Index of content:
Volume 36, Issue 6, June 2009
- SAM Therapy Symposium: Ballroom B
- CE ‐ Therapy: Dose Calculation Algorithms in 3D‐CRT and IMRT
36(2009); http://dx.doi.org/10.1118/1.3182301View Description Hide Description
Accurate photondose calculation models are today mainly based on dose calculation algorithms in which the dose distribution is predicted from first principles, i.e. model based algorithms. Basically a convolution is performed between the energy released in each voxel and a dose spread kernel. Due to limitations in computer speed and incomplete physics approximations have been introduced. They are to a first level the pencil beam convolution models and secondly the collapsed cone convolution models. This lecture will present these models and discuss the pros and cons for them and when possible also discuss the individual implementations in commercial treatment planning systems.
The models covered are pencil beam models which today still are the basis for most dose calculations in 3DCRT and IMRT optimisations. Secondly, the new pencil beam implementation including modelling of changes in electron transport especially in the lateral direction will be discussed. Finally the highly accurate collapsed cone models will be covered which produce results of the same quality as Monte Carlo simulations. The latter approach is not the topic of this first part of the lecture, however, it will be used to benchmark results from model based algorithms and to highlight limitations of these.
1. To provide an educational review of the physics and techniques behind model based algorithms e.g. convolution/superpositioning models.
2. To review the methods used to improve the simulation efficiency i.e. pencil beam and collapsed cone convolutions.
3. To briefly review the vendor codes currently used for clinical treatment planning.
4. To briefly review the potential clinical implications of accurate calculated dose distributions.
36(2009); http://dx.doi.org/10.1118/1.3182303View Description Hide Description
Accurate dose calculation is essential to the success of modern radiation therapy especially for treatment planning involving heterogeneous patient anatomy. This presentation will facilitate participants with the clinical implementation and application of Monte Carlodose calculation algorithms in treatment planning and dosimetry verification for advanced radiation therapytreatments. Following a brief introduction to the Monte Carlo method for radiation transport and radiotherapy applications we will discuss the radiotherapy process and the dose calculation requirements for treatment planning. Detailed descriptions will be given of the important steps and procedures for the clinical implementation and commissioning of Monte Carlodose calculation software including clinical accelerator simulation, radiationsource modeling, clinical beam commissioning, patient CT data conversion, beam modifier simulation, patient dose calculation, dose display and statistical analysis for Monte Carlodose calculation. We will also discuss a few issues that are Monte Carlo specific such as dose prescription, energy cutoff values for Monte Carlo electron transport, voxel size effect on dose calculation accuracy and techniques to improve computation efficiency. Finally, we will describe the current status of commercially available Monte Carlodose calculation systems for radiotherapytreatment planning.
- CE ‐ Therapy: HDR and LDR Brachytherapy: Everything You Need to Know
36(2009); http://dx.doi.org/10.1118/1.3182585View Description Hide Description
The development of Brachytherapy began about 1899 following the purification of radium by Pierre and Marie Curie and has been developing rapidly and continually since. The focus of this presentation will be on the most common current utilizations and aspects that present new and controversial issues: brachytherapy applications in breast, prostate, intra‐operative lung and for macular degeneration; electronic brachytherapy, error management and reduction; and some quality management issues. The discussion will consider how the physical nature of brachytherapy enhances and limits the treatments. A list of resources will be provided covering the basics and history of Brachytherapy.
1. Compare and contrast the advantages of LDR vs. HDR in the treatment of prostate cancer
2. Compare electronic brachytherapy to traditional brachytherapy
3. Review the more recent brachytherapy options for the treatment of breast cancer
4. Introduce brachytherapy for intra‐operative lung and macular degeneration
5. Review management of errors and reporting in brachytherapy and how to perform a root cause analysis
6. Review guidelines for quality assurance
- CE ‐ Therapy: Image Processing
36(2009); http://dx.doi.org/10.1118/1.3182439View Description Hide Description
Acquisition, processing and analysis of medical image data are now fundamental parts of patient management in radiation therapy.Image data are used to aid diagnosis and staging, to guide treatment planning and delivery and to help monitor the patient during and after therapy. Most radiotherapy departments have dedicated CT scanners, some with 4D capabilities. Many departments also have or are contemplating dedicated MR and PET/CT scanners. More imaging devices are also appearing in the treatment room, with in‐room, on‐board and integrated imaging devices becoming commonplace. The availability of hybrid MR scanner/treatment units is not far off.
Naturally, each imaging modality provides both benefits and challenges towards supporting and improving the radiotherapy process. In order to leverage the information in the various imaging studies, effective processing tools are needed to extract useful information and to combine and present it in a way that promotes a clear and efficient workflow. There are several classes of these tools including image enhancement, visualization, segmentation, registration and quantification. These tools may be used individually or in combination at many points in the radiotherapy process with the overall goal to create a more complete and accurate model of the patient so that an effective course of therapy can be devised and carried out.
This course provides an overview of the different imaging modalities and procedures used in radiotherapy and highlights the benefits and challenges of each. A detailed description of the various image processing tools used to extract, combine and analyze the information from different imaging studies is also presented. Finally, the effective use of these tools at each step of the radiotherapy process is described and elucidated using numerous clinical examples.
1. Act 1 Understand the benefits and challenges of the various imaging modalities used in radiation therapy.
2. Act 2 Understand the mechanics of the different classes of image processing tools using in radiotherapy.
3. Act 3 Understand how image processing tools are used to support and improve the radiotherapy process.
- CE ‐ Therapy: Particle Therapy: Issues and Considerations
36(2009); http://dx.doi.org/10.1118/1.3182187View Description Hide Description
The relative biological effectiveness (RBE) is defined as the ratio of the doses required by two radiations to cause the same level of effect. Thus, the RBE depends on the dose and the biological endpoint.
Proton therapy has been based on the use of a generic RBE of 1.1, which is applied to all treatments independent of dose/fraction, position in the irradiated volume, initial beam energy or the particular tissue. The variability of RBE in clinical situations is believed to be within 10% but quantitative dependencies of the RBE on various physical and biological properties are disregarded. The magnitude of RBE values and their variations is significantly larger for Carbon ion therapy. Studies have demonstrated significant RBE values of more than 3 in clinically relevant scenarios for Carbon ions. Further, there might be considerable variations in RBE within the irradiated volume that are being considered in treatment planning and delivery.
Heavy ions have a potential advantage compared to protons when it comes to their therapeutic ratio due to an elevated RBE in the tumor (based on the oxygen enhancement ratio and higher average LET values) compared to the surrounding tissue. However, on the other hand, at present there are still considerable uncertainties in heavy ion RBE values. Elevated RBE values (even for protons) might be expected particularly near the edges of the high‐dose volume because doses may be deposited by high‐LET particles. The increase in RBE as a function of depth in the patient results in an extension of the bio‐effective range of the beam. Further, because RBE values may increase with deceasing dose causing elevated RBE values for organs at risk compared to the target area. In order to incorporate detailed RBE modeling in treatment planning as a function of LET, dose and endpoint, two aspects have to be considered. Firstly, the available information from experimental studies and secondly, our ability to calculate RBE values for a given treatment plan based on parameters extracted from such experiments. RBE values are often based on cell survival data because this is the main endpoint of interest in radiation therapy. However, one migt expect differences in RBE for cell survival compared to cell mutation, the latter being an important endpoint for late effects.
This educational session will focus on summarizing the mechanisms behind RBE variations among treatment modalities. Further, RBE variations as a function of LET, tissue and dose will be presented based on experimental and simulated data for proton and Carbon ion beams. Finally, different approaches for theoretical modeling of RBE values for treatment planning purposes will be discussed briefly.
1. Understand the mechanisms behind heavy charged particle RBE values
2. Understand the variations of RBE as a function of physical and biological parameters
3. Understand the clinical implication of RBE values in proton and Carbon ion therapy
36(2009); http://dx.doi.org/10.1118/1.3182188View Description Hide Description
The dose localization advantages of proton beams derive primarily from the Bragg peak in the proton stopping distribution. Therefore, the potential clinical gains expected form proton beams are based on physical, rather than biological, considerations. The rationale for proton therapy is based on the hypothesis that the superior dose distributions of proton beams will lead to increased local control; increased disease‐free survival; decreased treatment‐related morbidity; and improved quality of life. The degree to which each of these end‐points can be changed by proton therapy will depend upon the particular disease site, patient population, and other factors. In the last few years there has been a significant increase in interest in proton therapy and as a consequence, many new facilities are being planned and built. There are currently over 25 institutions worldwide treating patients with proton beams and over 55,000 patients have been treated. There are at least 25 new facilities in various stages of planning and building. We will discuss the rationale for proton therapy, the current status of proton therapy,proton physics and dosimetry, and technology for the acceleration and delivery of proton beams. We will also discuss new developments in proton therapy accelerators and treatmentdelivery systems. Technologies for carbon ion therapy will also be discussed. We will address issues related to the cost of protontreatments relative to the cost of photontreatments and discuss various ways in which the cost of proton therapy can be decreased.
1. rationale for proton therapy;
2. current status of proton therapy;
3. physical characteristics of proton beams;
4. beam production and treatmentdelivery technology for proton beams;
5. acceptance testing and clinical commissioning of proton therapy beams; and
6. QA for protontreatments
36(2009); http://dx.doi.org/10.1118/1.3182189View Description Hide Description
The use of protons for radiation therapy offers theoretical advantages compared to external beam photonradiotherapy. It enables lowering of the integral dose to the patient due to the finite range of protons. However, proton therapy is less tolerant than photon therapy to uncertainties in both treatment planning and treatment delivery. For example, tissue inhomogeneity has a greater effect on protondose distributions than on photondose distributions. In planning proton therapy, the density of tissue along the proton path must be precisely determined and accounted for in order to obtain the required proton energy distribution to achieve the planned dose distribution in the patient. Failure to allow for a zone of higher density could result in a near zero dose in a distal segment of the target volume due to the reduced range of the protons. In contrast, for photons, because of their different energy loss processes, an increased density would cause only a modest lowering of the dose distal to the higher density region. Conversely, neglecting to account for an air cavity upstream of the target volume would, for proton beams; result in a high dose being deposited in distal normal structures while only a modestly increased dose would be deposited in the case of photon beams. Furthermore, motion and mis‐registration of the target volume with the radiation beams have far more severe consequences in proton therapy compared to photon therapy. If the target volumes are to be adequately irradiated, and adjacent OARs are to be protected in proton therapy, it is essential: that the causes and possible magnitudes of motion and mis‐registration are understood; that their possible consequences are understood; that measures are taken to minimize motion and mis‐registration to the extent possible and clinically warranted.
In proton therapytreatment planning uncertainties arise from several sources that include; dose calculation approximations, biological considerations, setup and anatomical variations, and internal movements of low and high density organs into the beam path. Organ motion also has a major impact on the proton range, which is managed by adding a distal safety margin. These margins reduce the benefit of proton therapy in treatment sites where the physical properties of protons could make a significant difference, such as lung cancer. Therefore, it is important to understand the sources of uncertainties in proton therapy quantify their magnitude and develop mitigation and/or minimization strategies.
The focus of this presentation is to; a) understand the potential sources of dosimetric uncertainties in proton therapy b) evaluate the impact of these uncertainties on the accuracy and conformity of dosedelivered to patients and c) suggest potential strategies that translate physical advantage of proton therapy into a maximized dosimetric benefit in the patient.
1. Explain the state‐of‐the‐art in proton therapytreatment planning.
2. Describe the need for knowing potential sources of treatment planning and delivery uncertainties in proton therapy.
3. Summarize strategies to mitigate proton therapydosimetric uncertainties.