Nuclear Physics Seminars

Pancreatic cancer is one of the most lethal cancers with a five-year survival of 13%. Although Radiation Therapy (RT) plays a critical role in tumor control, its dual impact—stimulating anti-tumor T cell production while suppressing the immune system—presents a significant therapeutic challenge. Current national pancreatic protocols are oblivious to lymphopenia. We have analyzed a retrospective data set of 69 pancreatic non-SBRT patients. Maximum lymphocyte reduction from radiation treatment (RT) to pancreas could be as much as 78% from the pretreatment ALC value, including 81% with grade 3 lymphopenia and a nadir at day 35 following RT initiation. Currently there is no computational model to predict radiation induced immune suppression (RIIS) for pancreas that would allow the treatment team to optimize radiation therapy to minimize RIIS. To mitigate these effects, we developed a predictive algorithm for Radiation-Induced Immune Suppression (RIIS). This algorithm allows for a direct comparison of RT plans, identifying those that minimize immune suppression without compromising tumor-targeting efficacy. Additionally the impact of immune rich organ dose volumes on the overall survival could shed light on what immune rich organs, especially T cell rich should be spared and by how much. We have linked the overall survival calculations with organ specific static dose volumes to further select the impactful immune rich organ sparing. By automating the selection of constraints for immune system preservation, our approach offers a pathway to improved treatment personalization in RT clinics.