A radiobiology-based inverse treatment planning method for optimisation of permanent l-125 prostate implants in focal brachytherapy

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.

A statistical, voxelised model of prostate cancer for biologically optimised radiotherapy

Background and purpose

Radiation therapy (RT) is commonly indicated for treatment of prostate cancer (PC). Biologicallyoptimised RT for PC may improve disease-free survival. This requires accurate spatial localisation and characterisation of tumour lesions. We aimed to generate a statistical, voxelised biological model to complement in vivomultiparametric MRI data to facilitate biologically-optimised RT.

Material and methods

Ex vivo prostate MRI and histopathological imaging were acquired for 63 PC patients. These data were co-registered to derive three-dimensional distributions of graded tumour lesions and cell density. Novel registration processes were used to map these data to a common reference geometry. Voxelised statistical models of tumour probability and cell density were generated to create the PC biological atlas. Cell density models were analysed using the Kullback–Leibler divergence to compare normal vs. lognormal approximations to empirical data.

Results

A reference geometry was constructed using ex vivo MRI space, patient data were deformably registered using a novel anatomy-guided process. Substructure correspondence was maintained using peripheral zone definitions to address spatial variability in prostate anatomy between patients. Three distinct approaches to interpolation were designed to map contours, tumour annotations and cell density maps from histology into ex vivo MRI space. Analysis suggests a log-normal model provides a more consistent representation of cell density when compared to a linear-normal model.

Conclusion

A biological model has been created that combines spatial distributions of tumour characteristics from a population into three-dimensional, voxelised, statistical models. This tool will be used to aid the development of biologically-optimised RT for PC patients.

Biologically Targeted Radiation Therapy: Incorporating Patient-Specific Hypoxia Data Derived from Quantitative Magnetic Resonance Imaging

PURPOSE

Hypoxia has been linked to radioresistance. Strategies to safely dose escalate dominant intraprostatic lesions have shown promising results, but further dose escalation to overcome the effects of hypoxia require a novel approach to constrain the dose in normal tissue.to safe levels. In this study, we demonstrate a biologically targeted radiotherapy (BiRT) approach that can utilise multiparametric magnetic resonance imaging (mpMRI) to target hypoxia for favourable treatment outcomes.

METHODS

mpMRI-derived tumour biology maps, developed via a radiogenomics study, were used to generate individualised, hypoxia-targeting prostate IMRT plans using an ultra- hypofractionation schedule. The spatial distribution of mpMRI textural features associated with hypoxia-related genetic profiles was used as a surrogate of tumour hypoxia. The effectiveness of the proposed approach was assessed by quantifying the potential benefit of a general focal boost approach on tumour control probability, and also by comparing the dose to organs at risk (OARs) with hypoxia-guided focal dose escalation (DE) plans generated for five patients.

RESULTS

Applying an appropriately guided focal boost can greatly mitigate the impact of hypoxia. Statistically significant reductions in rectal and bladder dose were observed for hypoxia-targeting, biologically optimised plans compared to isoeffective focal DE plans.

CONCLUSION

Results of this study suggest the use of mpMRI for voxel-level targeting of hypoxia, along with biological optimisation, can provide a mechanism for guiding focal DE that is considerably more efficient than application of a general, dose-based optimisation, focal boost.

Knowledge-based inverse treatment planning for low-dose-rate prostate brachytherapy

PURPOSE

Permanent low-dose-rate brachytherapy is a widely used treatment modality for managing prostate cancer. In such interventions, treatment planning can be a challenging task and requires experience and skills of the planner. We developed a novel knowledge-based (KB) optimization method based on previous treatment plans. The purpose of this method was to generate clinically acceptable plans that do not require extensive manual adjustments in clinical scenarios.

METHODS

Objective functions used in current inverse planning methods are preferably based on spatial invariant dose objectives rather than spatial dose distributions. Therefore, they are prone to return suboptimal plans resulting in time consuming plan adjustments. To overcome this limitation, a KB approach is introduced. The KB model uses the dose distributions of previous clinical plans projected onto a standardized geometry. From those standardized distributions a template plan is generated. The treatment plans were optimized with an in-house developed planning system by solving a constraint inverse optimization problem that mimics the projected template dose plan constraint to DVH metrics. The method is benchmarked under an IRB-approved retrospective study by comparing optimization time, dosimetric performance, and clinical acceptability against current clinical practice. The quality of the KB model is evaluated with a Turing test.

RESULTS

The KB model consists of five high-quality treatment plans. Those plans were selected by one of our experts and showed all desired dosimetric features. After generating the model treatment plans were created with one run of the optimizer for the remaining 20 patients. The optimization time including needle optimization ranged from 6 to 29 s. Based on a Wilcoxon signed rank test the new plans are dosimetrically equivalent to current clinical practice. The Turing test showed that the proposed method generates plans that are equivalent to current clinical practice and that the dose prediction drives the optimization to achieve high-quality treatment plans.

CONCLUSIONS

This study demonstrated that the proposed KB model was able to capture user-specific features in isodose lines which can be used to generate acceptable treatment plans with a single run of the optimization engine in under a minute. This could potentially reduce the time in the operating room and the time a patient is under anesthesia.

Voxel-level biological optimisation of prostate IMRT using patient-specific tumour location and clonogen density derived from mpMRI

AIMS

This study aimed to develop a framework for optimising prostate intensity-modulated radiotherapy (IMRT) based on patient-specific tumour biology, derived from multiparametric MRI (mpMRI). The framework included a probabilistic treatment planning technique in the effort to yield dose distributions with an improved expected treatment outcome compared with uniform-dose planning approaches.

METHODS

IMRT plans were generated for five prostate cancer patients using two inverse planning methods: uniform-dose to the planning target volume and probabilistic biological optimisation for clinical target volume tumour control probability (TCP) maximisation. Patient-specific tumour location and clonogen density information were derived from mpMRI and geometric uncertainties were incorporated in the TCP calculation. Potential reduction in dose to sensitive structures was assessed by comparing dose metrics of uniform-dose plans with biologically-optimised plans of an equivalent level of expected tumour control.

RESULTS

The planning study demonstrated biological optimisation has the potential to reduce expected normal tissue toxicity without sacrificing local control by shaping the dose distribution to the spatial distribution of tumour characteristics. On average, biologically-optimised plans achieved 38.6% (p-value: < 0.01) and 51.2% (p-value: < 0.01) reduction in expected rectum and bladder equivalent uniform dose, respectively, when compared with uniform-dose planning.

CONCLUSIONS

It was concluded that varying the dose distribution within the prostate to take account for each patient's clonogen distribution was feasible. Lower doses to normal structures compared to uniform-dose plans was possible whilst providing robust plans against geometric uncertainties. Further validation in a larger cohort is warranted along with considerations for adaptive therapy and limiting urethral dose.

Progress towards Patient-Specific, Spatially-Continuous Radiobiological Dose Prescription and Planning in Prostate Cancer IMRT: An Overview

Advances in imaging have enabled the identification of prostate cancer foci with an initial application to focal dose escalation, with subvolumes created with image intensity thresholds. Through quantitative imaging techniques, correlations between image parameters and tumour characteristics have been identified. Mathematical functions are typically used to relate image parameters to prescription dose to improve the clinical relevance of the resulting dose distribution. However, these relationships have remained speculative or invalidated. In contrast, the use of radiobiological models during treatment planning optimisation, termed biological optimisation, has the advantage of directly considering the biological effect of the resulting dose distribution. This has led to an increased interest in the accurate derivation of radiobiological parameters from quantitative imaging to inform the models. This article reviews the progress in treatment planning using image-informed tumour biology, from focal dose escalation to the current trend of individualised biological treatment planning using image-derived radiobiological parameters, with the focus on prostate intensity-modulated radiotherapy (IMRT).

Hybrid optimization based on non-coplanar needles for brachytherapy dose planning

PURPOSE

An ideal dose distribution in a target is the ultimate goal of preoperative dose planning. Furthermore, avoiding vital organs or tissues such as blood vessels or bones during the puncture procedure is significant in low-dose-rate brachytherapy. The aim of this work is to develop a hybrid inverse optimization method based on non-coplanar needles to assist the physician during conformal dose planning, which cannot be properly achieved with a traditional coplanar template.

MATERIAL AND METHODS

The hybrid inverse optimization technique include two novel technologies: an inverse optimization algorithm and a dose volume histogram evaluation method. Brachytherapy treatment planning system was designed as an experimental platform. Left lung adenocarcinoma case was used to test the performance of the method in non-coplanar and coplanar needles, and malignant tumor of spine case was involved to test the practical application of this technique. In addition, the optimization time of every test was also recorded.

RESULTS

The proposed method can achieve an ideal dose distribution, avoiding vital organs (bones). In the first experiment, 13 non-coplanar needles and 24 seeds were used to get an ideal dose distribution to cover the target, whereas 11 coplanar needles and 23 seeds were used to cover the same target. In the second experiment, the new method used 22 non-coplanar needles and 65 seeds to cover the target, while 63 seeds and 22 needles were used in the actual operation. In addition, the computation time of the hybrid inverse optimization method was 20.5 seconds in the tumor of 94.67 cm3 by using 22 needles, which was fast enough for clinical application.

CONCLUSIONS

The hybrid inverse optimization method achieved high conformity in the clinical practice. The non-coplanar needle can help to achieve a better dose distribution than the coplanar needle.

Radiobiological parameters in a tumour control probability model for prostate cancer LDR brachytherapy

To provide recommendations for the selection of radiobiological parameters for prostate cancer treatment planning. Recommendations were based on validation of the previously published values, parameter estimation and a consideration of their sensitivity within a tumour control probability (TCP) model using clinical outcomes data from low-dose-rate (LDR) brachytherapy. The proposed TCP model incorporated radiosensitivity (α) heterogeneity and a non-uniform distribution of clonogens. The clinical outcomes data included 849 prostate cancer patients treated with LDR brachytherapy at four Australian centres between 1995 and 2012. Phoenix definition of biochemical failure was used. Validation of the published values from four selected literature and parameter estimation was performed with a maximum likelihood estimation method. Each parameter was varied to evaluate the change in calculated TCP to quantify the sensitivity of the model to its radiobiological parameters. Using a previously published parameter set and a total clonogen number of 196 000 provided TCP estimates that best described the patient cohort. Fitting of all parameters with a maximum likelihood estimation was not possible. Variations in prostate TCP ranged from 0.004% to 0.67% per 1% change in each parameter. The largest variation was caused by the log-normal distribution parameters for α (mean, [Formula: see text], and standard deviation, σ _α ). Based on the results using the clinical cohort data, we recommend a previously published dataset is used for future application of the TCP model with inclusion of a patient-specific, non-uniform clonogen density distribution which could be derived from multiparametric imaging. The reduction in uncertainties in these parameters will improve the confidence in using biological models for clinical radiotherapy planning.

Determining optimal eluter design by modeling physical dose enhancement in brachytherapy

PURPOSE

In situ drug release concurrent with radiation therapy has been proposed to enhance the therapeutic ratio of permanent prostate brachytherapy. Both brachytherapy sources and brachytherapy spacers have been proposed as potential eluters to release compounds, such as nanoparticles or chemotherapeutic agents. The relative effectiveness of the approaches has not been compared yet. This work models the physical dose enhancement of implantable eluters in conjunction with brachytherapy to determine which delivery mechanism provides greatest opportunity to enhance the therapeutic ratio.

MATERIALS AND METHODS

The combined effect of implanted eluters and radioactive sources were modeled in a manner that allowed the comparison of the relative effectiveness of different types of implantable eluters over a range of parameters. Prostate geometry, source, and spacer positions were extracted from treatment plans used for 125 I permanent prostate implants. Compound concentrations were calculated using steady-state solution to the diffusion equation including an elimination term characterized by the diffusion-elimination modulus (ϕb ). Does enhancement was assumed to be dependent on compound concentration up to a saturation concentration (csat ). Equivalent uniform dose (EUD) was used as an objective to determine the optimal configuration of eluters for a range of diffusion-elimination moduli, concentrations, and number of eluters. The compound delivery vehicle that produced the greatest enhanced dose was tallied for points in parameter space mentioned to determine the conditions under whether there are situations where one approach is preferable to the other.

RESULTS

The enhanced effect of implanted eluters was calculated for prostate volumes from 14 to 45 cm3 , ϕb from 0.01 to 4 mm-1 , csat from 0.05 to 7.5 times the steady-state compound concentration released from the surface of the eluter. The number of used eluters (ne ) was simulated from 10 to 60 eluters. For the region of (csat , Φ)-space that results in a large fraction of the gland being maximally sensitized, compound eluting spacers or sources produce equal increase in EUD. In the majority of the remaining (csat , Φ)-space, eluting spacers result in a greater EUD than sources even where sources often produce greater maximal physical dose enhancement. Placing eluting implants in planned locations throughout the prostate results in even greater enhancement than using only source or spacer locations.

CONCLUSIONS

Eluting brachytherapy spacers offer an opportunity to increase EUD during the routine brachytherapy process. Incorporating additional needle placements permits compound eluting spacer placement independent of source placement and thereby allowing a further increase in the therapeutic ratio. Additional work is needed to understand the in vivo spatial distribution of compound around eluters, and to incorporate time dependence of both compound release and radiation dose.

Understanding the Relationship Between Interactive Optimisation and Visual Analytics in the Context of Prostate Brachytherapy

The fields of operations research and computer science have long sought to find automatic solver techniques that can find high-quality solutions to difficult real-world optimisation problems. The traditional workflow is to exactly model the problem and then enter this model into a general-purpose "black-box" solver. In practice, however, many problems cannot be solved completely automatically, but require a "human-in-the-loop" to iteratively refine the model and give hints to the solver. In this paper, we explore the parallels between this interactive optimisation workflow and the visual analytics sense-making loop. We assert that interactive optimisation is essentially a visual analytics task and propose a problem-solving loop analogous to the sense-making loop. We explore these ideas through an in-depth analysis of a use-case in prostate brachytherapy, an application where interactive optimisation may be able to provide significant assistance to practitioners in creating prostate cancer treatment plans customised to each patient's tumour characteristics. However, current brachytherapy treatment planning is usually a careful, mostly manual process involving multiple professionals. We developed a prototype interactive optimisation tool for brachytherapy that goes beyond current practice in supporting focal therapy - targeting tumour cells directly rather than simply seeking coverage of the whole prostate gland. We conducted semi-structured interviews, in two stages, with seven radiation oncology professionals in order to establish whether they would prefer to use interactive optimisation for treatment planning and whether such a tool could improve their trust in the novel focal therapy approach and in machine generated solutions to the problem.

Focal therapy for prostate cancer: the technical challenges

Focal therapy for prostate cancer has been proposed as an alternative treatment to whole gland therapy, offering the opportunity for tumor dose escalation and/or reduced toxicity. Brachytherapy, either low-dose-rate or high-dose-rate, provides an ideal approach, offering both precision in dose delivery and opportunity for a highly conformal, non-uniform dose distribution. Whilst multiple consensus documents have published clinical guidelines for patient selection, there are insufficient data to provide clear guidelines on target volume delineation, treatment planning margins, treatment planning approaches, and many other technical issues that should be considered before implementing a focal brachytherapy program. Without consensus guidelines, there is the potential for a diversity of practices to develop, leading to challenges in interpreting outcome data from multiple centers. This article provides an overview of the technical considerations for the implementation of a clinical service, and discusses related topics that should be considered in the design of clinical trials to ensure precise and accurate methods are applied for focal brachytherapy treatments.