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A phase-field model for non-small cell lung cancer under the effects of immunotherapy

Andreas WagnerPirmin SchlickeMarvin Fritz ...+3 Barbara Wohlmuth
Mar 2023
摘要
Formulating tumor models that predict growth under therapy is vital forimproving patient-specific treatment plans. In this context, we present ourrecent work on simulating non-small-scale cell lung cancer (NSCLC) in a simple,deterministic setting for two different patients receiving an immunotherapeutictreatment. At its core, our model consists of a Cahn-Hilliard-based phase-field modeldescribing the evolution of proliferative and necrotic tumor cells. These arecoupled to a simplified nutrient model that drives the growth of theproliferative cells and their decay into necrotic cells. The appliedimmunotherapy decreases the proliferative cell concentration. Here, we modelthe immunotherapeutic agent concentration in the entire lung over time by anordinary differential equation (ODE). Finally, reaction terms provide acoupling between all these equations. By assuming spherical, symmetric tumorgrowth and constant nutrient inflow, we simplify this full 3D cancer simulationmodel to a reduced 1D model. We can then resort to patient data gathered from computed tomography (CT)scans over several years to calibrate our model. For the reduced 1D model, weshow that our model can qualitatively describe observations duringimmunotherapy by fitting our model parameters to existing patient data. Ourmodel covers cases in which the immunotherapy is successful and limits thetumor size, as well as cases predicting a sudden relapse, leading toexponential tumor growth. Finally, we move from the reduced model back to the full 3D cancer simulationin the lung tissue. Thereby, we show the predictive benefits a more detailedpatient-specific simulation including spatial information could yield in thefuture.
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