Modeling the impact of intercellular signaling on dose metrics and therapeutic outcomes in spatially fractionated radiation therapy (SFRT) for lung cancer.

Spatially fractionated radiation therapy (SFRT) delivers heterogeneous dose distributions to enhance tumor control while reducing normal tissue toxicity. Since conventional models like the linear-quadratic (LQ) model overlook intercellular signaling, a key factor in non-uniform fields, this study uses an advanced mathematical model to assess its impact on SFRT plan evaluation. A volumetric-modulated arc therapy (VMAT)-based SFRT framework was developed, resulting in two treatment plans: VMAT-GRID and 3D lattice radiation therapy (3D-LRT). A kinetic model incorporating both direct radiation damage and intercellular signaling was implemented to simulate signal dynamics, DNA damage, and calculate the survival ratio across 3D voxelized volumes. Key dosimetric and biological indices, including mean dose, equivalent uniform dose (EUD), valley-to-peak dose ratio (VPDR), therapeutic ratio (TR), and normal tissue complication probability (NTCP), were computed using both physical and biological doses. Incorporating intercellular signaling led to increased EUD, mean dose, VPDR, and NTCP, particularly in 3D-LRT plans with steeper dose gradients. Additionally, signaling effects caused extra biological damage in non-irradiated cells within low-dose regions, which resulted in a decreased TR. This study highlights that accounting for radiation-induced signaling alters the evaluation of SFRT plans compared to models considering only direct radiation effects. Therefore, to achieve accurate assessment, particularly in complex techniques like 3D-LRT, it is advisable to employ models capable of capturing both direct and indirect radiation responses. Additionally, experimental validation is a crucial step toward translating this model into clinical practice.