bi, M.D., Ph.D., a Mayo Clinic gastroenterologist and senior author. “These findings suggest that routine CT scans may capture physiological changes associated with pancreatic cancer before patients are diagnosed.”
Implications for Early Detection
The body composition measures showed moderate ability to distinguish future PDAC patients from controls, indicating potential value for risk assessment strategies. Michael Wallace, M.D., another Mayo Clinic gastroenterologist and corresponding author, notes this is the largest controlled study of prediagnostic body composition trajectories in pancreatic cancer. “Our study shows that body composition changes associated with pancreatic cancer are detectable on routine CT scans and differ from the changes observed in similar patients without cancer,” he says.
By leveraging routinely acquired imaging data, this approach offers a scalable method to address the urgent need for pancreatic cancer early detection. The researchers are working on developing algorithms that incorporate body composition measures along with other routinely collected clinical factors and imaging biomarkers to identify patients at increased risk. For a complete list of authors, disclosures and COI information, see the study.