Tumor control probability in large sacral chordomas treated with carbon ions radiotherapy integrating advanced microstructural modelling

Purpose: To integrate patient-specific cell count data from diffusion-weighted MRI (DWI) into the linear-quadratic (LQ) Poisson tumor control probability (TCP) model for sacral chordomas (SC) treated with carbon ion radiotherapy (CIRT), aiming to improve local control (LC) and local relapse (LR) prediction. Materials and Methods: We considered data from 37 of the first 50 SC patients consecutively treated at the National Centre for Oncological Hadrontherapy (CNAO, Pavia, Italy). LQ Poisson formalism was revised to integrate either a linear (TCPLIN) or logarithmic (TCPLOG) dependence on clonogenic cell count, derived from baseline DWI through an optimal match with in-silico simulations. The models were compared with the case of a uniform cell density of 107 cells/cm3, as widely adopted in the literature. All models were fitted on 27 patients and tested on 10 held-out cases to assess the performance, both in terms of area under the receiver-operator curve (AUC) and considering the statistical differences in TCP between LR and LC. Results: In contrast to the constant cell density model, DWI-based models significantly separated the TCP of LC and LR patients, with TCPLOG describing an average TCP of 71.3 % ± 9.56 % for LC patients, compared to 48.9 % ± 9.49 % for LR test cases. AUC values of 0.92 and 0.96 were respectively achieved by TCPLIN and TCPLOG, compared to 0.88 for constant cell density, on the test set. Conclusion: DWI-based cell count data can significantly improve the performance of TCP models in predicting the probability of LC of SC treated with CIRT.