Development and Validation of an Interface Between the BIANCA Biophysical Model and Geant4 for Particle Therapy

<b>Objectives</b>: The main aim of this study consists of testing the consistency and reliability of the BIANCA (BIophysical ANalysis of Cell death and chromosome Aberrations) biophysical model across different radiation transport codes in the framework of cancer ion-therapy research. <b>Methods</b>: Spread-Out Bragg Peak (SOBP) profiles for protons, helium ions and carbon ions were simulated at three different depth ranges (2-3 cm, 5-8 cm, and 10-15 cm) applying two radiation transport codes, FLUKA and Geant4. While BIANCA has been interfaced to FLUKA in a previous work, an interface with Geant4 was purposely developed in this work. Cell survival along all considered SOBP profiles was predicted by BIANCA for two cell lines with very different radiosensitivities: Squamous Cell Carcinoma (SCC), with α/β = 12.68 Gy, and chordoma, with α/β = 2.37 Gy. The agreement between the predictions obtained from the two approaches was quantitatively evaluated by means of Root Mean Square Error (RMSE) and Gamma Index analysis, both for physical dose distributions and for cell survival predictions. <b>Results</b>: The comparison between FLUKA and Geant4 simulations demonstrated good agreement. The Gamma Index analysis yielded passing rates exceeding 94.9% for physical dose profiles (criteria: 3%/2 mm) and 96.0% for cell survival probabilities (criteria: 2%/2 mm) across all considered ion species (protons, He, C) and depths. Root Mean Square Error (RMSE) analysis confirmed average discrepancies below 2.5% for physical dose and 1% for biological survival. <b>Conclusions</b>: This study shows that the BIANCA model can be applied to predict cell killing along hadron therapy beams when interfaced both with FLUKA and with Geant4. Furthermore, the successful implementation of the interface with Geant4 expands the accessibility and applicability of BIANCA, paving the way for its future integration into different transport codes and/or treatment planning systems.