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Track structure Monte Carlo simulations are a useful tool to investigate the damage induced to DNA by ionizing radiation. These simulations usually rely on simplified geometrical representations of the DNA subcomponents. DNA damage is determined by the physical and physicochemical processes occurring within these volumes. In particular, damage to the DNA backbone is generally assumed to result in strand breaks. DNA damage can be categorized as direct (ionization of an atom part of the DNA molecule) or indirect (damage from reactive chemical species following water radiolysis). We also consider quasi-direct effects, i.e., damage originated by charge transfers after ionization of the hydration shell surrounding the DNA. DNA geometries are needed to account for the damage induced by ionizing radiation, and different geometry models can be used for speed or accuracy reasons. In this work, we use the Monte Carlo track structure tool TOPAS-nBio, built on top of Geant4-DNA, for simulation at the nanometer scale to evaluate differences among three DNA geometrical models in an entire cell nucleus, including a sphere/spheroid model specifically designed for this work. In addition to strand breaks, we explicitly consider the direct, quasi-direct, and indirect damage induced to DNA base moieties. We use results from the literature to determine the best values for the relevant parameters. For example, the proportion of hydroxyl radical reactions between base moieties was 80%, and between backbone, moieties was 20%, the proportion of radical attacks leading to a strand break was 11%, and the expected ratio of base damages and strand breaks was 2.5-3. Our results show that failure to update parameters for new geometric models can lead to significant differences in predicted damage yields.

In radiopharmaceutical treatmentsα-particles are employed to treat tumor cells. However, the mechanism that drives the biological effect induced is not well known. Being ionizing radiation,α-particles can affect biological organisms by producing damage to the DNA, either directly or indirectly. Following the principle that microdosimetry theory accounts for the stochastic way in which radiation deposits energy in sub-cellular sized volumes via physical collisions, we postulate that microdosimetry represents a reasonable framework to characterize the statistical nature of direct damage induction byα-particles to DNA. We used the TOPAS-nBio Monte Carlo package to simulate direct damage produced by monoenergetic alpha particles to different DNA structures. In separate simulations, we obtained the frequency-mean lineal energy (yF) and dose-mean lineal energy (yD) of microdosimetric distributions sampled with spherical sites of different sizes. The total number of DNA strand breaks, double strand breaks (DSBs) and complex strand breaks per track were quantified and presented as a function of eitheryForyD.The probability of interaction between a track and the DNA depends on how the base pairs are compacted. To characterize this variability on compactness, spherical sites of different size were used to match these probabilities of interaction, correlating the size-dependent specific energy (z) with the damage induced. The total number of DNA strand breaks per track was found to linearly correlate withyFandzFwhen using what we defined an effective volume as microdosimetric site, while the yield of DSB per unit dose linearly correlated withyDorzD,being larger for compacted than for unfolded DNA structures. The yield of complex breaks per unit dose exhibited a quadratic behavior with respect toyDand a greater difference among DNA compactness levels. Microdosimetric quantities correlate with the direct damage imparted on DNA.

Ru/Rh asymmetric plaques for ophthalmic brachytherapy have special geometric designs with a cutout intended to prevent irradiation of critical ocular structures proximal to the tumor. In this work, we present new geometric models for PENELOPE+PenEasy Monte Carlo simulations of these applicators, differing from the vendor-reported geometry, that better match their real geometry to assess their dosimetric impact. Simulation results were benchmarked to experimental dosimetric data from radiochromic film measurements, data provided by the manufacturer in the calibration certificates, and other experimental results published in the literature, obtaining, in all cases, better agreement with the modified geometries. The clinical impact of the new geometric models was evaluated by simulating real clinical cases using patient-specific eye models. The cases calculated using the modified geometries presented higher doses to the critical structures proximal to the cutout region. The modified geometric models presented in this work provide a more accurate representation of the asymmetric plaques, greatly improving the agreement between Monte Carlo calculations and experimental measurements. Lack of consideration of accurate geometric models has been shown to be translated into notable increases in dose to organs at risk in clinical cases. [ABSTRACT FROM AUTHOR]

Background and Purpose: Proton arc therapy and FLASH radiotherapy (FLASH-RT) each offer unique advantages in proton therapy. However, clinical translation of FLASH-RT faces challenges in defining and delivering high dose rates. We propose the use of proton FLASH-arc therapy (PFAT) to leverage the benefits of arc while addressing FLASH delivery concerns by spatially fractionating dose delivery to healthy tissue., Materials and Methods: Treatment plans for an abdominal phantom and a clinical brain case were designed in OpenTPS, using monoenergetic beams within a 360-degree gantry rotation. Beams were optimized to achieve target coverage while maximizing spatial fractionation in non-target regions. The temporal dose delivery to healthy-tissue voxels, or in specified organs-at-risk (OARs), was constrained via selective spot removal in the beamlets matrix. The dose, LET, number of spots per voxel, and voxel-wise average dose rate were calculated for each PFAT plan and compared to a corresponding IMPT scenario., Results: PFAT plans demonstrated comparable dose conformity to IMPT, with LET hotspots shifted towards the target center. The number of spots influencing healthy-tissue voxels was reduced, leading to regions of substantially higher dose rates in many points outside the target. OAR dose-rate optimization in the brain plan resulted in dose rates exceeding 40 Gy/s in the majority of points in the brainstem., Conclusion: The PFAT technique combines the advantages of FLASH and arc therapy, providing improved LET distributions and enhanced biological effect in the target, while achieving high dose rates in healthy tissue, thus reducing healthy tissue damage. This feasibility study demonstrates the capability of PFAT, setting the foundation for further optimization and application in diverse patient cases and complex geometries., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objectives: This study aims to explore the synergistic effects of combining Stereotactic Body Radiation Therapy (SBRT) and Selective Internal Radiation Therapy (SIRT) in that specific sequence for treating hepatocellular carcinoma (HCC), particularly in patients at high risk of radiation-induced liver disease (RILD)., Methods: We analyzed a case of a patient with HCC who was treated with SBRT at our institution. A virtual 90Y dose distribution was added using our in-house -BLINDED FOR REVIEW- model to keep a minimum dose to the healthy liver tissue. BED and EUD metrics were calculated to harmonize the dose distributions of SBRT and SIRT., Results: Our radiation biology-based models suggest that the combination of SBRT and SIRT could maintain effective tumor control while reducing the dose to normal liver tissue. Specifically, an SBRT plan of 10 Gy x 3 fractions combined with SIRT yielded comparable tumor control probability to an SBRT-only plan of 10 Gy x 5 fractions., Conclusion: The combination of SBRT and SIRT is a promising treatment strategy for HCC patients at high risk of RILD. While the LQ model and associated formalisms provide a useful starting point, further studies are needed to account for factors beyond these models. Nonetheless, the potential for significant dose reduction to normal tissue suggests that this combination therapy could offer substantial clinical benefits., Advances in Knowledge: This article presents a proposal to combine SBRT and SIRT, in this specific order, for HCC, discussing its advantages. A framework for future research into optimizing combination therapy for HCC is provided, utilizing a novel HCC vascular model to simulate 90Y doses., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Institute of Radiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Purpose: In radiotherapy (RT) for brain tumors, patient heterogeneity masks treatment effects, complicating the prediction and mitigation of radiation-induced brain necrosis. Therefore, understanding this heterogeneity is essential for improving outcome assessments and reducing toxicity., Experimental Design: We developed a clinically practical pipeline to clarify the relationship between dosimetric features and outcomes by identifying key variables. We processed data from a cohort of 130 patients treated with proton therapy for brain and head and neck tumors, utilizing an expert-augmented Bayesian network to understand variable interdependencies and assess structural dependencies. Critical evaluation involved a three-level grading system for each network connection and a Markov blanket analysis to identify variables directly impacting necrosis risk. Statistical assessments included log-likelihood ratio, integrated discrimination index, net reclassification index, and receiver operating characteristic (ROC)., Results: The analysis highlighted tumor location and proximity to critical structures such as white matter and ventricles as major determinants of necrosis risk. The majority of network connections were clinically supported, with quantitative measures confirming the significance of these variables in patient stratification (log-likelihood ratio = 12.17; P = 0.016; integrated discrimination index = 0.15; net reclassification index = 0.74). The ROC curve area was 0.66, emphasizing the discriminative value of nondosimetric variables., Conclusions: Key patient variables critical to understanding brain necrosis post-RT were identified, aiding the study of dosimetric impacts and providing treatment confounders and moderators. This pipeline aims to enhance outcome assessments by revealing at-risk patients, offering a versatile tool for broader applications in RT to improve treatment personalization in different disease sites., (©2024 American Association for Cancer Research.)

Objective . To allow the estimation of secondary cancer risks from radiation therapy treatment plans in a comprehensive and user-friendly Monte Carlo (MC) framework. Method . Patient planning computed tomography scans were extended superior-inferior using the International Commission on Radiological Protection's Publication 145 computational mesh phantoms and skeletal matching. Dose distributions were calculated with the TOPAS MC system using novel mesh capabilities and the digital imaging and communications in medicine radiotherapy extension interface. Finally, in-field and out-of-field cancer risk was calculated using both sarcoma and carcinoma risk models with two alternative parameter sets. Result . The TOPAS MC framework was extended to facilitate epidemiological studies on radiation-induced cancer risk. The framework is efficient and allows automated analysis of large datasets. Out-of-field organ dose was small compared to in-field dose, but the risk estimates indicate a non-negligible contribution to the total radiation induced cancer risk. Significance . This work equips the TOPAS MC system with anatomical extension, mesh geometry, and cancer risk model capabilities that make state-of-the-art out-of-field dose calculation and risk estimation accessible to a large pool of users. Furthermore, these capabilities will facilitate further refinement of risk models and sensitivity analysis of patient specific treatment options., (© 2024 Institute of Physics and Engineering in Medicine.)

Objective. To investigate different dosimetric aspects of 90 Y-IsoPet™ intratumoral therapy in canine soft tissue sarcomas, model the spatial spread of the gel post-injection, evaluate absorbed dose to clinical target volumes, and assess dose distributions and treatment efficacy. Approach. Six canine cases treated with 90 Y-IsoPet™ for soft tissue sarcoma at the Veterinary Health Center, University of Missouri are analyzed in this retrospective study. The dogs received intratumoral IsoPet™ injections, following a grid pattern to achieve a near-uniform dose distribution in the clinical target volume. Two dosimetry methods were performed retrospectively using the Monte Carlo toolkit OpenTOPAS: imaging-based dosimetry obtained from post-injection PET/CT scans, and stylized phantom-based dosimetry modeled from the planned injection points to the gross tumor volume. For the latter, a Gaussian parameter with variable sigma was introduced to reflect the spatial spread of IsoPet™. The two methods were compared using dose-volume histograms (DVHs) and dose homogeneity, allowing an approximation of the closest sigma for the spatial spread of the gel post-injection. In addition, we compared Monte Carlo-based dosimetry with voxel S-value (VSV)-based dosimetry to investigate the dosimetric differences. Main results. Imaging-based dosimetry showed differences between Monte Carlo and VSV calculations in tumor high-density areas with higher self-absorption. Stylized phantom-based dosimetry indicated a more homogeneous target dose with increasing sigma. The sigma approximation of the 90 Y-IsoPet™ post-injection gel spread resulted in a median sigma of approximately 0.44 mm across all cases to reproduce the dose heterogeneity observed in Monte Carlo calculations. Significance. The results indicate that dose modeling based on planned injection points can serve as a first-order approximation for the delivered dose in 90 Y-IsoPet™ therapy for canine soft tissue sarcomas. The dosimetry evaluation highlights the non-uniformity of absorbed doses despite the gel spread, emphasizing the importance of considering tumor dose heterogeneity in treatment evaluation. Our findings suggest that using Monte Carlo for dose calculation seems more suitable for this type of tumor where high-density areas might play an important role in dosimetry., (© 2024 Institute of Physics and Engineering in Medicine.)

Objective . To evaluate the pre-treatment and post-treatment imaging-based dosimetry of patients treated with 90Y-microspheres, including accurate estimations of dose to tumor, healthy liver and lung. To do so, the Monte Carlo (MC) TOPAS platform is in this work extended towards its utilization in radionuclide therapy. Approach . Five patients treated at the Massachusetts General Hospital were selected for this study. All patients had data for both pre-treatment SPECT-CT imaging using 99mTc-MAA as a surrogate of the 90Y-microspheres treatment and SPECT-CT imaging immediately after the 90Y activity administration. Pre- and post-treatment doses were computed with TOPAS using the SPECT images to localize the source positions and the CT images to account for tissue inhomoegeneities. We compared our results with analytical calculations following the voxel-based MIRD scheme. Main results . TOPAS results largely agreed with the MIRD-based calculations in soft tissue regions: the average difference in mean dose to the liver was 0.14 Gy GBq -1 (2.6%). However, dose distributions in the lung differed considerably: absolute differences in mean doses to the lung ranged from 1.2 to 6.3 Gy GBq -1 and relative differences from 153% to 231%. We also found large differences in the intra-hepatic dose distributions between pre- and post-treatment imaging, but only limited differences in the pulmonary dose. Significance . Doses to lung were found to be higher using TOPAS with respect to analytical calculations which may significantly underestimate dose to the lung, suggesting the use of MC methods for 90Y dosimetry. According to our results, pre-treatment imaging may still be representative of dose to lung in these treatments., (© 2021 Institute of Physics and Engineering in Medicine.)