A brief look at model-based dose calculation principles, practicalities, and promise

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Abstract

Model-based dose calculation algorithms (MBDCAs) have recently emerged as potential successors to the highly practical, but sometimes inaccurate TG-43 formalism for brachytherapy treatment planning. So named for their capacity to more accurately calculate dose deposition in a patient using information from medical images, these approaches to solve the linear Boltzmann radiation transport equation include point kernel superposition, the discrete ordinates method, and Monte Carlo simulation. In this overview, we describe three MBDCAs that are commercially available at the present time, and identify guidance from professional societies and the broader peer-reviewed literature intended to facilitate their safe and appropriate use. We also highlight several important considerations to keep in mind when introducing an MBDCA into clinical practice, and look briefly at early applications reported in the literature and selected from our own ongoing work. The enhanced dose calculation accuracy offered by a MBDCA comes at the additional cost of modelling the geometry and material composition of the patient in treatment position (as determined from imaging), and the treatment applicator (as characterized by the vendor). The adequacy of these inputs and of the radiation source model, which needs to be assessed for each treatment site, treatment technique, and radiation source type, determines the accuracy of the resultant dose calculations. Although new challenges associated with their familiarization, commissioning, clinical implementation, and quality assurance exist, MBDCAs clearly afford an opportunity to improve brachytherapy practice, particularly for low-energy sources.

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CITATION STYLE

APA

Sloboda, R. S., Morrison, H., Cawston-Grant, B., & Menon, G. V. (2017, February 28). A brief look at model-based dose calculation principles, practicalities, and promise. Journal of Contemporary Brachytherapy. Termedia Publishing House Ltd. https://doi.org/10.5114/jcb.2017.65849

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