Calcifications in low-dose rate prostate seed brachytherapy treatment: post-planning dosimetry and predictive factors

AAPM Task Group Report 267: A joint AAPM GEC-ESTRO report on biophysical models and tools for the planning and evaluation of brachytherapy

Brachytherapy utilizes a multitude of radioactive sources and treatment techniques that often exhibit widely different spatial and temporal dose delivery patterns. Biophysical models, capable of modeling the key interacting effects of dose delivery patterns with the underlying cellular processes of the irradiated tissues, can be a potentially useful tool for elucidating the radiobiological effects of complex brachytherapy dose delivery patterns and for comparing their relative clinical effectiveness. While the biophysical models have been used largely in research settings by experts, it has also been used increasingly by clinical medical physicists over the last two decades. A good understanding of the potentials and limitations of the biophysical models and their intended use is critically important in the widespread use of these models. To facilitate meaningful and consistent use of biophysical models in brachytherapy, Task Group 267 (TG-267) was formed jointly with the American Association of Physics in Medicine (AAPM) and The Groupe Européen de Curiethérapie and the European Society for Radiotherapy & Oncology (GEC-ESTRO) to review the existing biophysical models, model parameters, and their use in selected brachytherapy modalities and to develop practice guidelines for clinical medical physicists regarding the selection, use, and interpretation of biophysical models. The report provides an overview of the clinical background and the rationale for the development of biophysical models in radiation oncology and, particularly, in brachytherapy; a summary of the results of literature review of the existing biophysical models that have been used in brachytherapy; a focused discussion of the applications of relevant biophysical models for five selected brachytherapy modalities; and the task group recommendations on the use, reporting, and implementation of biophysical models for brachytherapy treatment planning and evaluation. The report concludes with discussions on the challenges and opportunities in using biophysical models for brachytherapy and with an outlook for future developments.

Aleatoric and epistemic uncertainty extraction of patient-specific deep learning-based dose predictions in LDR prostate brachytherapy

Objective.In brachytherapy, deep learning (DL) algorithms have shown the capability of predicting 3D dose volumes. The reliability and accuracy of such methodologies remain under scrutiny for prospective clinical applications. This study aims to establish fast DL-based predictive dose algorithms for low-dose rate (LDR) prostate brachytherapy and to evaluate their uncertainty and stability.Approach.Data from 200 prostate patients, treated with125I sources, was collected. The Monte Carlo (MC) ground truth dose volumes were calculated with TOPAS considering the interseed effects and an organ-based material assignment. Two 3D convolutional neural networks, UNet and ResUNet TSE, were trained using the patient geometry and the seed positions as the input data. The dataset was randomly split into training (150), validation (25) and test (25) sets. The aleatoric (associated with the input data) and epistemic (associated with the model) uncertainties of the DL models were assessed.Main results.For the full test set, with respect to the MC reference, the predicted prostateD90metric had mean differences of -0.64% and 0.08% for the UNet and ResUNet TSE models, respectively. In voxel-by-voxel comparisons, the average global dose difference ratio in the [-1%, 1%] range included 91.0% and 93.0% of voxels for the UNet and the ResUNet TSE, respectively. One forward pass or prediction took 4 ms for a 3D dose volume of 2.56 M voxels (128 × 160 × 128). The ResUNet TSE model closely encoded the well-known physics of the problem as seen in a set of uncertainty maps. The ResUNet TSE rectum D2cchad the largest uncertainty metric of 0.0042.Significance.The proposed DL models serve as rapid dose predictors that consider the patient anatomy and interseed attenuation effects. The derived uncertainty is interpretable, highlighting areas where DL models may struggle to provide accurate estimations. The uncertainty analysis offers a comprehensive evaluation tool for dose predictor model assessment.

A Monte Carlo dose recalculation pipeline for durable datasets: an I-125 LDR prostate brachytherapy use case

Monte Carlo (MC) dose datasets are valuable for large-scale dosimetric studies. This work aims to build and validate a DICOM-compliant automated MC dose recalculation pipeline with an application to the production of I-125 low dose-rate prostate brachytherapy MC datasets. Built as a self-contained application, the recalculation pipeline ingested clinical DICOM-RT studies, reproduced the treatment into the Monte Carlo simulation, and outputted a traceable and durable dose distribution in the DICOM dose format. MC simulations with TG43-equivalent conditions using both TOPAS andegs_brachyMC codes were compared to TG43 calculations to validate the pipeline. The consistency of the pipeline when generating TG186 simulations was measured by comparing simulations made with both MC codes. Finally,egs_brachysimulations were run on a 240-patient cohort to simulate a large-scale application of the pipeline. Compared to line source TG43 calculations, simulations with both MC codes had more than 90% of voxels with a global difference under ±1%. Differences of 2.1% and less were seen in dosimetric indices when comparing TG186 simulations from both MC codes. The large-scale comparison ofegs_brachysimulations with treatment planning system dose calculation seen the same dose overestimation of TG43 calculations showed in previous studies. The MC dose recalculation pipeline built and validated against TG43 calculations in this work efficiently produced durable MC dose datasets. Since the dataset could reproduce previous dosimetric studies within 15 h at a rate of 20 cases per 25 min, the pipeline is a promising tool for future large-scale dosimetric studies.

Modern Tools for Modern Brachytherapy

This review aims to showcase the brachytherapy tools and technologies that have emerged during the last 10 years. Soft-tissue contrast using magnetic resonance and ultrasound imaging has seen enormous growth in use to plan all forms of brachytherapy. The era of image-guided brachytherapy has encouraged the development of advanced applicators and given rise to the growth of individualised 3D printing to achieve reproducible and predictable implants. These advances increase the quality of implants to better direct radiation to target volumes while sparing normal tissue. Applicator reconstruction has moved beyond manual digitising, to drag and drop of three-dimensional applicator models with embedded pre-defined source pathways, ready for auto-recognition and automation. The simplified TG-43 dose calculation formalism directly linked to reference air kerma rate of high-energy sources in the medium water remains clinically robust. Model-based dose calculation algorithms accounting for tissue heterogeneity and applicator material will advance the field of brachytherapy dosimetry to become more clinically accurate. Improved dose-optimising toolkits contribute to the real-time and adaptive planning portfolio that harmonises and expedites the entire image-guided brachytherapy process. Traditional planning strategies remain relevant to validate emerging technologies and should continue to be incorporated in practice, particularly for cervical cancer. Overall, technological developments need commissioning and validation to make the best use of the advanced features by understanding their strengths and limitations. Brachytherapy has become high-tech and modern by respecting tradition and remaining accessible to all.

Acute and late side-effects after low dose-rate brachytherapy for prostate cancer; incidence, management and technical considerations

PURPOSE

To review common reported side effects and complications after primary LDR-BT (monotherapy) and discuss some of the technical aspects that could impact the treatment outcomes.

METHODS AND MATERIALS

A literature search was undertaken using medical subject headings (MeSH) complemented by the authors' personal and institutional expertise.

RESULTS

The reported incidence of acute and late grade 2 or above urinary, bowel and sexual side effects is very variable across the literature. The learning curve and the implant quality have a clear impact on the toxicity outcomes. Being aware of some of the technical challenges encountered during the procedure and ways to mitigate them could decrease the incidence of side effects. Careful planning of seed placement and seed deposition allow sparing of the organs at risk and a lower incidence of urinary and gastro-intestinal toxicity.

CONCLUSIONS

Low dose-rate brachytherapy remains a standard monotherapy treatment in the setting of favorable-risk prostate cancer. High disease control and low long-term toxicities are achievable in expert hands with a good technique.

Prostatic calcifications: Quantifying occurrence, radiodensity, and spatial distribution in prostate cancer patients

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Intraprostatic calcifications are under-recognized and under-reported in imaging.

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Intraprostatic calcifications are common in patients with prostate cancer.

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They commonly occur within tumors or in the vicinity of tumors.

Background

To evaluate the prevalence, density, and distribution of prostate calcification in patients with prostate cancer.

Methods

Patients who underwent both Gallium-68 PSMA PET/CT and MRI of the prostate over the course of a year were selected for analysis. The CT images with visible calcifications within the prostate were included and calcifications automatically isolated using a threshold of 130 HU. The corresponding multiparametric MRI was assessed and the peripheral zone, transition zone, MRI-visible tumor, and urethra manually contoured. The contoured MRI and CT images were registered using rigid registration, and calcifications mapped automatically to the MRI contours.

Results

A total of 85 men (age range 50–88, mean 69 years, standard deviation 7.2 years) were assessed. The mean serum Prostate Specific Antigen PSA was 16.7, range 0.12 to 94.4. Most patients had intermediate-risk disease (68%; Gleason grade group 2 and 3), 26% had high-risk disease (Gleason grade group 4 and 5), and 6% had low-risk disease (Gleason grade group 1). Forty-six patients out of 85 (54%) had intraprostatic calcification. Calcification occurred more in transition zone than the peripheral zone (65% vs. 35%). The mean density of the calcification was 227 HU (min 133, max 1,966 HU). In 12 patients, the calcification was within an MRI-visible tumor, in 24 patients, there were calcifications within a 9 mm distance of the tumor border, and in 9 patients, there were calcifications located between the urethra and tumor.

Conclusions

Calcifications are common in patients with prostate cancer. Their density and location may make them a significant consideration when planning treatment or retreatment with some types of minimally invasive therapy.

Dosimetric and radiobiological investigation of permanent implant prostate brachytherapy based on Monte Carlo calculations

PURPOSE

Permanent implant prostate brachytherapy plays an important role in prostate cancer treatment, but dose evaluations typically follow the water-based TG-43 formalism, ignoring patient anatomy and interseed attenuation. The purpose of this study is to investigate advanced TG-186 model-based dose calculations via retrospective dosimetric and radiobiological analysis for a new patient cohort.

METHODS AND MATERIALS

A cohort of 155 patients treated with permanent implant prostate brachytherapy from The Ottawa Hospital Cancer Centre is considered. Monte Carlo (MC) dose calculations are performed using tissue-based virtual patient models. Dose-volume histogram (DVH) metrics (target, organs at risk) are extracted from 3D dose distributions and compared with those from calculations under TG-43 assumptions (TG43). Equivalent uniform biologically effective dose and tumor control probability are calculated.

RESULTS

For the target, D₉₀ (V₁₀₀) is 136.7 ± 20.6 Gy (85.8% ± 7.8%) for TG43 and 132.8 ± 20.1 Gy (84.1% ± 8.2%) for MC; D₉₀ is 3.0% ± 1.1% lower for MC than TG43. For organs at risk, MC D_1cc = 104.4 ± 27.4 Gy (TG43: 106.3 ± 28.3 Gy) for rectum and 80.8 ± 29.7 Gy (TG43: 78.4 ± 28.4 Gy) for bladder; D_1cc = 185.9 ± 30.2 Gy (TG43: 191.1 ± 32.0 Gy) for urethra. Equivalent uniform biologically effective dose and tumor control probability are generally lower when evaluated using MC doses. The largest dosimetric and radiobiological discrepancies between TG43 and MC are for patients with intraprostatic calcifications, for whom there are low doses (cold spots) in the vicinity of calcifications within the target, identified with MC but not TG43.

CONCLUSIONS

DVH metrics and radiobiological indices evaluated with TG43 are systematically inaccurate by upward of several percent compared with MC patient-specific models. Mean cohort DVH metrics and their MC:TG43 variances are sensitive to patient cohort and clinical practice, underlining the importance of further retrospective MC studies toward widespread clinical adoption of advanced model-based dose calculations.

DVH-Based Inverse Planning Using Monte Carlo Dosimetry for LDR Prostate Brachytherapy

PURPOSE

Inverse planning is an integral part of modern low-dose-rate brachytherapy. Current clinical planning systems do not exploit the total dose information and largely use the American Association of Physicists in Medicine TG-43 dosimetry formalism to ensure clinically acceptable planning times. Thus, suboptimal plans may be derived as a result of TG-43-related dose overestimation and nonconformity with dose distribution requirements. The purpose of this study was to propose an inverse planning approach that can improve planning quality by combining dose-volume information and precision without compromising the overall execution times.

METHODS AND MATERIALS

The dose map was generated by accumulating precomputed Monte Carlo (MC) dose kernels for each candidate source implantation site. The MC computational burden was reduced by using graphics processing unit acceleration, allowing accurate dosimetry calculations to be performed in the intraoperative environment. The proposed dose-volume histogram (DVH) fast simulated annealing optimization algorithm was evaluated using clinical plans that were delivered to 18 patients who underwent low-dose-rate prostate brachytherapy.

RESULTS

Our method generated plans in 37.5 ± 3.2 seconds with similar prostate dose coverage, improved prostate dose homogeneity of up to 6.1%, and lower dose to the urethra of up to 4.0%.

CONCLUSIONS

A DVH-based optimization algorithm using MC dosimetry was developed. The inclusion of the DVH requirements allowed for increased control over the optimization outcome. The optimal plan's quality was further improved by considering tissue heterogeneity.

The influence of tissue composition uncertainty on dose distributions in brachytherapy

BACKGROUND AND PURPOSE

Model-based dose calculation algorithms (MBDCAs) have evolved from serving as a research tool into clinical practice in brachytherapy. This study investigates primary sources of tissue elemental compositions used as input to MBDCAs and the impact of their variability on MBDCA-based dosimetry.

MATERIALS AND METHODS

Relevant studies were retrieved through PubMed. Minimum dose delivered to 90% of the target (D₉₀), minimum dose delivered to the hottest specified volume for organs at risk (OAR) and mass energy-absorption coefficients (μ_en/ρ) generated by using EGSnrc "g" user-code were compared to assess the impact of compositional variability.

RESULTS

Elemental composition for hydrogen, carbon, oxygen and nitrogen are derived from the gross contents of fats, proteins and carbohydrates for any given tissue, the compositions of which are taken from literature dating back to 1940-1950. Heavier elements are derived from studies performed in the 1950-1960. Variability in elemental composition impacts greatly D₉₀ for target tissues and doses to OAR for brachytherapy with low energy sources and less for ¹⁹²Ir-based brachytherapy. Discrepancies in μ_en/ρ are also indicative of dose differences.

CONCLUSIONS

Updated elemental compositions are needed to optimize MBDCA-based dosimetry. Until then, tissue compositions based on gross simplifications in early studies will dominate the uncertainties in tissue heterogeneity.

Dosimetric impact of dual-energy CT tissue segmentation for low-energy prostate brachytherapy: a Monte Carlo study

The purpose of this study is to evaluate the impact of a novel tissue characterization method using dual-energy over single-energy computed tomography (DECT and SECT) on Monte Carlo (MC) dose calculations for low-dose rate (LDR) prostate brachytherapy performed in a patient like geometry. A virtual patient geometry is created using contours from a real patient pelvis CT scan, where known elemental compositions and varying densities are overwritten in each voxel. A second phantom is made with additional calcifications. Both phantoms are the ground truth with which all results are compared. Simulated CT images are generated from them using attenuation coefficients taken from the XCOM database with a 100 kVp spectrum for SECT and 80 and 140Sn kVp for DECT. Tissue segmentation for Monte Carlo dose calculation is made using a stoichiometric calibration method for the simulated SECT images. For the DECT images, Bayesian eigentissue decomposition is used. A LDR prostate brachytherapy plan is defined with ¹²⁵I sources and then calculated using the EGSnrc user-code Brachydose for each case. Dose distributions and dose-volume histograms (DVH) are compared to ground truth to assess the accuracy of tissue segmentation. For noiseless images, DECT-based tissue segmentation outperforms the SECT procedure with a root mean square error (RMS) on relative errors on dose distributions respectively of 2.39% versus 7.77%, and provides DVHs closest to the reference DVHs for all tissues. For a medium level of CT noise, Bayesian eigentissue decomposition still performs better on the overall dose calculation as the RMS error is found to be of 7.83% compared to 9.15% for SECT. Both methods give a similar DVH for the prostate while the DECT segmentation remains more accurate for organs at risk and in presence of calcifications, with less than 5% of RMS errors within the calcifications versus up to 154% for SECT. In a patient-like geometry, DECT-based tissue segmentation provides dose distributions with the highest accuracy and the least bias compared to SECT. When imaging noise is considered, benefits of DECT are noticeable if important calcifications are found within the prostate.

Coupling I-125 permanent implant prostate brachytherapy Monte Carlo dose calculations with radiobiological models

PURPOSE

To investigate the coupling of radiobiological models with patient-specific Monte Carlo (MC) dose calculations for permanent implant prostate brachytherapy (PIPB). To compare radiobiological indices evaluated with different radiobiological models using MC and simulated AAPM TG-43 dose calculations.

METHODS

Three-dimensional dose distributions previously computed using MC techniques with two types of patient models, TG43sim (AAPM TG-43 water-based conditions) and MCDmm (realistic tissues and interseed effects), for 613 PIPB patients are coupled with biological dose and tumour control probability (TCP) models. Two approaches and their extensions are considered to evaluate biological doses, biologically effective dose (BED) and isoeffective dose (IED), as well as two methods to evaluate TCP. Three novel extensions of equivalent uniform biologically effective dose (EUBED) are suggested which consider the spatial distribution of doses within the target volume. Adopted radiobiological model parameter values (α, β, etc) are those suggested by AAPM TG-137, and sensitivity to parameter choice is discussed.

RESULTS

MCDmm dose calculations can reveal low doses in the prostate target volume, due to tissue heterogeneities or inter-seed effects; considering these low doses in EUBED calculations can lower TCP estimates by up to 70%, with largest differences in patients with calcifications. There are large variations in biological doses and TCPs evaluated over the 613 patient cohort for each radiobiological model considered, reflecting the spectrum of physical doses calculated for these patients with either MCDmm or TG43sim. Depending on the model details, BED, IED and EUBED are, on average, 6.0-9.8%, 7.4-9.2% and 1.8-15% higher, respectively, with TG43sim than MCDmm. TCP estimates computed using MCDmm dose distributions are much lower than expected based on past treatment outcome studies, suggesting a need to re-assess model parameters when evaluating radiobiological indices coupled with heterogeneous tissue model-based dose calculations.

CONCLUSIONS

Cohort average differences in biological dose and TCP estimates between radiobiological models are generally larger than differences for any one radiobiological model evaluated with TG43sim or MCDmm dose calculations. However, heterogeneous tissue dose calculations, like MCDmm, can identify clinically-relevant low dose volumes, e.g., in patients with calcifications, which would otherwise be missed with TG-43. In addition to affecting physical dose distributions, these low dose volumes can largely impact radiobiological dose and TCP estimates, which further motivates the clinical implementation of model-based dose calculations for PIPB.

Development of virtual patient models for permanent implant brachytherapy Monte Carlo dose calculations: interdependence of CT image artifact mitigation and tissue assignment

This work investigates and compares CT image metallic artifact reduction (MAR) methods and tissue assignment schemes (TAS) for the development of virtual patient models for permanent implant brachytherapy Monte Carlo (MC) dose calculations. Four MAR techniques are investigated to mitigate seed artifacts from post-implant CT images of a homogeneous phantom and eight prostate patients: a raw sinogram approach using the original CT scanner data and three methods (simple threshold replacement (STR), 3D median filter, and virtual sinogram) requiring only the reconstructed CT image. Virtual patient models are developed using six TAS ranging from the AAPM-ESTRO-ABG TG-186 basic approach of assigning uniform density tissues (resulting in a model not dependent on MAR) to more complex models assigning prostate, calcification, and mixtures of prostate and calcification using CT-derived densities. The EGSnrc user-code BrachyDose is employed to calculate dose distributions. All four MAR methods eliminate bright seed spot artifacts, and the image-based methods provide comparable mitigation of artifacts compared with the raw sinogram approach. However, each MAR technique has limitations: STR is unable to mitigate low CT number artifacts, the median filter blurs the image which challenges the preservation of tissue heterogeneities, and both sinogram approaches introduce new streaks. Large local dose differences are generally due to differences in voxel tissue-type rather than mass density. The largest differences in target dose metrics (D90, V100, V150), over 50% lower compared to the other models, are when uncorrected CT images are used with TAS that consider calcifications. Metrics found using models which include calcifications are generally a few percent lower than prostate-only models. Generally, metrics from any MAR method and any TAS which considers calcifications agree within 6%. Overall, the studied MAR methods and TAS show promise for further retrospective MC dose calculation studies for various permanent implant brachytherapy treatments.