Dissemin is shutting down on January 1st, 2025

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IOP Publishing, Physics in Medicine & Biology, 8(46), p. 2177-2199

DOI: 10.1088/0031-9155/46/8/310

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Monte Carlo based treatment planning for modulated electron beam radiation therapy

Journal article published in 2001 by Michael C. Lee, Jun Deng ORCID, Jinsheng Li, Steve B. Jiang, C.-M. Ma
This paper is available in a repository.
This paper is available in a repository.

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Postprint: archiving forbidden
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Data provided by SHERPA/RoMEO

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 homogeneous model target and a 2D breast plan are presented. The potential use of this tool in clinical planning is discussed.