Direct optimization of the probability of lesion origin in proton treatment planning for low‐grade glioma patients

Background: In proton therapy of low-grade glioma (LGG) patients, contrastenhancing brain lesions (CEBLs) on magnetic resonance imaging are considered predictive of late radiation-induced lesions. From the observation that CEBLs tend to concentrate in regions of increased dose-averaged linear energy transfer (LETd) and proximal to the ventricular system, the probability of lesion origin (POLO) model has been established as a multivariate logistic regression model for the voxel-wise probability prediction of the CEBL origin. Purpose: To date, leveraging the predictive power of the POLO model for treat- ment planning relies on hand tuning the dose and LETd distribution to minimize the resulting probability predictions. In this paper, we therefore propose automated POLO model-based treatment planning by directly integrating POLO calculation and optimization into plan optimization for LGG patients. Approach: We introduce an extension of the original POLO model including a volumetric correction factor, and a model-based optimization scheme featuring a linear reformulation of the model together with feasible optimization functions based on the predicted POLO values. The developed framework is implemented in the open-source treatment planning toolkit matRad. Results: Our framework can generate clinically acceptable treatment plans while automatically taking into account outcome predictions from the POLO model. It also supports the definition of customized POLO model-based objec- tive and constraint functions. Optimization results from a sample LGG patient show that the POLO model-based outcome predictions can be minimized under expectable shifts in dose, LETd, and POLO distributions, while sustaining target coverage (Δ₏ₓₕ D95ₑ₁₄, ₅ₗ ≈ 0. 00, Δ₆ₓₕ D95ₑ₁₄, ₅ₗ ≈ 0. 03), even when NTCP is strongly downregulated. Conclusion: POLO model-based treatment plan optimization for LGG patients can be implemented in a technically feasible way, alleviating the need to hand tune the dose and LETd distribution. Future work should address multipatient follow-up studies.