Monte Carlo based treatment planning for modulated electron beam radiation therapy (2024)

Abstract

A Monte Carlo based treatment planning system for modulated electron radiation therapy (MERT) is presented. This new variation of intensity modulated radiation therapy (IMRT) utilizes an electron multileaf collimator (eMLC) to deliver non-uniform intensity maps at several electron energies. In this way, conformal dose distributions are delivered to irregular targets located a few centimetres below the surface while sparing deeper-lying normal anatomy. Planning for MERT begins with Monte Carlo generation of electron beamlets. Electrons are transported with proper in-air scattering and the dose is tallied in the phantom for each beamlet. An optimized beamlet plan may be calculated using inverse-planning methods. Step-and-shoot leaf sequences are generated for the intensity maps and dose distributions recalculated using Monte Carlo simulations. Here, scatter and leakage from the leaves are properly accounted for by transporting electrons through the eMLC geometry. The weights for the segments of the plan are re-optimized with the leaf positions fixed and bremsstrahlung leakage and electron scatter doses included. This optimization gives the final optimized plan. It is shown that a significant portion of the calculation time is spent transporting particles in the leaves. However, this is necessary since optimizing segment weights based on a model in which leaf transport is ignored results in an improperly optimized plan with overdosing of target and critical structures. A method of rapidly calculating the bremsstrahlung contribution is presented and shown to be an efficient solution to this problem. A hom*ogeneous model target and a 2D breast plan are presented. The potential use of this tool in clinical planning is discussed.

Original languageEnglish
Pages (from-to)2177-2199
Number of pages23
JournalPhysics in Medicine and Biology
Volume46
Issue number8
DOIs
StatePublished - 2001
Externally publishedYes

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Lee, M. C., Deng, J., Li, J., Jiang, S. B. (2001). Monte Carlo based treatment planning for modulated electron beam radiation therapy. Physics in Medicine and Biology, 46(8), 2177-2199. https://doi.org/10.1088/0031-9155/46/8/310

Lee, Michael C. ; Deng, Jun ; Li, Jinsheng et al. / Monte Carlo based treatment planning for modulated electron beam radiation therapy. In: Physics in Medicine and Biology. 2001 ; Vol. 46, No. 8. pp. 2177-2199.

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abstract = "A Monte Carlo based treatment planning system for modulated electron radiation therapy (MERT) is presented. This new variation of intensity modulated radiation therapy (IMRT) utilizes an electron multileaf collimator (eMLC) to deliver non-uniform intensity maps at several electron energies. In this way, conformal dose distributions are delivered to irregular targets located a few centimetres below the surface while sparing deeper-lying normal anatomy. Planning for MERT begins with Monte Carlo generation of electron beamlets. Electrons are transported with proper in-air scattering and the dose is tallied in the phantom for each beamlet. An optimized beamlet plan may be calculated using inverse-planning methods. Step-and-shoot leaf sequences are generated for the intensity maps and dose distributions recalculated using Monte Carlo simulations. Here, scatter and leakage from the leaves are properly accounted for by transporting electrons through the eMLC geometry. The weights for the segments of the plan are re-optimized with the leaf positions fixed and bremsstrahlung leakage and electron scatter doses included. This optimization gives the final optimized plan. It is shown that a significant portion of the calculation time is spent transporting particles in the leaves. However, this is necessary since optimizing segment weights based on a model in which leaf transport is ignored results in an improperly optimized plan with overdosing of target and critical structures. A method of rapidly calculating the bremsstrahlung contribution is presented and shown to be an efficient solution to this problem. A hom*ogeneous model target and a 2D breast plan are presented. The potential use of this tool in clinical planning is discussed.",

author = "Lee, {Michael C.} and Jun Deng and Jinsheng Li and Jiang, {Steve B.} and Ma, {C. M.}",

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Lee, MC, Deng, J, Li, J, Jiang, SB 2001, 'Monte Carlo based treatment planning for modulated electron beam radiation therapy', Physics in Medicine and Biology, vol. 46, no. 8, pp. 2177-2199. https://doi.org/10.1088/0031-9155/46/8/310

Monte Carlo based treatment planning for modulated electron beam radiation therapy. / Lee, Michael C.; Deng, Jun; Li, Jinsheng et al.
In: Physics in Medicine and Biology, Vol. 46, No. 8, 2001, p. 2177-2199.

Research output: Contribution to journalArticlepeer-review

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T1 - Monte Carlo based treatment planning for modulated electron beam radiation therapy

AU - Lee, Michael C.

AU - Deng, Jun

AU - Li, Jinsheng

AU - Jiang, Steve B.

AU - Ma, C. M.

PY - 2001

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N2 - A Monte Carlo based treatment planning system for modulated electron radiation therapy (MERT) is presented. This new variation of intensity modulated radiation therapy (IMRT) utilizes an electron multileaf collimator (eMLC) to deliver non-uniform intensity maps at several electron energies. In this way, conformal dose distributions are delivered to irregular targets located a few centimetres below the surface while sparing deeper-lying normal anatomy. Planning for MERT begins with Monte Carlo generation of electron beamlets. Electrons are transported with proper in-air scattering and the dose is tallied in the phantom for each beamlet. An optimized beamlet plan may be calculated using inverse-planning methods. Step-and-shoot leaf sequences are generated for the intensity maps and dose distributions recalculated using Monte Carlo simulations. Here, scatter and leakage from the leaves are properly accounted for by transporting electrons through the eMLC geometry. The weights for the segments of the plan are re-optimized with the leaf positions fixed and bremsstrahlung leakage and electron scatter doses included. This optimization gives the final optimized plan. It is shown that a significant portion of the calculation time is spent transporting particles in the leaves. However, this is necessary since optimizing segment weights based on a model in which leaf transport is ignored results in an improperly optimized plan with overdosing of target and critical structures. A method of rapidly calculating the bremsstrahlung contribution is presented and shown to be an efficient solution to this problem. A hom*ogeneous model target and a 2D breast plan are presented. The potential use of this tool in clinical planning is discussed.

AB - A Monte Carlo based treatment planning system for modulated electron radiation therapy (MERT) is presented. This new variation of intensity modulated radiation therapy (IMRT) utilizes an electron multileaf collimator (eMLC) to deliver non-uniform intensity maps at several electron energies. In this way, conformal dose distributions are delivered to irregular targets located a few centimetres below the surface while sparing deeper-lying normal anatomy. Planning for MERT begins with Monte Carlo generation of electron beamlets. Electrons are transported with proper in-air scattering and the dose is tallied in the phantom for each beamlet. An optimized beamlet plan may be calculated using inverse-planning methods. Step-and-shoot leaf sequences are generated for the intensity maps and dose distributions recalculated using Monte Carlo simulations. Here, scatter and leakage from the leaves are properly accounted for by transporting electrons through the eMLC geometry. The weights for the segments of the plan are re-optimized with the leaf positions fixed and bremsstrahlung leakage and electron scatter doses included. This optimization gives the final optimized plan. It is shown that a significant portion of the calculation time is spent transporting particles in the leaves. However, this is necessary since optimizing segment weights based on a model in which leaf transport is ignored results in an improperly optimized plan with overdosing of target and critical structures. A method of rapidly calculating the bremsstrahlung contribution is presented and shown to be an efficient solution to this problem. A hom*ogeneous model target and a 2D breast plan are presented. The potential use of this tool in clinical planning is discussed.

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Lee MC, Deng J, Li J, Jiang SB, Ma CM. Monte Carlo based treatment planning for modulated electron beam radiation therapy. Physics in Medicine and Biology. 2001;46(8):2177-2199. doi: 10.1088/0031-9155/46/8/310

Monte Carlo based treatment planning for modulated electron beam radiation therapy (2024)

FAQs

What is the basic principle of Monte Carlo in radiotherapy? ›

The Monte Carlo techniques are based on the transport of each individual particle (e.g., photon or electron) in the tissue. The transport of the particle is done using the physics of the interaction of the particles with matter. Other techniques transport the particles as a group.

How is treatment planned for imrt? ›

Planning IMRT

You begin with a CT scan at the radiotherapy department. You may also have MRI scans or PET scans. The information from these scans feeds directly into the radiotherapy planning computer. The treatment team carefully plans the treatment using the scan images.

What is Monte Carlo radiation? ›

Monte Carlo (MC) simulations play an important role in radiotherapy, especially as a method to evaluate physical properties that are either impossible or difficult to measure. For example, MC simulations (MCSs) are used to aid in the design of radiotherapy devices or to understand their properties.

What is the electron Monte Carlo algorithm? ›

eMC is a macro Monte Carlo (MC) code used to simulate the transport of electrons through a medium to calculate dose distributions within the human body. The algorithm consists of two components: a transport and an electron beam source model.

What is Monaco in radiotherapy? ›

High-precision treatment planning for radiation therapy

Monaco 6 delivers intuitive planning functionality for a broad range of treatments, from 3D conformal to stereotactic techniques, with integrated MOSAIQ® data management, auto-planning and unique proton planning capabilities.

What is the Monte Carlo method for radiative transfer? ›

The Monte Carlo method solves the radiative transfer equation (RTE) by simulating large ensembles of photon events represented by random samples from probability density functions (Ertürk and Howell, 2017).

What is the downside of IMRT? ›

What are the disadvantages of IMRT? Although there's a reduced risk that IMRT will damage healthy cells, it can still cause side effects. Also, while IMRT is a fairly quick procedure to deliver, because it's complex, it may take slightly more time to plan than other external beam radiation therapy types.

What is the success rate of IMRT radiotherapy? ›

Several studies have reported the survival rates in head and neck cancer patients after IMRT, and the reported 2- or 3-year overall survival rates range from 67% to 92.1%, the locoregional progression-free survival rates range from 64% to 87%, and the distant metastasis-free survival rates range from 76.3% to 92.7%, ...

What is the difference between radiation therapy and IMRT? ›

Intensity-modulated radiation therapy, also called IMRT, is an advanced type of radiation therapy. Radiation therapy uses powerful energy beams to kill cancer cells. The energy can come from X-rays, protons or other sources. With IMRT, the beams of radiation are carefully customized.

Why is Monte-Carlo used? ›

A Monte Carlo simulation is a model used to predict the probability of a variety of outcomes when the potential for random variables is present. Monte Carlo simulations help to explain the impact of risk and uncertainty in prediction and forecasting models.

What is the Monte-Carlo risk? ›

Monte Carlo simulation performs risk analysis by building models of possible results by substituting a range of values—called a probability distribution—for any factor that has inherent uncertainty.

Why is Monte Carlo simulation called Monte-Carlo? ›

The Monte Carlo Method was invented by John von Neumann and Stanislaw Ulam during World War II to improve decision making under uncertain conditions. It was named after a well-known casino town, called Monaco, since the element of chance is core to the modeling approach, similar to a game of roulette.

What is an example of a Monte Carlo method? ›

One simple example of a Monte Carlo Simulation is to consider calculating the probability of rolling two standard dice. There are 36 combinations of dice rolls. Based on this, you can manually compute the probability of a particular outcome.

Can Excel do Monte Carlo simulation? ›

A Monte Carlo simulation can be developed using Microsoft Excel and a game of dice. A Monte Carlo simulation is a method for modeling probabilities by using random numbers to approximate and simulate possible outcomes. Today, it is widely used as an analysis tool.

What are the principles of Monte Carlo simulation? ›

A Monte Carlo analysis consists of input variables, output variables, and a mathematical model. The computer system feeds independent variables into a mathematical model, simulates them, and produces dependent variables.

What is the Monte Carlo method of dosimetry? ›

The use of the Monte Carlo method to simulate radiation transport has for decades been considered as the most accurate means of predicting absorbed dose distributions and other quantities of interest in the radiation treatment of cancer patients using either external or radionuclide radiotherapy.

What are the basic principles of radiation therapy? ›

Radiation therapy, general principles. Cell survival, single fraction. Repeated small doses of radiation are less damaging to a sensitive cell than a single fraction containing an equivalent total dose (see the image below). Manipulation of the cellular environment can alter the shape of the survival curve.

On which of the following principles does the Monte Carlo simulation model rely on? ›

Monte Carlo simulation is a type of simulation that relies on repeated random sampling and statistical analysis to compute the results. This method of simulation is very closely related to random experiments, experiments for which the specific result is not known in advance.

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