On the impact of absorbed dose specification, tissue heterogeneities, and applicator heterogeneities on Monte Carlo-based dosimetry of Ir-192, Se-75, and Yb-169 in conventional and intensity-modulated brachytherapy for the treatment of cervical cancer

Radioprotection Performance Evaluation of 3D-Printed and Conventional Heat-Cured Dental Resins for Radiotherapy Prostheses

3D printing is increasingly used in dentistry, with biocompatible resins playing a key role. This study compared the radioprotective properties of a commonly used 3D-printed resin (Formlabs surgical guide resin) with traditional heat-cured resin and examined the relationship between material thickness and radiation attenuation. The specimens consisted of 3D-printed and heat-cured resin specimens, each measuring 45 × 45 mm2, with five different thicknesses (6, 8, 10, 12, and 14 mm), totaling 100 samples. Both types of resin specimens underwent testing with 150 MU external beam radiation therapy (EBRT) and 400 cGy brachytherapy. Radiation experiments indicated that under EBRT conditions, there were no significant differences in radiation attenuation between the 3D-printed and heat-cured resins across all thickness groups. In brachytherapy, the attenuation of the 3D-printed resin was significantly lower than the heat-cured resin in the 6 mm and 8 mm groups. Specifically, attenuation rates were 48.0 ± 0.7 (3D-printed) vs. 45.2 ± 1.9 (heat-cured) in the 6 mm group, and 39.6 ± 1.3 vs. 37.5 ± 1.1 in the 8 mm group. Both resins showed significant positive linear correlations between thickness and attenuation (p < 0.001) within 6-14 mm. Thus, 3D-printed resin shows promising radioprotective properties and is a viable alternative to traditional heat-cured resin.

RapidBrachyTG43: A Geant4-based TG-43 parameter and dose calculation module for brachytherapy dosimetry

BACKGROUND

The AAPM TG-43U1 formalism remains the clinical standard for dosimetry of low- and high-energy γ $\gamma$ -emitting brachytherapy sources. TG-43U1 and related reports provide consensus datasets of TG-43 parameters derived from various published measured data and Monte Carlo simulations. These data are used to perform standardized and fast dose calculations for brachytherapy treatment planning.

PURPOSE

Monte Carlo TG-43 dosimetry parameters are commonly derived to characterize novel brachytherapy sources. RapidBrachyTG43 is a module of RapidBrachyMCTPS, a Monte Carlo-based treatment planning system, designed to automate this process, requiring minimal user input to prepare Geant4-based Monte Carlo simulations for a source. RapidBrachyTG43 may also perform a TG-43 dose to water-in-water calculation for a plan, substantially accelerating the same calculation performed using RapidBrachyMCTPS's Monte Carlo dose calculation engine.

METHODS

TG-43 parametersS K / A $S_K/A$ , Λ $\Lambda$ ,g L ( r ) $g_L(r)$ , andF ( r , θ ) $F(r,\theta)$ were calculated using three commercial source models, one each of125 $^{125}$ I,192 $^{192}$ Ir, and60 $^{60}$ Co, and were benchmarked to published data. TG-43 dose to water was calculated for a clinical breast brachytherapy plan and was compared to a Monte Carlo dose calculation with all patient tissues, air, and catheters set to water.

RESULTS

TG-43 parameters for the three simulated sources agreed with benchmark datasets within tolerances specified by the High Energy Brachytherapy Dosimetry working group. A gamma index comparison between the TG-43 and Monte Carlo dose-to-water calculations with a dose difference and difference to agreement criterion of 1%/1 mm yielded a 98.9% pass rate, with all relevant dose volume histogram metrics for the plan agreeing within 1%. Performing a TG-43-based dose calculation provided an acceleration of dose-to-water calculation by a factor of 165.

CONCLUSIONS

Determination of TG-43 parameter data for novel brachytherapy sources may now be facilitated by RapidBrachyMCTPS. These parameter datasets and existing consensus or published datasets may also be used to determine the TG-43 dose for a plan in RapidBrachyMCTPS.

Deep learning for high-resolution dose prediction in high dose rate brachytherapy for breast cancer treatment

Objective.Monte Carlo (MC) simulations are the benchmark for accurate radiotherapy dose calculations, notably in patient-specific high dose rate brachytherapy (HDR BT), in cases where considering tissue heterogeneities is critical. However, the lengthy computational time limits the practical application of MC simulations. Prior research used deep learning (DL) for dose prediction as an alternative to MC simulations. While accurate dose predictions akin to MC were attained, graphics processing unit limitations constrained these predictions to large voxels of 3 mm × 3 mm × 3 mm. This study aimed to enable dose predictions as accurate as MC simulations in 1 mm × 1 mm × 1 mm voxels within a clinically acceptable timeframe.Approach.Computed tomography scans of 98 breast cancer patients treated with Iridium-192-based HDR BT were used: 70 for training, 14 for validation, and 14 for testing. A new cropping strategy based on the distance to the seed was devised to reduce the volume size, enabling efficient training of 3D DL models using 1 mm × 1 mm × 1 mm dose grids. Additionally, novel DL architecture with layer-level fusion were proposed to predict MC simulated dose to medium-in-medium (Dm,m). These architectures fuse information from TG-43 dose to water-in-water (Dw,w) with patient tissue composition at the layer-level. Different inputs describing patient body composition were investigated.Main results.The proposed approach demonstrated state-of-the-art performance, on par with the MCDm,mmaps, but 300 times faster. The mean absolute percent error for dosimetric indices between the MC and DL-predicted complete treatment plans was 0.17% ± 0.15% for the planning target volumeV100, 0.30% ± 0.32% for the skinD2cc, 0.82% ± 0.79% for the lungD2cc, 0.34% ± 0.29% for the chest wallD2ccand 1.08% ± 0.98% for the heartD2cc.Significance.Unlike the time-consuming MC simulations, the proposed novel strategy efficiently converts TG-43Dw,wmaps into preciseDm,mmaps at high resolution, enabling clinical integration.

The effect of vaginal cylinder inhomogeneity on the HDR brachytherapy dose calculations using Monte Carlo simulations

PURPOSE

To analytically assess the heterogeneity effect of vaginal cylinders (VC) made of high-density plastics on dose calculations, considering the prescription point (surface or 5 mm beyond the surface), and benchmark the accuracy of a commercial model-based dose calculation (MBDC) algorithm using Monte Carlo (MC) simulations.

METHODS AND MATERIALS

The GEANT4 MC code was used to simulate a commercial 192 Ir HDR source and VC, with diameters ranging from 20 to 35 mm, inside a virtual water phantom. Standard plans were generated from a commercial treatment planning system [TPS-BrachyVision ACUROS (BV)] optimized for a treatment length of 5 cm through two dose calculation approaches: (1) assuming all the environment as water (i.e., Dw,w-MC & Dw,w-TG43 ) and (2) accounting for the heterogeneity of VC applicators (i.e., Dw,w-App-MC & Dw,w-App-MBDC ). The compared isodose lines, and dose & energy difference maps were extracted for analysis. In addition, the dose difference on the peripheral surface, along the applicator and at middle of treatment length, as well as apical tip was evaluated.

RESULTS

The Dw,w-App-MC results indicated that the VC heterogeneity can cause a dose reduction of (up to) % 6.8 on average (for all sizes) on the peripheral surface, translating to 1 mm shrinkage of the isodose lines compared to Dw,w-MC . In addition, the results denoted that BV overestimates the dose on the peripheral surface and apical tip of about 3.7% and 17.9%, respectively, (i.e., Dw,w-App-MBDC vs Dw,w-App-MC ) when prescribing to the surface. However, the difference between the two were negligible at the prescription point when prescribing to 5 mm beyond the surface.

CONCLUSION

The VCs' heterogeneity could cause dose reduction when prescribing dose to the surface of the applicator, and hence increases the level of uncertainty. Thus, reviewing the TG43 results, in addition to ACUROS, becomes prudent, when evaluating the surface coverage at the apex.

75Se - A promising alternative to 192Ir for potential use in the skin cancer brachytherapy: A Monte Carlo simulation study using FLUKA code

This study aimed to evaluate the possibility of utilizing the HDR ⁷⁵Se source for skin cancer brachytherapy. In this work, based on the BVH-20 skin applicator, two cup-shaped applicators, without and with the flattening filter, were modeled. To obtain the optimal flattening filter shape, an approach based on the MC simulation in combination with an analytical estimation was used. Then, the dose distributions for ⁷⁵Se-applicators were generated using MC simulations in water, and their dosimetric characterizations such as flatness, symmetry, and penumbra were evaluated. Furthermore, the radiation leakage in the backside of the applicators was estimated by additional MC simulation. Finally, to evaluate the treatment times, calculations were performed for two ⁷⁵Se-applicators assuming 5 Gy per fraction. The flatness, symmetry, and penumbra values for the ⁷⁵Se-applicator without the flattening filter were estimated to be 13.7%, 1.05, and 0.41 cm respectively. The corresponding values for ⁷⁵Se-applicator with the flattening filter were estimated to be 1.6%, 1.06, and 0.10 cm respectively. The radiation leakage value at a distance of 2 cm from the applicator surface was calculated to be 0.2% and 0.4% for the ⁷⁵Se-applicator without and with the flattening filter respectively. Our results showed that the treatment time for the ⁷⁵Se-applicator is comparable with that of the ¹⁹²Ir-Leipzig applicator. The findings revealed that the dosimetric parameters of the ⁷⁵Se applicator are comparable with the ¹⁹²Ir skin applicator. Overall, the ⁷⁵Se source can be an alternative to ¹⁹²Ir sources for HDR brachytherapy of skin cancer.

Dosimetric impact of a robust optimization approach to mitigate effects from rotational uncertainty in prostate intensity-modulated brachytherapy

BACKGROUND

Intensity-modulated brachytherapy (IMBT) is an emerging technology for cancer treatment, in which radiation sources are shielded to shape the dose distribution. The rotatable shields provide an additional degree of freedom, but also introduce an additional, directional, type of uncertainty, compared to conventional high-dose-rate brachytherapy (HDR BT).

PURPOSE

We propose and evaluate a robust optimization approach to mitigate the effects of rotational uncertainty in the shields with respect to planning criteria.

METHODS

A previously suggested prototype for platinum-shielded prostate ¹⁶⁹ Yb-based dynamic IMBT is considered. We study a retrospective patient data set (anatomical contours and catheter placement) from two clinics, consisting of six patients that had previously undergone conventional ¹⁹² Ir HDR BT treatment. The Monte Carlo-based treatment planning software RapidBrachyMCTPS is used for dose calculations. In our computational experiments, we investigate systematic rotational shield errors of ±10° and ±20°, and the same systematic error is applied to all dwell positions in each scenario. This gives us three scenarios, one nominal and two with errors. The robust optimization approach finds a compromise between the average and worst-case scenario outcomes.

RESULTS

We compare dose plans obtained from standard models and their robust counterparts. With dwell times obtained from a linear penalty model (LPM), for 10° errors, the dose to urethra ( D 0.1 c c $D_{0.1cc}$ ) and rectum ( D 0.1 c c $D_{0.1cc}$ and D 1 c c $D_{1cc}$ ) increase with up to 5% and 7%, respectively, in the worst-case scenario, while with the robust counterpart, the corresponding increases were 3% and 3%. For all patients and all evaluated criteria, the worst-case scenario outcome with the robust approach had lower deviation compared to the standard model, without compromising target coverage. We also evaluated shield errors up to 20° and while the deviations increased to a large extent with the standard models, the robust models were capable of handling even such large errors.

CONCLUSIONS

We conclude that robust optimization can be used to mitigate the effects from rotational uncertainty and to ensure the treatment plan quality of IMBT.