PubMed Health⌕ Search

PubMed · 10071883

Intensity modulation methods for proton radiotherapy.

Abstract

The characteristic Bragg peak of protons or heavy ions provides a good localization of dose in three dimensions. Through their ability to deliver laterally and distally shaped homogenous fields, protons have been shown to be a precise and practical method for delivering highly conformal radiotherapy. However, in an analogous manner to intensity modulation for photons, protons can be used to construct dose distributions through the application of many individually inhomogeneous fields, but with the localization of dose in the Bragg peak providing the possibility of modulating intensity within each field in two or three dimensions. We describe four different methods of intensity modulation for protons and describe how these have been implemented in an existing proton planning system. As a preliminary evaluation of the efficacy of these methods, each has been applied to an example case using a variety of field combinations. Dose-volume histogram analysis of the resulting dose distributions shows that when large numbers of fields are used, all techniques exhibit both good target homogeneity and sparing of neighbouring critical structures, with little difference between the four techniques being discerned. As the number of fields is decreased, however, only a full 3D modulation of individual Bragg peaks can preserve both target coverage and sparing of normal tissues. We conclude that the 3D method provides the greatest flexibility for constructing conformal doses in challenging situations, but that when large numbers of beam ports are available, little advantage may be gained from the additional modulation of intensity in depth.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

A Lomax. 1999. Intensity modulation methods for proton radiotherapy.. https://doi.org/10.1088/0031-9155%2F44%2F1%2F014

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

A conceptual model for describing decision-making situations in integrated natural resource planning and modeling projects.

A conceptual model is developed herein for the purpose of stimulating discussions within groups planning and carrying out integrated natural resource projects. We first describe four basic components of integrated planning and modeling efforts: people, databases, technology, and organizational commitment. Second, we provide one view of the relationship between the size of the project's decision-making body and the timing of decisions during a project's life cycle. Finally, these two discussions are combined into a conceptual model describing the dynamic nature of decision-making within integrated projects. The abstractions and generalizations described here are not unique to private industry or governmental organizations and should provide the basis for a discussion of decision-making issues among interdisciplinary professionals embarking on large-scale or complex modeling efforts.

Computing Methodologies↗

Sequence alignment: an approximation law for the Z-value with applications to databank scanning.

The Z-value is an attempt to estimate the statistical significance of a Smith and Waterman dynamic programming alignment score (H-score) through the use of a Monte-Carlo procedure. In this paper, we give an approximation for the Z-value law deduced from the Poisson clumping heuristic developed by Waterman and Vingron (Stat. Sci. 9 (1994) 367) in the case of independent and identically distributed sequences comparison. As for non-gapped alignment scores, our approximation is of Gumbel type but with parameters that are sequence independent. This result makes clear the related experimental results mentioned by Comet et al. (Comput. Chem. 23 (1999) 317). Using 'quasi-real' sequences (i.e. randomly shuffled sequences of the same length and amino acid composition as the real ones) we investigate the relevance of our approximation result. Since the Monte-Carlo approach we use generates a bias for the Gumbel decay parameter estimation, a correction procedure is proposed. Applications to real sequences are considered and we show how our results can be used to detect the potential biological relationships between real sequences.

Computing Methodologies↗