Cedars-Sinai researchers are advancing artificial intelligence (AI) technology to combat the disproportionate impact of pancreatic cancer on Black patients, a group with significantly higher rates of the disease. Building on their prior success in creating an AI-powered imaging tool to predict pancreatic cancer, the team is refining the technology to address unique risk factors specific to this population.
Understanding Disparities in Pancreatic Cancer
“Black individuals face a pancreatic cancer incidence rate that is over 50% higher than other racial groups, and their survival rates are among the lowest,” explained Dr. Debiao Li, PhD, director of the Biomedical Imaging Research Institute at Cedars-Sinai. Factors such as genetics, socioeconomic conditions, and lifestyle variations likely contribute to these disparities, and Dr. Li’s team aims to explore how these differences may affect pancreatic tissue and cancer risk.
Advancing AI for Early Detection
Supported by a National Cancer Institute grant awarded in 2022, Cedars-Sinai investigators developed an AI-driven tool that leverages computed tomography (CT) scans to detect early, microscopic changes in the pancreas. These changes, often precursors to cancer, can emerge years before clinical symptoms, potentially allowing for early intervention. The researchers recently secured additional funding to adapt this tool specifically for Black patients by investigating population-specific characteristics.
The team is partnering with the University of Illinois Chicago, led by Dr. Cemal Yazici, MD, to test the tool in a diverse demographic, ensuring the model’s effectiveness in addressing the unique needs of Black patients.
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Combining Innovations for Comprehensive Screening
Traditional models relying solely on symptoms, weight, or genetic predisposition have struggled with predictive accuracy. Meanwhile, blood and urine biomarkers for pancreatic cancer remain in development. “Integrating these emerging tests with our AI imaging tool could revolutionize early detection,” said Dr. Stephen Pandol, MD, director of Basic and Translational Pancreas Research at Cedars-Sinai.
This combined approach aligns with Cedars-Sinai Cancer’s vision of personalized oncology. “Our AI-driven precision medicine strategy complements existing advancements, such as the Molecular Twin Precision Oncology Platform, to enhance cancer prediction and treatment,” added Dr. Dan Theodorescu, MD, PhD, director of Cedars-Sinai Cancer.
The Impact of Early Detection
Pancreatic cancer remains one of the deadliest malignancies, with a five-year survival rate hovering around 10%. However, early diagnosis—when surgical options are more viable—can boost survival rates to over 50%. Unfortunately, most cases are diagnosed in advanced stages due to the lack of early symptoms.
By monitoring high-risk individuals with annual imaging, the researchers aim to detect pancreatic cancer two to three years earlier than current standards allow. “Detecting cancer even a few years earlier could mean the difference between life and death for many patients,” emphasized Dr. Li.
As Cedars-Sinai continues to refine AI applications for early detection, this work represents a critical step toward addressing racial disparities in healthcare and improving outcomes for one of the most challenging cancers.
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