Monte Carlo dosimetry of high dose rate gynecologic interstitial brachytherapy

Personalized brachytherapy dose reconstruction using deep learning

BACKGROUND AND PURPOSE

Accurate calculation of the absorbed dose delivered to the tumor and normal tissues improves treatment gain factor, which is the major advantage of brachytherapy over external radiation therapy. To address the simplifications of TG-43 assumptions that ignore the dosimetric impact of medium heterogeneities, we proposed a deep learning (DL)-based approach, which improves the accuracy while requiring a reasonable computation time.

MATERIALS AND METHODS

We developed a Monte Carlo (MC)-based personalized brachytherapy dosimetry simulator (PBrDoseSim), deployed to generate patient-specific dose distributions. A deep neural network (DNN) was trained to predict personalized dose distributions derived from MC simulations, serving as ground truth. The paired channel input used for the training is composed of dose distribution kernel in water medium along with the full-volumetric density maps obtained from CT images reflecting medium heterogeneity.

RESULTS

The predicted single-dwell dose kernels were in good agreement with MC-based kernels serving as reference, achieving a mean relative absolute error (MRAE) and mean absolute error (MAE) of 1.16 ± 0.42% and 4.2 ± 2.7 × 10^-4 (Gy.sec^-1/voxel), respectively. The MRAE of the dose volume histograms (DVHs) between the DNN and MC calculations in the clinical target volume were 1.8 ± 0.86%, 0.56 ± 0.56%, and 1.48 ± 0.72% for D90, V150, and V100, respectively. For bladder, sigmoid, and rectum, the MRAE of D5cc between the DNN and MC calculations were 2.7 ± 1.7%, 1.9 ± 1.3%, and 2.1 ± 1.7%, respectively.

CONCLUSION

The proposed DNN-based personalized brachytherapy dosimetry approach exhibited comparable performance to the MC method while overcoming the computational burden of MC calculations and oversimplifications of TG-43.

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

PURPOSE

The purpose of this study was to evaluate the impact of dose reporting schemes and tissue/applicator heterogeneities for ¹⁹² Ir-, ⁷⁵ Se-, and ¹⁶⁹ Yb-based MRI-guided conventional and intensity-modulated brachytherapy.

METHODS AND MATERIALS

Treatment plans using a variety of dose reporting and tissue/applicator segmentation schemes were generated for a cohort (n = 10) of cervical cancer patients treated with ¹⁹² Ir-based Venezia brachytherapy. Dose calculations were performed using RapidBrachyMCTPS, a Geant4-based research Monte Carlo treatment planning system. Ultimately, five dose calculation scenarios were evaluated: (a) dose to water in water (D_w,w ); (b) D_w,w taking the applicator material into consideration (D_w,wApp ); (c) dose to water in medium (D_w,m ); (d and e) dose to medium in medium with mass densities assigned either nominally per structure (D_{m,m (Nom)} ) or voxel-by-voxel (D_m,m ).

RESULTS

Ignoring the plastic Venezia applicator (D_w,wApp ) overestimates D_m,m by up to 1% (average) with high energy source (¹⁹² Ir and ⁷⁵ Se) and up to 2% with ¹⁶⁹ Yb. Scoring dose to water (D_w,wApp or D_w,m ) generally overestimates dose and this effect increases with decreasing photon energy. Reporting dose other than D_m,m (or D_{m,m Nom} ) for ¹⁶⁹ Yb-based conventional and intensity-modulated brachytherapy leads to a simultaneous overestimation (up to 4%) of CTV_HR D₉₀ and underestimation (up to 2%) of bladder D_2cc due to a significant dip in the mass-energy absorption ratios at the depths of nearby targets and OARs. Using a nominal mass-density assignment per structure, rather than a CT-derived voxel-by-voxel assignment for MRI-guided brachytherapy, amounts to a dose error up to 1% for all radionuclides considered.

CONCLUSIONS

The effects of the considered dose reporting schemes trend correspondingly between conventional and intensity-modulated brachytherapy. In the absence of CT-derived mass densities, MRI-only-based dosimetry can adequately approximate D_m,m by assigning nominal mass densities to structures. Tissue and applicator heterogeneities do not significantly impact dosimetry for ¹⁹² Ir and ⁷⁵ Se, but do for ¹⁶⁹ Yb; dose reporting must be explicitly defined since D_w,m and D_w,w may overstate the dosimetric benefits.

Model-Based Dose Calculation Algorithms for Brachytherapy Dosimetry

The purpose of this study was to review the limitations of dose calculation formalisms for photon-emitting brachytherapy sources based on the American Association of Physicists in Medicine (AAPM) Task Group No. 43 (TG-43) report and to provide recommendations to transition to model-based dose calculation algorithms. Additionally, an overview of these algorithms and approaches is presented. The influence of tissue and seed/applicator heterogeneities on brachytherapy dose distributions for breast, gynecologic, head and neck, rectum, and prostate cancers as well as eye plaques and electronic brachytherapy treatments were investigated by comparing dose calculations based on the TG-43 formalism and model-based dose calculation algorithms.

On the impact of improved dosimetric accuracy on head and neck high dose rate brachytherapy

PURPOSE

To study the effect of finite patient dimensions and tissue heterogeneities in head and neck high dose rate brachytherapy.

METHODS AND MATERIALS

The current practice of TG-43 dosimetry was compared to patient specific dosimetry obtained using Monte Carlo simulation for a sample of 22 patient plans. The dose distributions were compared in terms of percentage dose differences as well as differences in dose volume histogram and radiobiological indices for the target and organs at risk (mandible, parotids, skin, and spinal cord).

RESULTS

Noticeable percentage differences exist between TG-43 and patient specific dosimetry, mainly at low dose points. Expressed as fractions of the planning aim dose, percentage differences are within 2% with a general TG-43 overestimation except for the spine. These differences are consistent resulting in statistically significant differences of dose volume histogram and radiobiology indices. Absolute differences of these indices are however small to warrant clinical importance in terms of tumor control or complication probabilities.

CONCLUSIONS

The introduction of dosimetry methods characterized by improved accuracy is a valuable advancement. It does not appear however to influence dose prescription or call for amendment of clinical recommendations for the mobile tongue, base of tongue, and floor of mouth patient cohort of this study.

BrachyGuide: a brachytherapy-dedicated DICOM RT viewer and interface to Monte Carlo simulation software

This work presents BrachyGuide, a brachytherapy‐dedicated software tool for the automatic preparation of input files for Monte Carlo simulation from treatment plans exported in DICOM RT format, and results of calculations performed for its benchmarking. Three plans were prepared using two computational models, the image series of a water sphere and a multicatheter breast brachytherapy patient, for each of two commercially available treatment planning systems: BrachyVision and Oncentra Brachy. One plan involved a single source dwell position of an 192Ir HDR source (VS2000 or mHDR‐v2) at the center of the water sphere using the TG43 algorithm, and the other two corresponded to the TG43 and advanced dose calculation algorithm for the multicatheter breast brachytherapy patient. Monte Carlo input files were prepared using BrachyGuide and simulations were performed with MCNP v.6.1. For the TG43 patient plans, the Monte Carlo computational model was manually edited in the prepared input files to resemble TG43 dosimetry assumptions. Hence all DICOM RT dose exports were equivalent to corresponding simulation results and their comparison was used for benchmarking the use of BrachyGuide. Monte Carlo simulation results and corresponding DICOM RT dose exports agree within type A uncertainties in the majority of points in the computational models. Treatment planning system, algorithm, and source specific differences greater than type A uncertainties were also observed, but these were explained by treatment planning system‐related issues and other sources of type B uncertainty. These differences have to be taken into account in commissioning procedures of brachytherapy dosimetry algorithms. BrachyGuide is accurate and effective for use in the preparation of commissioning tests for new brachytherapy dosimetry algorithms as a user‐oriented commissioning tool and the expedition of retrospective patient cohort studies of dosimetry planning.

PACS numbers: 87.53.Bn, 87.53.Jw, 87.55.D‐, 87.55.Qr, 87.55.km, 87.55.K‐

Current state of the art brachytherapy treatment planning dosimetry algorithms

Following literature contributions delineating the deficiencies introduced by the approximations of conventional brachytherapy dosimetry, different model-based dosimetry algorithms have been incorporated into commercial systems for (192)Ir brachytherapy treatment planning. The calculation settings of these algorithms are pre-configured according to criteria established by their developers for optimizing computation speed vs accuracy. Their clinical use is hence straightforward. A basic understanding of these algorithms and their limitations is essential, however, for commissioning; detecting differences from conventional algorithms; explaining their origin; assessing their impact; and maintaining global uniformity of clinical practice.