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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.10174 |
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| _version_ | 1866913022476288000 |
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| author | Palkowitsch, Martina Kilian, Larissa S. Hennings, Fabian Lühr, Armin Thiem, Justus Grey, Arne Bütof, Rebecca Seidlitz, Annekatrin Troost, Esther G. C. Krause, Mechthild Löck, Steffen |
| author_facet | Palkowitsch, Martina Kilian, Larissa S. Hennings, Fabian Lühr, Armin Thiem, Justus Grey, Arne Bütof, Rebecca Seidlitz, Annekatrin Troost, Esther G. C. Krause, Mechthild Löck, Steffen |
| contents | Purpose: Recent investigations of radiation-induced contrast enhancements (RICE) in brain tumor patients after proton therapy indicated variability in proton relative biological effectiveness (RBE) and increased radiosensitivity of the periventricular region (PVR). Prior studies, however, were restricted to proton cohorts requiring assumptions on reference radiation. This study assessed proton RBE variability and PVR radiosensitivity using spatially resolved predictive modeling of RICE in a combined photon-proton cohort. Methods and Materials: Predictive models for RICE detected on follow-up magnetic resonance imaging were developed in 152 brain tumor patients treated with photons or protons. Logistic regression was applied at the voxel level to model spatial occurrence and at the patient level to model incidence. A clinical RBE model was derived from voxel-wise comparisons of estimated risk between photon and proton irradiation. Results: In total, 128 RICE of various grades occurred in 64 patients. Voxel-level modeling identified absorbed dose (D), D multiplied by dose-averaged linear energy transfer (LETd) for proton therapy, and PVR as independent predictors of RICE. The model implied a variable proton RBE described by RBE=1+m$\cdot$LETd, with m=0.10 $μ$m/keV. At the patient level, the equivalent uniform dose (EUDa=8) in the brain based on this RBE achieved the highest predictive performance. Conclusions: RICE was spatially associated with increased LET-dependent proton RBE and elevated PVR radiosensitivity across photon and proton radiotherapy. The cross-modality framework enables clinical assessment of proton RBE without reliance on predefined reference dose-response relationships. Incorporating variable proton RBE and the PVR as an organ at risk may improve risk assessment and mitigation of radiation-induced side effects. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_10174 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Combined photon-proton modeling of radiation-induced brain imaging changes supports variability in proton relative biological effectiveness and increased periventricular radiosensitivity Palkowitsch, Martina Kilian, Larissa S. Hennings, Fabian Lühr, Armin Thiem, Justus Grey, Arne Bütof, Rebecca Seidlitz, Annekatrin Troost, Esther G. C. Krause, Mechthild Löck, Steffen Medical Physics Purpose: Recent investigations of radiation-induced contrast enhancements (RICE) in brain tumor patients after proton therapy indicated variability in proton relative biological effectiveness (RBE) and increased radiosensitivity of the periventricular region (PVR). Prior studies, however, were restricted to proton cohorts requiring assumptions on reference radiation. This study assessed proton RBE variability and PVR radiosensitivity using spatially resolved predictive modeling of RICE in a combined photon-proton cohort. Methods and Materials: Predictive models for RICE detected on follow-up magnetic resonance imaging were developed in 152 brain tumor patients treated with photons or protons. Logistic regression was applied at the voxel level to model spatial occurrence and at the patient level to model incidence. A clinical RBE model was derived from voxel-wise comparisons of estimated risk between photon and proton irradiation. Results: In total, 128 RICE of various grades occurred in 64 patients. Voxel-level modeling identified absorbed dose (D), D multiplied by dose-averaged linear energy transfer (LETd) for proton therapy, and PVR as independent predictors of RICE. The model implied a variable proton RBE described by RBE=1+m$\cdot$LETd, with m=0.10 $μ$m/keV. At the patient level, the equivalent uniform dose (EUDa=8) in the brain based on this RBE achieved the highest predictive performance. Conclusions: RICE was spatially associated with increased LET-dependent proton RBE and elevated PVR radiosensitivity across photon and proton radiotherapy. The cross-modality framework enables clinical assessment of proton RBE without reliance on predefined reference dose-response relationships. Incorporating variable proton RBE and the PVR as an organ at risk may improve risk assessment and mitigation of radiation-induced side effects. |
| title | Combined photon-proton modeling of radiation-induced brain imaging changes supports variability in proton relative biological effectiveness and increased periventricular radiosensitivity |
| topic | Medical Physics |
| url | https://arxiv.org/abs/2604.10174 |