ESTRO 2025 - Abstract Book

S3884

Radiobiology - Immuno-radiobiology

ESTRO 2025

3669

Digital Poster Predicting lymphocyte count for VMAT and IMPT treatments with a dynamic lymphocyte flow model for locally advanced cervical cancer Sander C Kuipers 1,2 , Marianne M van Tuyll van Serooskerken 3 , Danny Lathouwers 3 , Anouk Corbeau 4 , Stephanie M de Boer 4 , Remi A Nout 1 , Mischa S Hoogeman 1,2 , Jérémy Godart 1,2 1 Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, Netherlands. 2 Department of Medical Physics & Informatics, HollandPTC, Delft, Netherlands. 3 Department of Radiation Science & Technology, Delft University of Technology, Delft, Netherlands. 4 Department of Radiation Oncology, Leiden University Medical Center, Leiden, Netherlands Purpose/Objective: Radiation-induced lymphopenia is associated with poorer prognosis for overall survival for solid tumors. For locally advanced cervical cancer (LACC), recent efforts are made to spare lymphoid organs in the treatment planning, for example sparing bone marrow with IMPT. However, it is not clear if this sparing accounts for the dynamic character of the immune system. We created a dynamic flow model that predicts the relative lymphocyte count (RLC) compared to baseline during and after radiotherapy treatment. With this dynamic model, we aim to compare the impact of the treatment modalities VMAT and IMPT on the RLC for women with LACC. Material/Methods: A dynamic lymphatic flow model was developed to simulate the migration of lymphocytes between seven compartments. A schematic representation of the model is shown in Figure 1. The lymphatic flow in the blood compartment was simulated with the HEDOS model [1]. Biological cell death, lymphocyte production, and radiation induced cell death, modeled with a linear survival model, were integrated in the model. Input variables were based on literature data. The lymphatic-flow model was applied to 19 LACC patients. For each of the 19 LACC patients, VMAT and IMPT treatment plans were created, with dose-volume histograms (DVHs) generated for each compartment. The model calculated radiation dose to lymphocytes using these DVHs to estimate radiation-induced cell death over time. The primary outcomes of the model included the relative lymphocyte count (RLC) over time and the RLC nadir in both the blood and total body. Results: IMPT demonstrated lower doses to lymphocytes and higher RLC nadir than VMAT for all 19 patients. The mean (min – max) RLC nadir in the patient was 65.9% (61.2% – 69.9%) for VMAT and 73.0% (67.5% – 79.7%) for IMPT. The RLC nadir in the blood was 37.4% (32.7% – 43.6%) for VMAT and 51.1% (44.1% – 63.3%) for IMPT. The RLC in the blood and in the patient are shown in Figure 2 for both treatment modalities. Conclusion: We modelled the lymphatic flow, which predicts the lymphocyte count during and after EBRT relative to baseline. With this model we showed the sparing effect IMPT has on the lymphocytes compared to VMAT. The sparing effect was especially present in the blood as the lymphocyte count of the total body is less affected by the change in treatment modality. Future research will involve tuning and validation of the model with in-vivo measurements and altering the model to be applied to other treatment areas.