Intensity Modulated Radiation Therapy Re-Planning Coupled with Radiation-Induced Immune Suppression Models Predict Improved Clinical Outcomes In Locally Advanced Non-Small Cell Lung Cancer (NSCLC) Patients
Abstract
Purpose
Evidence suggests a competing dynamic for radiation therapy (RT) and immunological response to tumors; while radiation-induced immune suppression (RIIS) inhibits immune processes, which may result in lower tumor control and survival and increase infections and hospitalizations, RT also enhances T-cell infiltration into tumors [1-3]. Recently, RIIS models for advanced stage non-small cell lung cancer (NSCLC) have accurately predicted both actual lymphocyte count (ALC) and the effects of decreased ALC on overall survival (OS) [4,5]. Within this abstract, we present RT re-planning that satisfies original plan requirements, and additionally reduces RT dose to immune-rich structures to mitigate RIIS. Predicted change in ALC and OS between original (i.e., administered) and RIIS-avoidance RT plans is reported to support hypothesis.
Methods
Data from 26 advanced-stage NSCLC patients is presented therein. Re-planned treatments met original constraints and avoided immune-rich organs, including lymph nodes (utilizing eContour [6]), heart and great vessels, thoracic spine, liver, and spleen. ALC was estimated with a novel Python-based RIIS model with RT DICOM data from patients as input and simulating the real-time coupled dynamics of lymphocyte circulation between blood and lymph-rich compartments. Predictive ALC was compared between sets of plans. Furthermore, we utilized previous work from our group on significant correlations of OS with higher LN-GTV doses V5, V10, V20 to predict the OS improvement from replans.
Results
From our initial re-planning, average non-draining lymph node V 500, 1000, 2000 volumes decreased by 24% (p=0.056), 35% (p=0.009), and 44% (p=0.004), respectively. The RIIS modeling reports a mean and max ALC improvement of 2.9% and 11.3%, respectively. The predicted average OS at 24 and 60 months after treatment increased by approximately 4.7% and 5.7%, respectively, for RIIS-avoidance plans compared to original plans.
Conclusion
Leveraging the RIIS modeling, RIIS-avoidance treatment plans can reduce RIIS, and improve ALC and OS within NSCLC patients.