
Body Composition Changes on CT Scans May Help Identify Pancreatic Cancer Risk
Patients with pancreatic cancer experience measurable changes in body composition years before diagnosis that differ from those seen in similar individuals without cancer.
People who develop pancreatic cancer experience measurable changes in body composition years before diagnosis that differ from those seen in similar individuals without cancer, according to a
Pancreatic cancer remains one of the deadliest cancers, largely because most patients are diagnosed after the disease has already spread. Current surveillance programs focus primarily on people with inherited genetic risk or strong family histories, yet most pancreatic cancers occur outside those high-risk groups.
Researchers found that patients who developed pancreatic ductal adenocarcinoma (PDAC), the most common type of
The study analyzed abdominal CT scans from 1,825 patients with pancreatic ductal adenocarcinoma and 3,650 matched controls from Mayo Clinic sites in Arizona, Florida and Minnesota. Using an artificial intelligence-based body composition tool, researchers measured changes in skeletal muscle, subcutaneous fat and visceral fat over time.
"Pancreatic cancer often develops silently, making early detection extremely challenging," says
Compared with controls, patients who developed pancreatic cancer experienced significantly steeper declines in both subcutaneous and visceral fat during the three years before diagnosis. Differences in muscle mass were most apparent during the final 12 months before diagnosis.
"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," says
Building Toward Earlier Pancreatic Cancer Risk Detection
Researchers also evaluated whether longitudinal changes in muscle and fat measurements could distinguish patients who later developed pancreatic cancer from matched controls. The body composition measures demonstrated moderate discriminatory ability, suggesting they may provide additional information for future risk assessment strategies.
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.
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