Explicitly encoding the cyclic nature of breathing signal allows for accurate breathing motion prediction in radiotherapy with minimal training data.

Background and purpose: Active breathing motion management in radiotherapy consists of motion monitoring, quantification and mitigation. It is impacted by associated latencies of a few 100 ms. Artificial neural networks can successfully predict breathing motion and eliminate latencies. However, they require usually a large dataset for training. The objective of this work was to demonstrate that explicitly encoding the cyclic nature of the breathing signal into the training data enables significant reduction of training datasets which can be obtained from healthy volunteers. Material and methods: Seventy surface scanner breathing signals from 25 healthy volunteers in anterior-posterior direction were used for training and validation (ratio 4:1) of long short-term memory models. The model performance was compared to a model using decomposition into phase, amplitude and a time-dependent baseline. Testing of the models was performed on 55 independent breathing signals in anterior-posterior direction from surface scanner (35 lung, 20 liver) of 30 patients with a mean breathing amplitude of (5.9 ± 6.7) mm. Results: Using the decomposed breathing signal allowed for a reduction of the absolute root-mean square error (RMSE) from 0.34 mm to 0.12 mm during validation. Testing using patient data yielded an average absolute RMSE of the breathing signal of (0.16 ± 0.11) mm with a prediction horizon of 500 ms. Conclusion: It was demonstrated that a motion prediction model can be trained with less than 100 datasets of healthy volunteers if breathing cycle parameters are considered. Applied to 55 patients, the model predicted breathing motion with a high accuracy.

DNA-PKcs Inhibition Sensitizes Human Chondrosarcoma Cells to Carbon Ion Irradiation via Cell Cycle Arrest and Telomere Capping Disruption.

In order to overcome the resistance to radiotherapy in human chondrosarcoma cells, the prevention from efficient DNA repair with a combined treatment with the DNA-dependent protein kinase catalytic subunit (DNA-PKcs) inhibitor AZD7648 was explored for carbon ion (C-ion) as well as reference photon (X-ray) irradiation (IR) using gene expression analysis, flow cytometry, protein phosphorylation, and telomere length shortening. Proliferation markers and cell cycle distribution changed significantly after combined treatment, revealing a prominent G2/M arrest. The expression of the G2/M checkpoint genes cyclin B, CDK1, and WEE1 was significantly reduced by IR alone and the combined treatment. While IR alone showed no effects, additional AZD7648 treatment resulted in a dose-dependent reduction in AKT phosphorylation and an increase in Chk2 phosphorylation. Twenty-four hours after IR, the key genes of DNA repair mechanisms were reduced by the combined treatment, which led to impaired DNA repair and increased radiosensitivity. A time-dependent shortening of telomere length was observed in both cell lines after combined treatment with AZD7648 and 8 Gy X-ray/C-ion IR. Our data suggest that the inhibition of DNA-PKcs may increase sensitivity to X-rays and C-ion IR by impairing its functional role in DNA repair mechanisms and telomere end protection.

Dose averaged linear energy transfer optimization for large sacral chordomas in carbon ion therapy.

BACKGROUND: Carbon ion beams are well accepted as densely ionizing radiation with a high linear energy transfer (LET). However, the current clinical practice does not fully exploit the highest possible dose-averaged LET (LETd) and, consequently, the biological potential in the target. This aspect becomes worse in larger tumors for which inferior clinical outcomes and corresponding lower LETd was reported. PURPOSE: The vicinity to critical organs in general and the inferior overall survival reported for larger sacral chordomas treated with carbon ion radiotherapy (CIRT), makes the treatment of such tumors challenging. In this work it was aimed to increase the LETd in large volume tumors while maintaining the relative biological effectiveness (RBE)-weighted dose, utilizing the LETd optimization functions of a commercial treatment planning system (TPS). METHODS: Ten reference sequential boost carbon ion treatment plans, designed to mimic clinical plans for large sacral chordoma tumors, were generated. High dose clinical target volumes (CTV-HD) larger than 250 cm 3 $250 \,{\rm cm}^{3}$ were considered as large targets. The total RBE-weighted median dose prescription with the local effect model (LEM) was D RBE , 50 % = 73.6 Gy $\textrm {D}_{\rm RBE, 50\%}=73.6 \,{\rm Gy}$ in 16 fractions (nine to low dose and seven to high dose planning target volume). No LETd optimization was performed in the reference plans, while LETd optimized plans used the minimum LETd (Lmin) optimization function in RayStation 2023B. Three different Lmin values were investigated and specified for the seven boost fractions: L min = 60 keV / µ m $\textrm {L}_{\rm min}=60 \,{\rm keV}/{\umu }{\rm m}$ , L min = 80 keV / µ m $\textrm {L}_{\rm min}=80 \,{\rm keV}/{\umu }{\rm m}$ and L min = 100 keV / µ m $\textrm {L}_{\rm min}=100 \,{\rm keV}/{\umu }{\rm m}$ . To compare the LETd optimized against reference plans, LETd and RBE-weighted dose based goals similar to and less strict than clinical ones were specified for the target. The goals for the organs at risk (OAR) remained unchanged. Robustness evaluation was studied for eight scenarios ( ± 3.5 % $\pm 3.5\%$ range uncertainty and ± 3 mm $\pm 3 \,{\rm mm}$ setup uncertainty along the main three axes). RESULTS: The optimization method with L min = 60 keV / µ m $\textrm {L}_{\rm min}=60 \,{\rm keV}/{\umu }{\rm m}$ resulted in an optimal LETd distribution with an average increase of LET d , 98 % ${\rm {LET}}_{{\rm {d,}}98\%}$ (and LET d , 50 % ${\rm {LET}}_{{\rm {d,}}50\%}$ ) in the CTV-HD by 8.9 ± 1.5 keV / µ m $8.9\pm 1.5 \,{\rm keV}/{\umu }{\rm m}$ ( 27 % $27\%$ ) (and 6.9 ± 1.3 keV / µ m $6.9\pm 1.3 \,{\rm keV}/{\umu }{\rm m}$ ( 17 % $17\%$ )), without significant difference in the RBE-weighted dose. By allowing ± 5 % $\pm 5\%$ over- and under-dosage in the target, the LET d , 98 % ${\rm {LET}}_{{\rm {d,}}98\%}$ (and LET d , 50 % ${\rm {LET}}_{{\rm {d,}}50\%}$ ) can be increased by 11.3 ± 1.2 keV / µ m $11.3\pm 1.2 \,{\rm keV}/{\umu }{\rm m}$ ( 34 % $34\%$ ) (and 11.7 ± 3.4 keV / µ m $11.7\pm 3.4 \,{\rm keV}/{\umu }{\rm m}$ ( 29 % $29\%$ )), using the optimization parameters L min = 80 keV / µ m $\textrm {L}_{\rm min}=80 \,{\rm keV}/{\umu }{\rm m}$ . The pass rate for the OAR goals in the LETd optimized plans was in the same level as the reference plans. LETd optimization lead to less robust plans compared to reference plans. CONCLUSIONS: Compared to conventionally optimized treatment plans, the LETd in the target was increased while maintaining the RBE-weighted dose using TPS LETd optimization functionalities. Regularly assessing RBE-weighted dose robustness and acquiring more in-room images remain crucial and inevitable aspects during treatment.

The role of artificial intelligence in informed patient consent for radiotherapy treatments-a case report.

Recent advancements in large language models (LMM; e.g., ChatGPT (OpenAI, San Francisco, California, USA)) have seen widespread use in various fields, including healthcare. This case study reports on the first use of LMM in a pretreatment discussion and in obtaining informed consent for a radiation oncology treatment. Further, the reproducibility of the replies by ChatGPT 3.5 was analyzed. A breast cancer patient, following legal consultation, engaged in a conversation with ChatGPT 3.5 regarding her radiotherapy treatment. The patient posed questions about side effects, prevention, activities, medications, and late effects. While some answers contained inaccuracies, responses closely resembled doctors' replies. In a final evaluation discussion, the patient, however, stated that she preferred the presence of a physician and expressed concerns about the source of the provided information. The reproducibility was tested in ten iterations. Future guidelines for using such models in radiation oncology should be driven by medical professionals. While artificial intelligence (AI) supports essential tasks, human interaction remains crucial.

Diamond based integrated detection system for dosimetric and microdosimetric characterization of radiotherapy ion beams.

BACKGROUND: Ion beam therapy allows for a substantial sparing of normal tissues and higher biological efficacy. Synthetic single crystal diamond is a very good material to produce high-spatial-resolution and highly radiation hard detectors for both dosimetry and microdosimetry in ion beam therapy. PURPOSE: The aim of this work is the design, fabrication and test of an integrated waterproof detector based on synthetic single crystal diamond able to simultaneously perform dosimetric and microdosimetric characterization of clinical ion beams. METHODS: The active elements of the integrated diamond device, that is, dosimeter and microdosimeter, were both realized in a Schottky diode configuration featured by different area, thickness, and shape by means of photolithography technologies for the selective growth of intrinsic and boron-doped CVD diamond. The cross-section of the sensitive volume of the dosimetric element is 4 mm2 and 1 µm-thick, while the microdosimetric one has an active cross-sectional area of 100 × 100 µm2 and a thickness of about 6.2 µm. The dosimetric and microdosimetric performance of the developed device was assessed at different depths in a water phantom at the MedAustron ion beam therapy facility using a monoenergetic uniformly scanned carbon ion beam of 284.7 MeV/u and proton beam of 148.7 MeV. The particle flux in the region of the microdosimeter was 6·107  cm2 /s for both irradiation fields. At each depth, dose and dose distributions in lineal energy were measured simultaneously and the dose mean lineal energy values were then calculated. Monte Carlo simulations were also carried out by using the GATE-Geant4 code to evaluate the relative dose, dose averaged linear energy transfer (LETd ), and microdosimetric spectra at various depths in water for the radiation fields used, by considering the contribution from the secondary particles generated in the ion interaction processes as well. RESULTS: Dosimetric and microdosimetric quantities were measured by the developed prototype with relatively low noise (∼2 keV/µm). A good agreement between the measured and simulated dose profiles was found, with discrepancies in the peak to plateau ratio of about 3% and 4% for proton and carbon ion beams respectively, showing a negligible LET dependence of the dosimetric element of the device. The microdosimetric spectra were validated with Monte Carlo simulations and a good agreement between the spectra shapes and positions was found. Dose mean lineal energy values were found to be in close agreement with those reported in the literature for clinical ion beams, showing a sharp increase along the Bragg curve, being also consistent with the calculated LETd for all depths within the experimental error of 10%. CONCLUSIONS: The experimental indicate that the proposed device can allow enhanced dosimetry in particle therapy centers, where the absorbed dose measurement is implemented by the microdosimetric characterization of the radiation field, thus providing complementary results. In addition, the proposed device allows for the reduction of the experimental uncertainties associated with detector positioning and could facilitate the partial overcoming of some drawbacks related to the low sensitivity of diamond microdosimeters to low LET radiation.

Investigation on the physical dose filtered by linear energy transfer for treatment plan evaluation in carbon ion therapy.

BACKGROUND: Large tumor size has been reported as a predicting factor for inferior clinical outcome in carbon ion radiotherapy (CIRT). Besides the clinical factors accompanied with such tumors, larger tumors receive typically more low linear energy transfer (LET) contributions than small ones which may be the underlying physical cause. Although dose averaged LET is often used as a single parameter descriptor to quantify the beam quality, there is no evidence that this parameter is the optimal clinical predictor for the complex mixed radiation fields in CIRT. PURPOSE: Purpose of this study was to investigate on a novel dosimetric quantity, namely high-LET-dose ( D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ , the physical dose filtered based on an LET threshold) as a single parameter estimator to differentiate between carbon ion treatment plans (cTP) with a small and large tumor volume. METHODS: Ten cTPs with a planning target volume, PTV ≥ 500 cm 3 $\mathrm{PTV}\ge {500}\,{{\rm cm}^{3}}$ (large) and nine with a PTV < 500 cm 3 $\mathrm{PTV}<{500}\,{{\rm cm}^{3}}$ (small) were selected for this study. To find a reasonable LET threshold ( L thr $\textrm {L}_{\textrm {thr}}$ ) that results in a significant difference in terms of D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ , the voxel based normalized high-LET-dose ( D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ ) distribution in the clinical target volume (CTV) was studied on a subset (12 out of 19 cTPs) for 18 LET thresholds, using standard distribution descriptors (mean, variance and skewness). The classical dose volume histogram concept was used to evaluate the D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ distributions within the target of all 19 cTPs at the before determined L thr $\textrm {L}_{\textrm {thr}}$ . Statistical significance of the difference between the two groups in terms of mean D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ volume histogram parameters was evaluated by means of (two-sided) t-test or Mann-Whitney-U-test. In addition, the minimum target coverage at the above determined L thr $\textrm {L}_{\textrm {thr}}$ was compared and validated against three other thresholds to verify its potential in differentiation between small and large volume tumors. RESULTS: An L thr $\textrm {L}_{\textrm {thr}}$ of approximately 30 keV / µ m ${30}\,{\rm keV/}\umu {\rm m}$ was found to be a reasonable threshold to classify the two groups. At this threshold, the D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ were significantly larger ( p < 0.05 $p<0.05$ ) in small CTVs. For the small tumor group, the near-minimum and median D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ (and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ ) in the CTV were in average 9.3 ± 1.5 Gy $9.3\pm {1.5}\,{\rm Gy}$ (0.31 ± 0.08) and 13.6 ± 1.6 Gy $13.6\pm {1.6}\,{\rm Gy}$ (0.46 ± 0.06), respectively. For the large tumors, these parameters were 6.6 ± 0.2 Gy $6.6\pm {0.2}\,{\rm Gy}$ (0.20 ± 0.01) and 8.6 ± 0.4 Gy $8.6\pm {0.4}\,{\rm Gy}$ (0.28 ± 0.02). The difference between the two groups in terms of mean near-minimum and median D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ ( D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ ) was 2.7 Gy (11%) and 5.0 Gy (18%), respectively. CONCLUSIONS: The feasibility of high-LET-dose based evaluation was shown in this study where a lower D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ was found in cTPs with a large tumor size. Further investigation is needed to draw clinical conclusions. The proposed methodology in this work can be utilized for future high-LET-dose based studies.

Proton dosimetry in a magnetic field: Measurement and calculation of magnetic field correction factors for a plane-parallel ionization chamber.

BACKGROUND: The combination of magnetic resonance imaging and proton therapy offers the potential to improve cancer treatment. The magnetic field (MF)-dependent change in the dosage of ionization chambers in magnetic resonance imaging-integrated proton therapy (MRiPT) is considered by the correction factor k B ⃗ , M , Q $k_{\vec{B},M,Q}$ , which needs to be determined experimentally or computed via Monte Carlo (MC) simulations. PURPOSE: In this study, k B ⃗ , M , Q $k_{\vec{B},M,Q}$ was both measured and simulated with high accuracy for a plane-parallel ionization chamber at different clinical relevant proton energies and MF strengths. MATERIAL AND METHODS: The dose-response of the Advanced Markus chamber (TM34045, PTW, Freiburg, Germany) irradiated with homogeneous 10 × $\times$ 10 cm 2 $^2$ quasi mono-energetic fields, using 103.3, 128.4, 153.1, 223.1, and 252.7 MeV proton beams was measured in a water phantom placed in the MF of an electromagnet with MF strengths of 0.32, 0.5, and 1 T. The detector was positioned at a depth of 2 g/cm 2 $^2$ in water, with chamber electrodes parallel to the MF lines and perpendicular to the proton beam incidence direction. The measurements were compared with TOPAS MC simulations utilizing COMSOL-calculated 0.32, 0.5, and 1 T MF maps of the electromagnet. k B ⃗ , M , Q $k_{\vec{B},M,Q}$ was calculated for the measurements for all energies and MF strengths based on the equation: k B ⃗ , M , Q = M Q M Q B ⃗ $k_{\vec{B},M,Q}=\frac{M_\mathrm{Q}}{M_\mathrm{Q}^{\vec{B}}}$ , where M Q B ⃗ $M_\mathrm{Q}^{\vec{B}}$ and M Q $M_\mathrm{Q}$ were the temperature and air-pressure corrected detector readings with and without the MF, respectively. MC-based correction factors were determined as k B ⃗ , M , Q = D det D det B ⃗ $k_{\vec{B},M,Q}=\frac{D_\mathrm{det}}{D_\mathrm{det}^{\vec{B}}}$ , where D det B ⃗ $D_\mathrm{det}^{\vec{B}}$ and D det $D_\mathrm{det}$ were the doses deposited in the air cavity of the ionization chamber model with and without the MF, respectively. Furthermore, MF effects on the chamber dosimetry are studied using MC simulations, examining the impact on the absorbed dose-to-water ( D W $D_{W}$ ) and the shift in depth of the Bragg peak. RESULTS: The detector showed a reduced dose-response for all measured energies and MF strengths, resulting in experimentally determined k B ⃗ , M , Q $k_{\vec{B},M,Q}$ values larger than unity. For all energies and MF strengths examined, k B ⃗ , M , Q $k_{\vec{B},M,Q}$ ranged between 1.0065 and 1.0205. The dependence on the energy and the MF strength was found to be non-linear with a maximum at 1 T and 252.7 MeV. The MC simulated k B ⃗ , M , Q $k_{\vec{B},M,Q}$ values agreed with the experimentally determined correction factors within their standard deviations with a maximum difference of 0.6%. The MC calculated impact on D W $D_{W}$ was smaller 0.2 %. CONCLUSION: For the first time, measurements and simulations were compared for proton dosimetry within MFs using an Advanced Markus chamber. Good agreement of k B ⃗ , M , Q $k_{\vec{B},M,Q}$ was found between experimentally determined and MC calculated values. The performed benchmarking of the MC code allows for calculating k B ⃗ , M , Q $k_{\vec{B},M,Q}$ for various ionization chamber models, MF strengths and proton energies to generate the data needed for a proton dosimetry protocol within MFs and is, therefore, a step towards MRiPT.

Stereoscopic X-ray image and thermo-optical surface guidance for breast cancer radiotherapy in deep inspiration breath-hold.

PURPOSE: To investigate the feasibility of a thermo-optical surface imaging (SGRT) system combined with room-based stereoscopic X­ray image guidance (IGRT) in a dedicated breast deep inspiration breath-hold (DIBH) irradiation workflow. In this context, benchmarking of portal imaging (EPID) and cone-beam CT (CBCT) against stereoscopic X­rays was performed. METHODS: SGRT + IGRT data of 30 left-sided DIBH breast patients (1 patient with bilateral cancer) treated in 351 fractions using thermo-optical surface imaging and X-ray IGRT were retrospectively analysed. Patients were prepositioned based on a free-breathing surface reference derived from a CT scan. Once the DIBH was reached using visual feedback, two stereoscopic X­ray images were acquired and registered to the digitally reconstructed radiographs derived from the DIBH CT. Based on this registration, a couch correction was performed. Positioning and monitoring by surface and X-ray imaging were verified by protocol-based EPID or CBCT imaging at selected fractions and the calculation of residual geometric deviations. RESULTS: The median X­ray-derived couch correction vector was 4.9 (interquartile range [IQR] 3.3-7.1) mm long. Verification imaging was performed for 134 fractions (216 RT field verifications) with EPID and for 37 fractions with CBCT, respectively. The median 2D/3D deviation vector length over all verification images was 2.5 (IQR 1.6-3.9) mm/3.4 (IQR 2.2-4.8) mm for EPID/CBCT, both being well within the planning target volume (PTV) margins (7 mm). A moderate correlation (0.49-0.65) was observed between the surface signal and X-ray position in DIBH. CONCLUSION: DIBH treatments using thermo-optical SGRT and X-ray IGRT were feasible for breast cancer patients. Stereoscopic X­ray positioning was successfully verified by standard IGRT techniques.

Radiobiological Assessment of Targeted Radionuclide Therapy with [177Lu]Lu-PSMA-I&T in 2D vs. 3D Cell Culture Models.

In vitro therapeutic efficacy studies are commonly conducted in cell monolayers. However, three-dimensional (3D) tumor spheroids are known to better represent in vivo tumors. This study used [177Lu]Lu-PSMA-I&T, an already clinically applied radiopharmaceutical for targeted radionuclide therapy against metastatic castrate-resistant prostate cancer, to demonstrate the differences in the radiobiological response between 2D and 3D cell culture models of the prostate cancer cell lines PC-3 (PSMA negative) and LNCaP (PSMA positive). After assessing the target expression in both models via Western Blot, cell viability, reproductive ability, and growth inhibition were assessed. To investigate the geometric effects on dosimetry for the 2D vs. 3D models, Monte Carlo simulations were performed. Our results showed that PSMA expression in LNCaP spheroids was highly preserved, and target specificity was shown in both models. In monolayers of LNCaP, no short-term (48 h after treatment), but only long-term (14 days after treatment) radiobiological effects were evident, showing decreased viability and reproductive ability with the increasing activity. Further, LNCaP spheroid growth was inhibited with the increasing activity. Overall, treatment efficacy was higher in LNCaP spheroids compared to monolayers, which can be explained by the difference in the resulting dose, among others.

Clinical Implementation and Evaluation of Auto-Segmentation Tools for Multi-Site Contouring in Radiotherapy.

Background and purpose: Tools for auto-segmentation in radiotherapy are widely available, but guidelines for clinical implementation are missing. The goal was to develop a workflow for performance evaluation of three commercial auto-segmentation tools to select one candidate for clinical implementation. Materials and Methods: One hundred patients with six treatment sites (brain, head-and-neck, thorax, abdomen, and pelvis) were included. Three sets of AI-based contours for organs-at-risk (OAR) generated by three software tools and manually drawn expert contours were blindly rated for contouring accuracy. The dice similarity coefficient (DSC), the Hausdorff distance, and a dose/volume evaluation based on the recalculation of the original treatment plan were assessed. Statistically significant differences were tested using the Kruskal-Wallis test and the post-hoc Dunn Test with Bonferroni correction. Results: The mean DSC scores compared to expert contours for all OARs combined were 0.80 ± 0.10, 0.75 ± 0.10, and 0.74 ± 0.11 for the three software tools. Physicians' rating identified equivalent or superior performance of some AI-based contours in head (eye, lens, optic nerve, brain, chiasm), thorax (e.g., heart and lungs), and pelvis and abdomen (e.g., kidney, femoral head) compared to manual contours. For some OARs, the AI models provided results requiring only minor corrections. Bowel-bag and stomach were not fit for direct use. During the interdisciplinary discussion, the physicians' rating was considered the most relevant. Conclusion: A comprehensive method for evaluation and clinical implementation of commercially available auto-segmentation software was developed. The in-depth analysis yielded clear instructions for clinical use within the radiotherapy department.

Evaluation of a novel CBCT conversion method implemented in a treatment planning system.

BACKGROUND: To evaluate a novel CBCT conversion algorithm for dose calculation implemented in a research version of a treatment planning system (TPS). METHODS: The algorithm was implemented in a research version of RayStation (v. 11B-DTK, RaySearch, Stockholm, Sweden). CBCTs acquired for each ten head and neck (HN), gynecology (GYN) and lung cancer (LNG) patients were collected and converted using the new algorithm (CBCTc). A bulk density overriding technique implemented in the same version of the TPS was used for comparison (CBCTb). A deformed CT (dCT) was created by using deformable image registration of the planning CT (pCT) to the CBCT to reduce anatomical changes. All treatment plans were recalculated on the pCT, dCT, CBCTc and the CBCTb. The resulting dose distributions were analyzed using the MICE toolkit (NONPIMedical AB Sweden, Umeå) with local gamma analysis, with 1% dose difference and 1 mm distance to agreement criteria. A Wilcoxon paired rank sum test was applied to test the differences in gamma pass rates (GPRs). A p value smaller than 0.05 considered statistically significant. RESULTS: The GPRs for the CBCTb method were systematically lower compared to the CBCTc method. Using the 10% dose threshold and the dCT as reference the median GPRs were for the CBCTc method were 100% and 99.8% for the HN and GYN cases, respectively. Compared to that the GPRs of the CBCTb method were lower with values of 99.8% and 98.0%, for the HN and GYN cases, respectively. The GPRs of the LNG cases were 99.9% and 97.5% for the CBCTc and CBCTb method, respectively. These differences were statistically significant. The main differences between the dose calculated on the CBCTs and the pCTs were found in regions near air/tissue interfaces, which are also subject to anatomical variations. CONCLUSION: The dose distribution calculated using the new CBCTc method showed excellent agreement with the dose calculated using dCT and pCT and was superior to the CBCTb method. The main reasons for deviations of the calculated dose distribution were caused by anatomical variations between the pCT and the corrected CBCT.

First microdosimetric measurements with a tissue-equivalent proportional counter at the MedAustron ion-beam therapy facility.

The aim of this work is to present the first microdosimetric spectra measured with a miniaturised tissue-equivalent proportional counter in the clinical environment of the MedAustron ion-beam therapy facility. These spectra were gathered with a 62.4-MeV proton beam and have been compared with microdosimetric spectra measured in the 62-MeV clinical proton beam of the CATANA beam line. Monte Carlo simulations were performed using the Geant4 toolkit GATE and a fully commissioned clinical beam line model. Finally, similarities and discrepancies of the measured data to simulations based on a simple and complex detector geometry are discussed.

Proton and Carbon Ion Irradiation Changes the Process of Endochondral Ossification in an Ex Vivo Femur Organotypic Culture Model.

Particle therapy (PT) that utilizes protons and carbon ions offers a promising way to reduce the side effects of radiation oncology, especially in pediatric patients. To investigate the influence of PT on growing bone, we exposed an organotypic rat ex vivo femur culture model to PT. After irradiation, histological staining, immunohistochemical staining, and gene expression analysis were conducted following 1 or 14 days of in vitro culture (DIV). Our data indicated a significant loss of proliferating chondrocytes at 1 DIV, which was followed by regeneration attempts through chondrocytic cluster formation at 14 DIV. Accelerated levels of mineralization were observed, which correlated with increased proteoglycan production and secretion into the pericellular matrix. Col2α1 expression, which increased during the cultivation period, was significantly inhibited by PT. Additionally, the decrease in ColX expression over time was more pronounced compared to the non-IR control. The chondrogenic markers BMP2, RUNX2, OPG, and the osteogenic marker ALPL, showed a significant reduction in the increase in expression after 14 DIV due to PT treatment. It was noted that carbon ions had a stronger influence than protons. Our bone model demonstrated the occurrence of pathological and regenerative processes induced by PT, thus building on the current understanding of the biological mechanisms of bone.

Increasing Quality and Efficiency of the Radiotherapy Treatment Planning Process by Constructing and Implementing a Workflow-Monitoring Application.

PURPOSE: To demonstrate how the efficiency of the treatment planning processes of a university radiation oncology department (2,500 new patients/year) could be improved by constructing and implementing a workflow-monitoring application. METHODS: A web-based application was developed in house, which enhanced the process management tools of the clinic's oncology information system. The application calculates the days left for the next task in the treatment planning process and visualizes the information on a browser-based whiteboard. Workflow monitoring considers tumor types (breast, prostate, lung, etc) and treatment techniques and is backward planned from the planned start of treatment. The effect of introducing this application was analyzed over four phases: (1) baseline data without the workflow-monitoring application, (2) after introducing workflow visualization via a browser-based whiteboard, (3) after upgrading the whiteboard and introducing backend rules, and (4) after updating these rules on the basis of data from the previous phase. RESULTS: Implementing the workflow-monitoring application and the introduced measures significantly reduced delays and, consequently, stress and a negative working atmosphere in the treatment planning process. Most notably, the amount of last-minute physics checks (on the day of the treatment start) could be reduced by 50%. CONCLUSION: The study showed what measures can help organize and prioritize the treatment planning workflow. The increased efficiency is believed to improve the quality and reduce the risk of human error.

MR-guided ion therapy: Detector response in magnetic fields during carbon ion irradiation.

BACKGROUND: Combining carbon ion therapy with on-bed MR imaging has the potential to bring particle therapy to a new level of precision. However, the introduction of magnetic fields brings challenges for dosimetry and quality assurance. For protons, a small, but significant change in detector response was shown in the presence of magnetic fields previously. For carbon ion beams, so far no such experiments have been performed. PURPOSE: To investigate the influence of external magnetic fields on the response of air-filled ionization chambers. METHODS: Four commercially available ionization chambers, three thimble type (Farmer, Semiflex, and PinPoint), and a plane parallel (Bragg peak) detector were investigated. Detectors were aligned in water such that their effective point of measurement was located at 2 cm depth. Irradiations were performed using 10 × 10 cm 2 $10\times 10\nobreakspace \mathrm{cm}^2$ square fields for carbon ions of 186.1, 272.5, and 402.8 MeV/u employing magnetic field strengths of 0, 0.25, 0.5, and 1 T. In addition, the detector response for protons and carbon ions was compared taking into account the secondary electron spectra and employing protons of 252.7 MeV for comparison. RESULTS: For all four detectors, a statistically significant change in detector response, dependent on the magnetic field strength, was found. The effect was more pronounced for higher energies. The highest effects were found at 0.5 T for the PinPoint detector with a change in detector response of 1.1%. The response of different detector types appeared to be related to the cavity diameter. For proton and carbon ion irradiation with similar secondary electron spectra, the change in detector response was larger for carbon ions compared to protons. CONCLUSION: A small, but significant dependence of the detector response was found for carbon ion irradiation in a magnetic field. The effect was found to be larger for smaller cavity diameters and at medium magnetic field strengths. Changes in detector response were more pronounced for carbon ions compared to protons.

Parameter based 4D dose calculations for proton therapy.

Background and purpose Retrospective log file-based analysis provides the actual dose delivered based on the patient's breathing and the daily beam-delivery dynamics. To predict the motion sensitivity of the treatment plan on a patient-specific basis before treatment start a prospective tool is required. Such a parameter-based tool has been investigated with the aim to be used in clinical routine. Materials and Methods 4D dose calculations (4DDC) were performed for seven cancer patients with small breathing motion treated with scanned pulsed proton beams. Validation of the parameter-based 4DDC (p-4DDC) method was performed with an anthropomorphic phantom and patient data employing measurements and a log file-based 4DDC tool. The dose volume histogram parameters (Dx%) were investigated for the target and the organs at risk, compared to static and the file-based approach. Results The difference between the measured and the p-4DDC dose was within the deviation of the measurements. The maximum deviation was 0.4Gy. For the planning target volume D98% varied up to 15% compared to the static scenario, while the results from the log file and p-4DDC agreed within 2%. For the liver patients, D33%liver deviated up to 35% compared to static and 10% comparing the two 4DDC tools, while for the pancreas patients the D1%stomach varied up to 45% and 11%, respectively. Conclusion The results showed that p-4DDC could be used prospectively. The next step will be the clinical implementation of the p-4DDC tool, which can support a decision to either adapt the treatment plan or apply motion mitigation strategies.

Generating deliverable DICOM RT treatment plans for prostate VMAT by predicting MLC motion sequences with an encoder-decoder network.

BACKGROUND: Deep learning-based auto-planning is an active research field; however, for some tasks a treatment planning system (TPS) is still required. PURPOSE: To introduce a deep learning-based model generating deliverable DICOM RT treatment plans that can be directly irradiated by a linear accelerator (LINAC). The model was based on an encoder-decoder network and can predict multileaf collimator (MLC) motion sequences for prostate VMAT radiotherapy. METHODS: A total of 619 treatment plans from 460 patients treated for prostate cancer with single-arc VMAT were included in this study. An encoder-decoder network was trained using 465 clinical treatment plans and validated on 77 plans. The performance was analyzed on a separate test set of 77 treatment plans. Separate L1 losses were computed for the leaf and jaw positions as well as the monitor units, with the leaf loss being weighted by a factor of 100 before being added to the other losses. The generated treatment plans were recalculated in a treatment planning system and the dose-volume metrics and gamma passing rates were compared to the original dose. RESULTS: All generated treatment plans showed good agreement with the original data, with an average gamma passing rate (3%/3 mm) of 91.9 ± 7.1%. However, the coverage of the PTVs. was slightly lower for the generated plans (D98%  = 92.9 ± 2.6%) in comparison to the original plans (D98%  = 95.7 ± 2.2%). There was no significant difference in mean dose to the bladder between the predicted and original plan (Dmean of 28.0 ± 13.5 vs. 28.1 ± 13.3% of prescribed dose) or rectum (Dmean of 42.3 ± 7.4 vs. 42.6 ± 7.5%). The maximum dose to bladder was only slightly higher in the predicted plans (D2% of 100.7 ± 5.3 vs. 99.8 ± 4.0%) and for the rectum it was even lower (D2% of 100.5 ± 3.7 vs. 100.1 ± 4.3). CONCLUSIONS: The deep learning-based model could predict MLC motion sequences in prostate VMAT plans, eliminating the need for sequencing inside a TPS, thus revolutionizing autonomous treatment planning workflows. This research completes the loop in deep learning-based treatment planning processes, enabling more efficient workflows for real-time or online adaptive radiotherapy.

Impact of log file source and data frequency on accuracy of log file-based patient specific quality assurance.

Performing phantom measurements for patient-specific quality assurance (PSQA) adds a significant amount of time to the adaptive radiotherapy procedure. Log file based PSQA can be used to increase the efficiency of this process. This study compared the dosimetric accuracy of high-frequency linear accelerator (Linac) log files and low-frequency log data stored in the oncology information system (OIS). Thirty patients were included, that were recently treated in the head and neck (HN), brain, and prostate region with volumetric modulated arc therapy (VMAT) and an additional ten patients treated using stereotactic body radiation therapy (SBRT) with 3D-conformal radiotherapy (3D-CRT) technique. Log data containing a single fraction were used to calculate the dose distributions. The dosimetric differences between Linac log files and OIS logs were evaluated with a gamma analysis with 2%/2 mm criterion and dose threshold of 30%. The original treatment plan was used as a reference. Moreover, DVH parameters of D98%, D50%, and D2% of the planning-target volume (PTV) and dose to several organs at risk (OARs) were reported. Significant differences in dose distributions between the two log types and the original dose were observed for PTV D98% and D2% (r < 0.001) for HN cases, PTV D98% (r = 0.005) for brain cases, and PTV D50% (r = 0.015) for prostate cases. No significant differences were found between the two log types with respect to D50%. The root mean square (RMS) error of the leaf positions of the OIS log was approximately twice the RMS error of the Linac log file for VMAT plans, but identical for 3D-CRT plans. The relationship between the gamma pass rate and the RMS error showed a moderate correlation for the Linac log files (r = -0.58, p < 0.001) and strong correlation for OIS logs (r = -0.71, p < 0.001). Furthermore, all doses calculated using Linac log files and OIS log data had a GPR >90% for an RMS error < 3.3 mm. Based on these findings, a tolerance limit of RMS error of 3.3 mm for considering OIS log based PSQA was established. Nevertheless, the OIS log data quality should be improved to achieve adequate PSQA.