In order to ensure the safety and effectiveness of magnetic induction hyperthermia in clinical applications, numerical simulations on the temperature distributions and extent of thermal damage to the targeted regions must be conducted in the preopera

Purpose. Monte Carlo (MC) track structure codes are commonly used for predicting energy deposition and radiation-induced DNA damage at the nanometer scale. Various simulation parameters such as physics model, DNA model, and direct damage threshold have been developed. The differences in adopted parameters lead to disparity in calculation results, which requires quantitative evaluation. Methods. Three simulation configurations were implemented in TOPAS-nBio MC toolkit to investigate the impact of physics models, DNA model, and direct damage threshold on the prediction of energy deposition and DNA damage. Dose point kernels (DPKs) of electrons and nanometer-sized volumes irradiated with electrons, protons, and alpha particles were utilized to evaluate the impact of physics models on energy deposition. Proton irradiation of plasmid DNA was used to investigate the disparity in single-strand break and double-strand break (DSB) yields caused by differences in physics models, DNA models, and direct damage thresholds. Results. Electron DPKs obtained with different physics models show similar trends but different diffusiveness and maximums. Energy deposition distributions in nanometer-sized volumes irradiated with electrons, protons, and alpha particles calculated using different physics models have the same trend although discrepancies can be observed at the lowest and highest energy deposits. Strand breaks from incident protons in DNA plasmids vary with adopted parameters. For the configurations in this study, changing physics model, DNA model, and direct damage threshold can cause differences of up to 57%, 69%, and 15% in DSB yields, respectively. All these simulation results are essentially in agreement with previously published simulation or experimental studies. Conclusion. All the physics models, DNA models, and direct damage thresholds investigated in this study are applicable to predict energy deposition and DNA damage. Although the choice of parameters can lead to disparity in simulation results, which serves as a reference for future studies.

This study aims to develop a method for verifying site-specific and/or beam path specific proton beam range, which could reduce range uncertainty margins and the associated treatment complications. It investigates the range uncertainties from both CT HU to relative stopping power conversion and patient positioning errors for prostate treatment using pelvic-like biological phantoms. Three 25 × 14 × 12 cm ³ phantoms, made of fresh animal tissues mimicking the pelvic anatomies of prostate patients, were scanned with a general electric CT simulator. A 22 cm circular passive scattering beam with 29 cm range and 8 cm modulation width was used to measure the water equivalent path lengths (WEPL) through the phantoms at multiple points using the dose extinction method with a MatriXXPT detector. The measured WEPLs were compared to those predicted by TOPAS simulations and ray-tracing WEPL calculations. For the three phantoms, the WEPL differences between measured and theoretical prediction (WDMT) are below 1.8% for TOPAS, and 2.5% for ray-tracing. WDMT varies with phantom anatomies by about 0.5% for both TOPAS and ray-tracing. WDMT also correlates with the tissue types of a specific treated region. For the regions where the proton beam path is parallel to sharp bone edges, the WDMTs of TOPAS and ray-tracing respectively reach up to 1.8% and 2.5%. For the region where proton beams pass through just soft tissues, the WDMT is mostly less than 1% for both TOPAS and ray-tracing. For prostate treatments, range uncertainty depends on the tissue types within a specific treated region, patient anatomies and the range calculation methods in the planning algorithms. Our study indicates range uncertainty is less than 2.5% for the whole treated region with both ray-tracing and TOPAS, which suggests the potential to reduce the current 3.5% range uncertainty margin used in the clinics by at least 1% even for single-energy CT data.

Background and Purpose: Based on the distortion of the current conformity index (CI) formula in handling multi-target plans, the $V_{TV}$ parameter in the current CI formula has been redefined to more accurately calculate the CI value of multi-target plans, providing a reference for clinical applications. Methods and Materials: Considering the limitations of the current $V_{TV}$ calculation formula in CI proposed by van’t Riet and Paddick, a new $V_{TV}$ has been defined to better reflect the true conformity of the target volume in multi-target planning. We selected 15 breast cancer (BC) plans with PTVsc and PTVcw as the target volumes, and 15 nasopharyngeal carcinoma (NPC) plans with PTVp, PTVn, PTVrpn, PTV1, and PTV2 as target volumes. $V_{TV}^{new}$ and $C{I}_{new}$ were calculated using the proposed formulas, while $V_{TV}^{old}$ and $C{I}_{old}$ were calculated using traditional formulas based on van’t Riet and Paddick. A paired, two-tailed Wilcoxon signed-rank test was conducted to compare $V_{TV}^{new}$ with $V_{TV}^{old}$, and $C{I}_{new}$ with $C{I}_{old}$ across all target volumes. Pearson’s correlation analysis was performed between $C{I}_{new}$ and $C{I}_{old}$. Results: For BC, the $V_{TV}$ values calculated by the two methods for PTVsc and PTVcw showed statistically significant differences; the values calculated in this study were significantly lower than those calculated by van’t Riet and Paddick (p < 0.05). Consequently, the $C{I}_{new}$ values for BC were significantly higher than $C{I}_{old}$. These results were consistent with those for PTVp, PTVn, PTVrpn, and PTV2 in NPC. For PTV1 in NPC, the results calculated by the two formulas were identical. Conclusions: The new $V_{TV}$ calculation formula eliminates the influence of dose spillage from adjacent targets, retaining only the prescription dose range of the specific target under analysis. This makes the calculated CI more reflective of true conformity compared to traditional formulas. We recommend using the proposed formula to calculate CI values for multi-target plans such as those for BC and NPC.

Radiation damage prediction is essential to guarantee the operational reliability of lead halide perovskite detectors deployed in medical imaging, aerospace, and high-energy radiation fields. This work proposes a multi-descriptor model to evaluate proton damage in perovskite detectors, integrating Monte Carlo particle transport with integral nonionizing energy loss (NIEL), damage energy, primary knock-on atom statistics, vacancy distribution, and displacement per atom (DPA). A 10 × 10 × 2 mm3 FAPbBr3 was simulated under monoenergetic 70, 100, 150, 200, and 250 MeV proton beams with 1.0×106 incident protons. The NIEL mass stopping power decreases from 6.47×10−4 to 1.04×10−4 MeV/cm2/g, while vacancy and DPA metrics exhibit distinct energy-dependent behaviors. Irradiation experiments on Bi/FAPbBr3/C devices reveal μτ retentions of 97.2%, 91.5%, and 66.6% at 70, 100, and 150 MeV, accompanied by maximal dark-current deterioration at 150 MeV. Comparative analysis implies that local peak vacancy descriptors may better capture measured degradation trends relative to integral NIEL or total DPA. This study provides a radiation damage prediction model to evaluate the radiation tolerance of perovskite detectors.

Objective. This study extends a DNA damage simulation package to incorporate a biphasic spatiotemporal non-homologous end joining (NHEJ) repair framework. The aim is to predict radiation induced chromosome aberrations for various beam qualities and dose rates from an independent parameter set. Approach. A biphasic NHEJ kinetic model, characterized by fast and slow components with experimentally constrained repair rate constants ( λ _f = 2.48 h ⁻¹ and λ _s = 0.408 h ⁻¹ ) and slow portion ( η _DSB = 19%), was coupled to a DNA end diffusion process ( D = 0.1 μm ² h ⁻¹ ). DNA damage data from Monte Carlo-based biophysical program was used as input, while different types of chromosome aberrations were generated as output. The extended framework was benchmarked against chromosome aberration measurements in human fibroblasts under acute γ -rays, α particles, and chronic low dose-rate γ -ray irradiations. All parameters were obtained from independent measurements without fitting to chromosome aberration data. Model performance was evaluated using the coefficient of determination ( R ² ). Main Results. For acute γ -rays and α particles, the proposed model reproduced the dose-response curves of dicentrics and interstitial deletions with reasonable accuracy, while larger deviations were observed for rings and terminal deletions. The corresponding total-aberration R ² were 0.973 and 0.947. Notably, the inclusion of spatiotemporal repair dynamics substantially improved agreement of rings and terminal deletions for α -particles compared to a pure distance-dependent model. Simulations of chronic γ -ray irradiations reproduced total aberration yields at 6.3 cGy h ⁻¹ with R ² = 0.968, while the 2.8 cGy h ⁻¹ case exhibited notable deviation with R ² = − 0.517. Sensitivity analyses suggested model stability and robustness with all sensitivity coefficients remaining below 1.3. Significance. By integrating spatial diffusion and biphasic repair kinetics, the proposed model provides a quantitative link between microdosimetric energy deposition and macroscopic chromosome aberrations. The approach offers a foundation for mechanistic modeling of relative biological effectiveness in particle therapy.