PURPOSE:Ion beam radiation therapy offers steep dose gradients and high biological effectiveness required for the treatment of complex cancer cases. While the vast majority of ion beam therapy centers currently use protons and carbon ions, there is renewed interest in helium ions due to their unique physical and radiobiological properties. All ion-beam treatments are subject to beam-range uncertainties, mainly due to potential changes in patient morphology. In vivo treatment monitoring of secondary ions could potentially provide feedback on treatment quality, enabling dose reduction in healthy tissue or escalation of the tumor dose. METHODS AND MATERIALS:This work presents the first in vivo monitoring of a patient undergoing helium-ion therapy for a solitary fibrous tumor. The method is based on tracking secondary ions emitted from the patient as a natural byproduct of ion beam radiation therapy. RESULTS:The comparison of 2 measured secondary-ion distributions confirmed high treatment reproducibility for the reported patient. However, significant differences between the 2 fractions were detected at the border of the skull base and the sinus sphenoidalis, which could originate from potential interfractional cavity filling. CONCLUSIONS:We successfully performed the world's first in vivo monitoring of innovative helium-ion therapy. In the future, the observed signals will need to be validated in patients who receive regular control computed tomography scans. Moreover, Monte Carlo simulations and phantom measurements will help establish a robust link between changes in the secondary-ion distribution and clinically relevant changes in dose.

BACKGROUND:Carbon-ion radiotherapy offers highly precise targeting of tumors while sparing healthy tissue compared to X-ray therapy. However, this precision comes at the cost of an increased sensitivity of the treatment to range uncertainties, which can arise from anatomical changes of the patient. Our group develops an in-vivo treatment monitoring method by tracking of charged nuclear fragments using hybrid silicon pixel detectors. PURPOSE:Anatomical changes outside of the region accessed by carbon-ion beams are clinically not relevant, as they do not affect the dose distribution. However, they can potentially influence the fragment data, producing artifacts, which might be interpreted as signals produced by clinically relevant anatomical changes. This misinterpretation would cause unnecessary clinical action, like performing a CT scan. This work proposes methods for the identification and suppression of clinically irrelevant artifacts with the aim of avoiding unnecessary clinical action. METHODS:A clinically relevant and an irrelevant anatomical change are emulated by introducing coin-sized air cavities at different positions in a homogeneous cylindrical plastic head phantom. Charged nuclear fragments are detected by a Timepix3-based mini-tracker during irradiations of this phantom with a clinically realistic treatment plan. All measurements are performed for two different positions of the mini-tracker. The reconstructed fragmentation vertex distributions are analyzed and compared to those of reference measurements. RESULTS:A significant signal from the clinically irrelevant air cavity was observed. This artifact was found to differ from the signal of the clinically relevant cavity. Most importantly, the location of the artifact changes with the mini-tracker position, whereas the relevant signal remains unchanged. This facilitates identification of the artifact as well as its suppression by combining the data from several mini-trackers at different positions around the patient. CONCLUSIONS:Clinically irrelevant changes were shown to potentially impede carbon-ion treatment monitoring by tracking of charged nuclear fragments. However, positioning several mini-trackers around the patient, which monitor the treatment from different perspectives, was found to be the key to the identification and suppression of artifacts from anatomical changes outside of the region accessed by carbon-ion beams. This is implemented in the detection system of an ongoing clinical trial.

The exploitation of the high relative biological effectiveness (RBE) of carbon ions is one of the major rationales for their use as a radiation therapy modality. As the RBE depends on many physical and biological factors, biophysical models are used to compute it for the complex radiation fields used in clinical settings. However, the models currently applied in clinics or used to interpret clinical results make different RBE predictions. This creates difficulties for direct comparability of RBE-weighted doses delivered and reported within different approaches. Additional conventions on how these models are applied also differ and further complicate the comparison. Consequently, it is crucial to understand the impact of RBE modeling on the delivered absorbed doses and the reported RBE-weighted doses. Translation concepts between dose prescription systems, that is, the models and the context in which they are used, are needed to exchange treatment protocols between centers with different planning methods and to establish joint clinical studies or meta-studies. Although many of these problems are solved for specific cases, a broad perspective is lacking on how to transparently proceed with multiple RBE models and corresponding concepts of RBE-weighted dose. The present publication is a product of an initiative within the subcommittee on Guidelines in Carbon Ion Radiation Therapy of the Particle Therapy Co-operative group (PTCOG). It aims to (1) raise awareness of the problem; (2) demonstrate the impact of different models used for RBE predictions; (3) provide information on how RBE is currently accounted for; and (4) give an overview of approaches toward the translation of doses. Along this route, we provide several expert consensus statements agreed on by all authors, which provide insights into the complexity of understanding and comparing different dose prescription systems. Despite this complexity, transforming treatment plans between any 2 systems is feasible, opening up novel planning strategies that consider multiple models and paving the way for multi-institutional clinical studies .

BACKGROUND:To ensure accurate, safe, and reproducible patient treatments, it is essential to have precise knowledge and a solid understanding of patient-specific quality assurance (PSQA). For many years, the delivery of doses to all patients has been verified using dosimetric measurements. However, these measurements require substantial work, and the reasons for the occasional deviations are unclear. For these reasons, alternative methods such as independent dose calculations (IDCs) and analysis of beam-monitor log files are increasingly discussed in the particle therapy community. Nevertheless, before replacing dose-verification measurements with other methods, existing measurement data should be thoroughly analyzed to determine what can be learned from them and how they compare with potential alternatives. These alternative methods are mentioned in this work only to provide context and to outline possible directions for future studies. PURPOSE:To evaluate the dosimetric accuracy and efficiency of PSQA using a water phantom (WP) over a 10-year period at the Heidelberg Ion Beam Therapy Center (HIT). METHODS:Between 2016 and 2025, 23014 treatment fields with protons, carbon, or helium ions were verified using a WP equipped with 24 pinpoint ionization chambers. The patient treatment plans were recalculated in the water phantom geometry and compared to measured absolute doses. The data were categorized by treatment room, ion species, treatment planning systems (TPS), range shifter (RaShi) use, indication, depth, and target volume, excluding measurements with human errors. Statistical analysis compared measured and calculated doses, focusing on mean, maximum, and minimum dose deviations. Furthermore, the workflow efficiency was assessed based on the beam time required for dosimetric verification, as well as the total time needed for preparation and analysis. RESULTS:Mean dose deviations were in general slightly negative (t-test, p < 0.01), within ±1 % across all categories (total mean ± SD  =  -0.50 ± 0.90 %), with 91 % of fields passing institutional ±5 % tolerances. Further, significant differences (p < 0.01) were also observed between treatment rooms, ion species, TPS platforms, and RaShi settings. Additionally, the RayStation TPS showed lower deviations than the Syngo TPS, and helium ions had the smallest deviations. Moreover, repeated verifications reduced variability but without significant improvement. Correlations with target depth or volume were statistically significant but clinically negligible. Less than 1 % of maximum and minimum dose measurements exceeded ±7 % annually. Finally, over 4308 h of beam time, preparation, and analysis were spent on PSQA during the 10-year period. CONCLUSIONS:PSQA at HIT demonstrated high dosimetric accuracy and delivery stability. Integration of IDCs and log file analysis may improve efficiency and allow to omit verification measurements in well-established cases without compromising patient safety and treatment quality, if the extensive machine QA program is maintained.

Accurate organ segmentation is crucial for prostate cancer radiotherapy, but cone-beam computer tomography (CBCT) based models are hindered by low image quality and annotation scarcity. Existing approaches rely on deformable registration, which struggles with softtissue deformations, or direct CBCT training, which suffers from domain shifts and low-quality labels. We propose a domain adaptation framework that enables robust prostate segmentation on CBCT using crossmodality supervision from planning CT (pCT). A cycle-consistent generative adversarial network translates pCT into synthetic CBCT, enabling segmentation models to train on high-quality pCT-derived annotations while adapting to CBCT characteristics. Additionally, anatomy-aware augmentation enhances robustness to organ deformations across diverse patient anatomies. Using a multi-center dataset, our approach achieves segmentation accuracy comparable to pCT-trained models. By eliminating the need for manual CBCT annotations, our method enables practical AI-driven segmentation for adaptive radiotherapy.

BACKGROUND:In proton therapy of low-grade glioma (LGG) patients, contrast-enhancing 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 treatment 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 objective 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 PTV D95 RBE , fx ≈ 0.00 ${{\Delta}}_{\text{PTV}}{\text{D95}}_{\textit{RBE},\textit{fx}}\approx 0.00$ , Δ GTV D95 RBE , fx ≈ 0.03 ${{\Delta}}_{\text{GTV}}{\text{D95}}_{\textit{RBE},\textit{fx}}\approx 0.03$ ), 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.

BACKGROUND:Nanodosimetry relates the cumulative or statistical moments of Ionization Detail (ID) with biological endpoints of relevance to cancer radiotherapy using charged particles. This association suggests to develop an additional physics-detailed layer of modeling that may complement biological modeling and treatment planning. The recently introduced cluster dose g ( I p ) may serve as a purely physical quantity bridging the Ionization Parameter ( I p ) to the macroscopic treatment planning scale. PURPOSE:In this work, we developed a framework to enable flexible and direct cluster dose optimization using a pencil-beam algorithm, which we validated with condensed history Monte Carlo (MC) simulations. METHODS:Cluster dose combines the contributions to I p from all particles within a macroscopic volume. Our framework, implemented in the open source planning toolkit matRad, utilizes the particle and energy-dependent I p values from an ID database precomputed from MC track strucure (MCTS) simulations. First, we create pencil-beam (PB) kernels, including fluence spectra, from condensed history MC simulations. For a water box phantom and a representative prostate patient, we create treatment plans optimized on dose and cluster dose F 5 coverage and homogeneity for protons, helium and carbon ions. Plans were validated with Geant4/TOPAS MC. RESULTS:Our framework provided accurate, practical cluster dose calculation and planning. PB algorithms achieve typical accuracy for cluster dose calculation comparable to dose calculation. Recalculation with TOPAS on the box phantom yielded 3D gamma passing rates (GPRs) greater than 97 % . For the prostate patient, GPRs exceeded 98 % . Both used the 3 % / 3 m m criterion with a threshold of 10 % of the maximum dose. Using cluster dose F 5 optimization, homogeneous cluster dose target coverage was achieved in all plans. A constant cluster dose prescription across all ion species shows the expected decrease in required absorbed dose for heavier ions. CONCLUSIONS:We demonstrate that fast, direct cluster dose calculation and optimization is feasible using MC validated planning with PB algorithms. Cluster dose prescription and optimization results in the expected cluster dose coverage and physical dose levels depending on the respective primary ion.

Background and Purpose:Carbon ion radiotherapy (CIRT) for liver patients is usually administrated in four high-dose fractions, requiring high geometrical precision. Work is underway to implement online magnetic resonance (MR)-guided adaptive workflows for this indication. For the generation of a daily computed tomography (dCT), deformable image registration (DIR) can be used. Here, a study on a deformable anthropomorphic abdomen phantom was conducted to assess the accuracy of MR-to-CT DIR. Materials and Methods:We applied eight different static compressions on the phantom to induce deformations, acquired CT and MR images and performed DIR to generate dCT images for each MR. We assessed the geometric uncertainties of DIR for T1- and T2-weighted MRI sequences by comparing the deformed structures against a manually segmented ground-truth. Furthermore, we assessed the DIR impact on the dose distribution on a single-beam CIRT plan, comparing the beam's range (R80%) on the dCT against those of the CT images. Results:From the geometric analysis, we obtained mean Dice similarity coefficients (DSC) for the liver of 0.94 ± 0.02 for the T1- and 0.95 ± 0.10 for the T2-weighted MR sequences. These values were above the mean deformation induced on the liver (DSC of 0.87 ± 0.08). As for the range uncertainty induced by DIR, we observed mean R80% uncertainties up to 1.35 mm when comparing treatment doses on the dCT and CT images. Conclusions:Geometric and beam range uncertainties have been assessed systematically and were found to be small. These results support further implementation of an MR-guided DIR-based online adaptive workflow for liver CIRT.

Objective.To determine beam quality correction factors,, in single-layer scanned carbon and helium ion beams using water calorimetry, thereby reducing uncertainties in dosimetry for light ion therapy.Approach.Water calorimetry measurements were performed under harmonized conditions at two synchrotron-based ion beam therapy centers (MedAustron, Austria and HIT, Germany). Measurements were conducted in the plateau region of single-layer scanned beams. Carbon ion beams covered nominal energies from 213.4-402.8 MeV/u, while helium ion beams were measured at 196.3 and 198.8 MeV/u. Multiple cylindrical (IBA FC65-G, PTW 30013) and plane-parallel (IBA PPC05, PPC40; PTW 34001, 34045) ionization chamber types were investigated.Results.-factors were determined with standard uncertainties of approximately 1%, depending on chamber type and measurement condition. For all investigated chambers, inter-center agreement was observed within the combined standard uncertainties. Chamber-to-chamber variability was below 0.5% for chamber types for which two samples were available, except for the IBA PPC05, for which differences up to 1.3% were observed. For carbon ion beams, the measured-factors are consistent with previously published water calorimetry-based results. However, systematic deviations up to 3% persist between experimentally determined and Monte Carlo-derivedvalues. The measured-factors for helium ions show trends that are broadly similar to those observed in carbon ion beams across all chamber types.Significance.This work expands the experimental-database for light ions by providing new carbon ion data and the first experimental-factors for helium ion beams. These results provide essential experimental data for future refinement of dosimetry recommendations, and highlight persistent discrepancies between the experimental and Monte Carlo-based-factors that require further investigation.

Knowing about anatomical deformations in patient images is crucial for adaptive image-guided radiation therapy. Biomechanical models ensure biofidelity in deformable image registration, but manual contouring limits their clinical use. We investigate the application of automatically generated contours for a biomechanical registration model in head and neck cancer treatment. For that, we automatically generate individual bone segmentations on planning CT scans examining a custom-trained nnU-Net model and the ready-trained TotalSegmentator model. Both sets of segmentations are evaluated using DICE, Hausdorff Distance and surface DICE. We investigate their impact on the build-up of the biomechanical articulated skeleton model by deviations in joint positioning and CT-CT registration accuracy using target registration error (TRE). The custom-trained model achieves 1.51 +/- 0.26 mm TRE, with no significant difference in registration accuracy. While the TotalSegmentator does not provide all structures needed for the complete biomechanical model build-up. Overall, deep learning-based automatic bone segmentation can replace manual contouring in this model, matching its performance.

Ultra-high dose rate (UHDR) radiotherapy has been shown in preclinical studies to reduce normal tissue toxicity without compromising tumour control, a phenomenon referred to as the Flash effect. The radiochemical and biological mechanisms responsible for this effect remain unclear. This study investigates radical formation and oxygen depletion under UHDR and conventional dose rate (CDR) conditions to gain mechanistic insight. Radical formation was investigated using electron spin resonance (ESR) spectroscopy with both spin trapping and spin probe techniques. Oxygen consumption was monitored continuously during irradiation to complement radical yield measurements. E3 medium containing either spin traps (DMPO, DEPMPO, BMPO) or spin probes (CMH, TMTH, CAT1H) was prepared under hypoxic, physioxic, and normoxic conditions. Irradiations were performed at the Electron Linac for beams with high Brilliance and low Emittance at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) with 30 MeV electrons across a broad range of dose rates (0.1 Gy s −1 –10 5 Gy s −1 ). Spin probe measurements enabled consistent comparisons between CDR and UHDR, revealing a significant dependence of spin concentration on both oxygenation and dose rate. In contrast, spin trapping showed reduced radical yields with decreasing oxygen levels, but no significant dose-rate dependence. Direct comparisons between UHDR and CDR were limited by differences in the decay kinetics of the spin adducts. Oxygen measurements confirmed a reduced oxygen consumption at UHDR, with the extent of depletion strongly dependent on initial oxygen concentration. The results support the hypothesis that UHDR conditions promote radical–radical recombination, shifting the reaction equilibrium and reducing the pool of radicals available to react in the homogeneous chemical phase, particularly with oxygen. The combined application of ESR spin trapping, spin probes, and real-time oxygen measurements offers complementary insight into dose-rate-dependent radical processes.

PURPOSE:To describe performance measurements, adaptations and time stability over 20 months of a diagnostic MR scanner for integration into MR-guided photon and particle radiotherapy. MATERIAL AND METHODS:For realization of MR-guided photon and particle therapy (MRgRT/MRgPT), a 1.5 T MR scanner was installed at the Heidelberg Ion Beam Therapy Center. To integrate MRI into the treatment process, a flat tabletop and dedicated coil holders for flex coils were used, which prevent deformation of the patient external contour and allow for the use of immobilization tools for reproducible positioning. The signal-to-noise ratio (SNR) was compared for the diagnostic and therapy-specific setup using the flat couch top and flexible coils for the a) head & neck and b) abdominal region as well as for different bandwidths and clinical pulse sequences. Additionally, a quality assurance (QA) protocol with monthly measurements of the ACR phantom and measurement of geometric distortions for a large field-of-view (FOV) was implemented to assess the imaging quality parameters of the device over the course of 20 months. RESULTS:The SNR measurements showed a decreased SNR for the RT-specific as compared to the diagnostic setup of (a) 26% to 34% and (b) 11% to 33%. No significant bandwidth dependency for this ratio was found. The longitudinal assessment of the image quality parameters with the ACR and distortion phantom confirmed the long-term stability of the MRI device. CONCLUSION:A diagnostic MRI was commissioned for use in MR-guided particle therapy. Using a radiotherapy specific setup, a high geometric accuracy and signal homogeneity was obtained after some adaptions and the measured parameters were shown to be stable over a period of 20 months.

Background and purpose:Carbon ion radiotherapy (CIRT) has demonstrated promising treatment outcomes for pancreatic cancer. However, breathing-induced organ motion can compromise the efficacy of the treatment, leading to under- or over-dosage within the target and organs at risk (OARs). In this work, the dose during CIRT was simultaneously measured at the target and OARs using an anthropomorphic phantom to evaluate the effectiveness of respiratory gating for compensating breathing motion. Materials and methods:The Pancreas Phantom for Ion beam Therapy (PPIeT) was irradiated with carbon ions. The phantom features a pancreas with a virtual tumour and OARs including a duodenum, kidneys, a spine and a spinal cord. Breathing-induced organ motion was imitated with amplitudes of 0 mm (control), 5 mm, 10 mm and 20 mm while irradiating with and without gating. Dose measurements were performed using an ionisation chamber and passive detectors. Results:The prescribed uniform dose of 1.37 Gy in the virtual tumour was experimentally validated for the control. Breathing-induced motion of 20 mm led to a 75 % dose coverage at the target improving to 91 % with gating. For the OARs, the mean dose varied according to the organ, with gating showing no significant differences. Conclusions:Accurate CIRT dosimetry with variable breathing-induced motions can be conducted with PPIeT for a pancreatic tumour and the OARs. Gating mitigated the effects of breathing-induced motion in the tumour.

Objectives. Carbon-ion radiotherapy is a cancer treatment modality with exceptional precision and effectiveness compared to conventional x-ray therapy. Our goal is to support maintaining its precise dose administration throughout a multi-fractional radiation treatment by detecting possible anatomical changes decremental to conformal dose deposition without the need for additional imaging. To that end our work group has developed a custom detection system using TimePix3 trackers during treatment to detect the naturally occurring secondary charged particles, which carry information about the irradiated region. This enables treatment-day accurate in-vivo monitoring of patient anatomy without requiring additional imaging. Our goal is to provide a robust and extensible methodological framework that allows us to extract relevant information supporting clinical decision making. Approach. Comparing the measurements of different states of the same patient, we aim to determine if an anatomical change is present and at what location it occurred. Departing from solely utilizing statistical differences in local particle counts, the presented method exploits the spectral domain of the measurement differences. We perform a localized spectral analysis and exploit joint localized frequency band variations to robustly identify the location of changes between two measurement states. Main Results. We show the validity of our approach, reporting the performance results of applying our method to measurements acquired during irradiation experiments using polymethyl methacrylate head phantoms carried out at the Heidelberg Ion Beam Therapy Center. Furthermore, we demonstrate the flexibility of our analysis framework by showing the impact of applying filters or using alternative sub-modules in its multi-stage processing pipeline. Significance. We provide a data-analytical framework as well as basic analytical methods required to extract evidence for the presence of anatomical changes from secondary charged particle measurements for subsequent clinical assessment. These represent essential building blocks required to perform full 3D reconstruction of anatomical changes based solely on secondary particles.