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Purpose: In image-guided adaptive brachytherapy (IGABT) a quantitative evaluation of the dosimetric changes between fractions due to anatomical variations, can be implemented via rigid registration of images from subsequent fractions based on the applicator as a reference structure. With available treatment planning systems (TPS), this is a manual and time-consuming process. The aim of this retrospective study was to automate this process. A neural network (NN) was trained to predict the applicator structure from MR images. The resulting segmentation was used to automatically register MR-volumes., Material and Methods: DICOM images and plans of 56 patients treated for cervical cancer with high dose-rate (HDR) brachytherapy were used in the study. A 2D and a 3D NN were trained to segment applicator structures on clinical T2-weighted MRI datasets. Different rigid registration algorithms were investigated and compared. To evaluate a fully automatic registration workflow, the NN-predicted applicator segmentations (AS) were used for rigid image registration with the best performing algorithm. The DICE coefficient and mean distance error between dwell positions (MDE) were used to evaluate segmentation and registration performance., Results: The mean DICE coefficient for the predicted AS was 0.70 ± 0.07 and 0.58 ± 0.04 for the 3D NN and 2D NN, respectively. Registration algorithms achieved MDE errors from 8.1 ± 3.7 mm (worst) to 0.7 ± 0.5 mm (best), using ground-truth AS. Using the predicted AS from the 3D NN together with the best registration algorithm, an MDE of 2.7 ± 1.4 mm was achieved., Conclusion: Using a combination of deep learning models and state of the art image registration techniques has been demonstrated to be a promising solution for automatic image registration in IGABT. In combination with auto-contouring of organs at risk, the auto-registration workflow from this study could become part of an online-dosimetric interfraction evaluation workflow in the future., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [Department of Radiation Oncology at Medical University of Vienna receives financial and/or equipment support for research and educational purposes from Elekta AB. CK, AS and NN received travel support and honoraria for educational activities from Elekta AB. YN is an employee of Elekta AB.], (Copyright © 2022. Published by Elsevier GmbH.)

Purpose: This work aims to simulate clustered DNA damage from ionizing radiation and estimate the relative biological effectiveness (RBE) for radionuclide (rBT)- and electronic (eBT)-based surface brachytherapy through a hybrid Monte Carlo (MC) approach, using realistic models of the sources and applicators., Methods: Damage from ionizing radiation has been studied using the Monte Carlo Damage Simulation algorithm using as input the primary electron fluence simulated using a state-of-the-art MC code, PENELOPE-2018. Two 192 Ir rBT applicators, Valencia and Leipzig, one 60 Co source with a Freiburg Flap applicator (reference source), and two eBT systems, Esteya and INTRABEAM, have been included in this study implementing full realizations of their geometries as disclosed by the manufacturer. The role played by filtration and tube kilovoltage has also been addressed., Results: For rBT, an RBE value of about 1.01 has been found for the applicators and phantoms considered. In the case of eBT, RBE values for the Esteya system show an almost constant RBE value of about 1.06 for all depths and materials. For INTRABEAM, variations in the range of 1.12-1.06 are reported depending on phantom composition and depth. Modifications in the Esteya system, filtration, and tube kilovoltage give rise to variations in the same range., Conclusions: Current clinical practice does not incorporate biological effects in surface brachytherapy. Therefore, the same absorbed dose is administered to the patients independently on the particularities of the rBT or eBT system considered. The almost constant RBE values reported for rBT support that assumption regardless of the details of the patient geometry, the presence of a flattening filter in the applicator design, or even significant modifications in the photon energy spectra above 300 keV. That is not the case for eBT, where a clear dependence on the eBT system and the characteristics of the patient geometry are reported. A complete study specific for each eBT system, including detailed applicator characteristics (size, shape, filtering, among others) and common anatomical locations, should be performed before adopting an existing RBE value., (© 2022 American Association of Physicists in Medicine.)

Purpose: Recently, we introduced a bi-objective optimization approach based on dose-volume indices to automatically create clinically good HDR prostate brachytherapy plans. To calculate dose-volume indices, a reconstruction algorithm is used to determine the 3D organ shape from 2D contours, inevitably containing settings that influence the result. We augment the optimization approach to quickly find plans that are robust to differences in 3D reconstruction., Methods: Studied reconstruction settings were: interpolation between delineated organ contours, overlap between contours, and organ shape at the top and bottom contour. Two options for each setting yields 8 possible 3D organ reconstructions per patient, over which the robust model defines minimax optimization. For the original model, settings were based on our treatment planning system. Both models were tested on data of 26 patients and compared by re-evaluating selected optimized plans both in the original model (1 organ reconstruction, the difference determines the cost), and in the robust model (8 organ reconstructions, the difference determines the benefit)., Results: Robust optimization increased the run time from 3 to 6 min. The median cost for robust optimization as observed in the original model was -0.25% in the dose-volume indices with a range of [-0.01%, -1.03%]. The median benefit of robust optimization as observed in the robust model was 0.93% with a range of [0.19%, 4.16%]. For 4 patients, selected plans that appeared good when optimized in the original model, violated the clinical protocol with more than 1% when considering different settings. This was not the case for robustly optimized plans., Conclusions: Plans of high quality, irrespective of 3D organ reconstruction settings, can be obtained using our robust optimization approach. With its limited effect on total runtime, our approach therefore offers a way to account for dosimetry uncertainties that result from choices in organ reconstruction settings that is viable in clinical practice.

Three different correction factors for measurements with the parallel-plate ionization chamber PTW T34013 on the Esteya electronic brachytherapy unit have been investigated. This chamber type is recommended by AAPM TG-253 for depth-dose measurements in the 69.5 kV x-ray beam generated by the Esteya unit.Monte Carlo simulations using the PENELOPE-2018 system were performed to determine the absorbed dose deposited in water and in the chamber sensitive volume at different depths with a Type A uncertainty smaller than 0.1%. Chamber-to-chamber differences have been explored performing measurements using three different chambers. The range of conical applicators available, from 10 to 30 mm in diameter, has been explored.Using a depth-independent global chamber perturbation correction factor without a shift of the effective point of measurement yielded differences between the absorbed dose to water and the corrected absorbed dose in the sensitive volume of the chamber of up to 1% and 0.6% for the 10 mm and 30 mm applicators, respectively. Calculations using a depth-dependent perturbation factor, including or excluding a shift of the effective point of measurement, resulted in depth-dose differences of about ± 0.5% or less for both applicators. The smallest depth-dose differences were obtained when a shift of the effective point of measurement was implemented, being displaced 0.4 mm towards the center of the sensitive volume of the chamber. The correction factors were obtained with combined uncertainties of 0.4% ( k  = 2). Uncertainties due to chamber-to-chamber differences are found to be lower than 2%.The results emphasize the relevance of carrying out detailed Monte Carlo studies for each electronic brachytherapy device and ionization chamber used for its dosimetry., (Creative Commons Attribution license.)

Purpose: Bi-objective simultaneous optimization of catheter positions and dwell times for high-dose-rate (HDR) prostate brachytherapy, based directly on dose-volume indices, has shown promising results. However, optimization with the state-of-the-art evolutionary algorithm MO-RV-GOMEA so far required several hours of runtime, and resulting catheter positions were not always clinically feasible. The aim of this study is to extend the optimization model and apply GPU parallelization to achieve clinically acceptable computation times. The resulting optimization procedure is compared with a previously introduced method based solely on geometric criteria, the adapted Centroidal Voronoi Tessellations (CVT) algorithm., Methods: Bi-objective simultaneous optimization was performed with a GPU-parallelized version of MO-RV-GOMEA. This optimization of catheter positions and dwell times was retrospectively applied to the data of 26 patients previously treated with HDR prostate brachytherapy for 8-16 catheters (steps of 2). Optimization of catheter positions using CVT was performed in seconds, after which optimization of only the dwell times using MO-RV-GOMEA was performed in 1 min., Results: Simultaneous optimization of catheter positions and dwell times using MO-RV-GOMEA was performed in 5 min. For 16 down to 8 catheters (steps of 2), MO-RV-GOMEA found plans satisfying the planning-aims for 20, 20, 18, 14, and 11 out of the 26 patients, respectively. CVT achieved this for 19, 17, 13, 9, and 2 patients, respectively. The P-value for the difference between MO-RV-GOMEA and CVT was 0.023 for 16 catheters, 0.005 for 14 catheters, and <0.001 for 12, 10, and 8 catheters., Conclusions: With bi-objective simultaneous optimization on a GPU, high-quality catheter positions can now be obtained within 5 min, which is clinically acceptable, but slower than CVT. For 16 catheters, the difference between MO-RV-GOMEA and CVT is clinically irrelevant. For 14 catheters and less, MO-RV-GOMEA outperforms CVT in finding plans satisfying all planning-aims., (© 2020 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

Purpose: The purpose of this study is to improve upon a recently introduced bi-objective treatment planning method for prostate high-dose-rate (HDR) brachytherapy (BT), both in terms of resulting plan quality and runtime requirements, to the extent that its execution time is clinically acceptable., Methods: Bi-objective treatment planning is done using a state-of-the-art multiobjective evolutionary algorithm, which produces a large number of potential treatment plans with different trade-offs between coverage of the target volumes and sparing organs at risk. A graphics processing unit (GPU) is used for large-scale parallelization of dose calculations and the calculation of the dose-volume (DV) indices of potential treatment plans. Moreover, the objectives of the previously used bi-objective optimization model are modified to produce better results., Results: We applied the GPU-accelerated bi-objective treatment planning method to a set of 18 patients, resulting in a set containing a few hundred potential treatment plans with different trade-offs for each of these patients. Due to accelerations introduced in this article, results previously achieved after 1 hour are now achieved within 30 seconds of optimization. We found plans satisfying the clinical protocol for 15 of 18 patients, whereas this was the case for only 4 of 18 clinical plans. Higher quality treatment plans are obtained when the accuracy of DV index calculation is increased using more dose calculation points, requiring still no more than 3 minutes of optimization for 100 000 points., Conclusions: Large sets of high-quality treatment plans that trade-off coverage and sparing are now achievable within 30 seconds, due to the GPU-acceleration of a previously introduced bi-objective treatment planning method for prostate HDR brachytherapy. Higher quality plans can be achieved when optimizing for 3 minutes, which we still consider to be clinically acceptable. This allows for more insightful treatment plan selection in a clinical setting., (© 2019 American Association of Physicists in Medicine.)

Prostate brachytherapy treatment using permanent implantation of low-energy (LE) low-dose rate (LDR) sources is successfully and widely applied in Europe. In addition, seeds are used in other tumour sites, such as ophthalmic tumours, implanted temporarily. The calibration issues for LE-LDR photon emitting sources are specific and different from other sources used in brachytherapy. In this report, the BRAPHYQS (BRAchytherapy PHYsics Quality assurance System) working group of GEC-ESTRO, has developed the present recommendations to assure harmonized and high-quality seed calibration in European clinics. There are practical aspects for which a clarification/procedure is needed, including aspects not specifically accounted for in currently existing AAPM and ESTRO societal recommendations. The aim of this report has been to provide a European wide standard in LE-LDR source calibration at end-user level, in order to keep brachytherapy treatments with high safety and quality levels. The recommendations herein reflect the guidance to the ESTRO brachytherapy users and describe the procedures in a clinic or hospital to ensure the correct calibration of LE-LDR seeds., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

Purpose: To investigate the variation in computed dose-volume (DV) indices for high-dose-rate (HDR) prostate brachytherapy that can result from typical differences in computation settings in treatment planning systems (TPSs)., Methods: Five factors were taken into account: number of dose-calculation points, radioactive source description, interpolation between delineated contours, intersections between delineated organ contours, and organ shape at the top and bottom contour using either full or partial slice thickness. Using in-house developed software, the DV indices of the treatment plans of 26 patients were calculated with different settings, and compared to a baseline setting that closely followed the default settings of the TPS used in our medical center. Studied organs were prostate and seminal vesicles, denoted as targets, and bladder, rectum, and urethra, denoted as organs at risk (OARs), which were delineated on MRI scans with a 3.3 mm slice thickness., Results: When sampling a fixed number of points in each organ, in order to achieve a width of the 95% confidence interval over all patients of the DV indices of 1% or less, only 32,000 points had to be sampled per target, but 256,000 points had to be sampled per OAR. For the remaining factors, DV indices changed up to 0.4% for rectum, 1.3% for urethra, and 2.6% for prostate. DV indices of the bladder changed especially if the high-dose-region was (partly) located at the most caudal contour, up to 8.5%, and DV indices of the vesicles changed especially if there were few delineated contours, up to 9.8%, both due to the use of full slice thickness for the top and bottom contour., Conclusions: The values of DV indices used in prostate HDR brachytherapy treatment planning are influenced by the computation settings in a TPS, especially at the most caudal part of the bladder, as well as in the seminal vesicles., (© 2019 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.)

Purpose: The purpose of this work is threefold: First, to obtain the phase space of an electronic brachytherapy (eBT) system designed for surface skin treatments. Second, to explore the use of some efficiency enhancing (EFEN) strategies in the determination of the phase space. Third, to use the phase space previously obtained to perform a dosimetric characterization of the Esteya eBT system., Methods: The Monte Carlo study of the 69.5 kVp x-ray beam of the Esteya ® unit (Elekta Brachytherapy, Veenendaal, The Netherlands) was performed with PENELOPE2014. The EFEN strategies included the use of variance reduction techniques and mixed Class II simulations, where transport parameters were fine-tuned. Four source models were studied varying the most relevant parameters characterizing the electron beam impinging the target: the energy spectrum (mono-energetic or Gaussian shaped), and the electron distribution over the focal spot (uniform or Gaussian shaped). Phase spaces obtained were analyzed to detect differences in the calculated data due to the EFEN strategy or the source configuration. Depth dose curves and absorbed dose profiles were obtained for each source model and compared to experimental data previously published., Results: In our EFEN strategy, the interaction forcing variance reduction (VRIF) technique increases efficiency by a factor ~20. Tailoring the transport parameters values (C1 and C2) does not increase the efficiency in a significant way. Applying a universal cutoff energy EABS of 10 keV saves 84% of CPU time while showing negligible impact on the calculated results. Disabling the electron transport by imposing an electron energy cutoff of 70 keV (except for the target) saves an extra 8% (losing in the process 1.2% of the photons). The Gaussian energy source (FWHM = 10%, centered at the nominal kVp, homogeneous electron distribution) shows characteristic K-lines in its energy spectrum, not observed experimentally. The average photon energy using an ideal source (mono-energetic, homogeneous electron distribution) was 36.19 ± 0.09 keV, in agreement with the published measured data of 36.2 ± 0.2 keV. The use of a Gaussian-distributed electron source (mono-energetic) increases the penumbra by 50%, which is closer to the measurement results. The maximum discrepancy of the calculated percent depth dose with the corresponding measured values is 4.5% (at the phantom surface, less than 2% beyond 1 mm depth) and 5% (for the 80% of the field) in the dose profile. Our results agree with the findings published by other authors and are consistent within the expected Type A and B uncertainties., Conclusions: Our results agree with the published measurement results within the reported uncertainties. The observed differences in PDD, dose profiles, and photon spectrum come from three main sources of uncertainty: intermachine variations, measurements, and Monte Carlo calculations. It has been observed that a mono-energetic source with a Gaussian electron distribution over the focal spot is a suitable choice to reproduce the experimental data., (© 2018 American Association of Physicists in Medicine.)